{"size":9451,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 15;\nname = \"15v2 4 2 1 1 4 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-14 I y] (1 (I Sin[x])^9 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^9) + Exp[-12 I y] (3 (I Sin[x])^10 Cos[x]^5 + 3 (I Sin[x])^5 Cos[x]^10 + 4 (I Sin[x])^9 Cos[x]^6 + 4 (I Sin[x])^6 Cos[x]^9 + 1 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^4 + 6 (I Sin[x])^8 Cos[x]^7 + 6 (I Sin[x])^7 Cos[x]^8) + Exp[-10 I y] (43 (I Sin[x])^8 Cos[x]^7 + 43 (I Sin[x])^7 Cos[x]^8 + 16 (I Sin[x])^10 Cos[x]^5 + 16 (I Sin[x])^5 Cos[x]^10 + 26 (I Sin[x])^9 Cos[x]^6 + 26 (I Sin[x])^6 Cos[x]^9 + 5 (I Sin[x])^11 Cos[x]^4 + 5 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^3 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^3) + Exp[-8 I y] (109 (I Sin[x])^9 Cos[x]^6 + 109 (I Sin[x])^6 Cos[x]^9 + 129 (I Sin[x])^8 Cos[x]^7 + 129 (I Sin[x])^7 Cos[x]^8 + 71 (I Sin[x])^5 Cos[x]^10 + 71 (I Sin[x])^10 Cos[x]^5 + 39 (I Sin[x])^11 Cos[x]^4 + 39 (I Sin[x])^4 Cos[x]^11 + 14 (I Sin[x])^3 Cos[x]^12 + 14 (I Sin[x])^12 Cos[x]^3 + 2 (I Sin[x])^2 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^2) + Exp[-6 I y] (348 (I Sin[x])^7 Cos[x]^8 + 348 (I Sin[x])^8 Cos[x]^7 + 297 (I Sin[x])^9 Cos[x]^6 + 297 (I Sin[x])^6 Cos[x]^9 + 105 (I Sin[x])^11 Cos[x]^4 + 105 (I Sin[x])^4 Cos[x]^11 + 190 (I Sin[x])^10 Cos[x]^5 + 190 (I Sin[x])^5 Cos[x]^10 + 45 (I Sin[x])^12 Cos[x]^3 + 45 (I Sin[x])^3 Cos[x]^12 + 14 (I Sin[x])^2 Cos[x]^13 + 14 (I Sin[x])^13 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^1) + Exp[-4 I y] (783 (I Sin[x])^8 Cos[x]^7 + 783 (I Sin[x])^7 Cos[x]^8 + 383 (I Sin[x])^10 Cos[x]^5 + 383 (I Sin[x])^5 Cos[x]^10 + 624 (I Sin[x])^9 Cos[x]^6 + 624 (I Sin[x])^6 Cos[x]^9 + 158 (I Sin[x])^4 Cos[x]^11 + 158 (I Sin[x])^11 Cos[x]^4 + 44 (I Sin[x])^12 Cos[x]^3 + 44 (I Sin[x])^3 Cos[x]^12 + 9 (I Sin[x])^13 Cos[x]^2 + 9 (I Sin[x])^2 Cos[x]^13 + 1 (I Sin[x])^1 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^1) + Exp[-2 I y] (1072 (I Sin[x])^8 Cos[x]^7 + 1072 (I Sin[x])^7 Cos[x]^8 + 861 (I Sin[x])^6 Cos[x]^9 + 861 (I Sin[x])^9 Cos[x]^6 + 591 (I Sin[x])^10 Cos[x]^5 + 591 (I Sin[x])^5 Cos[x]^10 + 314 (I Sin[x])^11 Cos[x]^4 + 314 (I Sin[x])^4 Cos[x]^11 + 124 (I Sin[x])^12 Cos[x]^3 + 124 (I Sin[x])^3 Cos[x]^12 + 33 (I Sin[x])^13 Cos[x]^2 + 33 (I Sin[x])^2 Cos[x]^13 + 7 (I Sin[x])^1 Cos[x]^14 + 7 (I Sin[x])^14 Cos[x]^1 + 1 Cos[x]^15 + 1 (I Sin[x])^15) + Exp[0 I y] (1490 (I Sin[x])^7 Cos[x]^8 + 1490 (I Sin[x])^8 Cos[x]^7 + 1077 (I Sin[x])^6 Cos[x]^9 + 1077 (I Sin[x])^9 Cos[x]^6 + 226 (I Sin[x])^11 Cos[x]^4 + 226 (I Sin[x])^4 Cos[x]^11 + 563 (I Sin[x])^10 Cos[x]^5 + 563 (I Sin[x])^5 Cos[x]^10 + 64 (I Sin[x])^12 Cos[x]^3 + 64 (I Sin[x])^3 Cos[x]^12 + 11 (I Sin[x])^2 Cos[x]^13 + 11 (I Sin[x])^13 Cos[x]^2 + 1 (I Sin[x])^14 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^14) + Exp[2 I y] (919 (I Sin[x])^9 Cos[x]^6 + 919 (I Sin[x])^6 Cos[x]^9 + 1102 (I Sin[x])^7 Cos[x]^8 + 1102 (I Sin[x])^8 Cos[x]^7 + 576 (I Sin[x])^10 Cos[x]^5 + 576 (I Sin[x])^5 Cos[x]^10 + 275 (I Sin[x])^11 Cos[x]^4 + 275 (I Sin[x])^4 Cos[x]^11 + 99 (I Sin[x])^12 Cos[x]^3 + 99 (I Sin[x])^3 Cos[x]^12 + 28 (I Sin[x])^2 Cos[x]^13 + 28 (I Sin[x])^13 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^1) + Exp[4 I y] (864 (I Sin[x])^8 Cos[x]^7 + 864 (I Sin[x])^7 Cos[x]^8 + 638 (I Sin[x])^6 Cos[x]^9 + 638 (I Sin[x])^9 Cos[x]^6 + 343 (I Sin[x])^5 Cos[x]^10 + 343 (I Sin[x])^10 Cos[x]^5 + 123 (I Sin[x])^4 Cos[x]^11 + 123 (I Sin[x])^11 Cos[x]^4 + 30 (I Sin[x])^3 Cos[x]^12 + 30 (I Sin[x])^12 Cos[x]^3 + 4 (I Sin[x])^13 Cos[x]^2 + 4 (I Sin[x])^2 Cos[x]^13) + Exp[6 I y] (399 (I Sin[x])^8 Cos[x]^7 + 399 (I Sin[x])^7 Cos[x]^8 + 184 (I Sin[x])^10 Cos[x]^5 + 184 (I Sin[x])^5 Cos[x]^10 + 294 (I Sin[x])^6 Cos[x]^9 + 294 (I Sin[x])^9 Cos[x]^6 + 90 (I Sin[x])^4 Cos[x]^11 + 90 (I Sin[x])^11 Cos[x]^4 + 30 (I Sin[x])^3 Cos[x]^12 + 30 (I Sin[x])^12 Cos[x]^3 + 4 (I Sin[x])^2 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^2) + Exp[8 I y] (153 (I Sin[x])^7 Cos[x]^8 + 153 (I Sin[x])^8 Cos[x]^7 + 65 (I Sin[x])^5 Cos[x]^10 + 65 (I Sin[x])^10 Cos[x]^5 + 117 (I Sin[x])^6 Cos[x]^9 + 117 (I Sin[x])^9 Cos[x]^6 + 25 (I Sin[x])^11 Cos[x]^4 + 25 (I Sin[x])^4 Cos[x]^11 + 4 (I Sin[x])^12 Cos[x]^3 + 4 (I Sin[x])^3 Cos[x]^12) + Exp[10 I y] (38 (I Sin[x])^7 Cos[x]^8 + 38 (I Sin[x])^8 Cos[x]^7 + 33 (I Sin[x])^9 Cos[x]^6 + 33 (I Sin[x])^6 Cos[x]^9 + 16 (I Sin[x])^5 Cos[x]^10 + 16 (I Sin[x])^10 Cos[x]^5 + 4 (I Sin[x])^4 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^4) + Exp[12 I y] (5 (I Sin[x])^6 Cos[x]^9 + 5 (I Sin[x])^9 Cos[x]^6 + 7 (I Sin[x])^8 Cos[x]^7 + 7 (I Sin[x])^7 Cos[x]^8 + 2 (I Sin[x])^10 Cos[x]^5 + 2 (I Sin[x])^5 Cos[x]^10) + Exp[14 I y] (1 (I Sin[x])^8 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^8))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-14 I y] (1 (I Sin[x])^9 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^9) + Exp[-12 I y] (3 (I Sin[x])^10 Cos[x]^5 + 3 (I Sin[x])^5 Cos[x]^10 + 4 (I Sin[x])^9 Cos[x]^6 + 4 (I Sin[x])^6 Cos[x]^9 + 1 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^4 + 6 (I Sin[x])^8 Cos[x]^7 + 6 (I Sin[x])^7 Cos[x]^8) + Exp[-10 I y] (43 (I Sin[x])^8 Cos[x]^7 + 43 (I Sin[x])^7 Cos[x]^8 + 16 (I Sin[x])^10 Cos[x]^5 + 16 (I Sin[x])^5 Cos[x]^10 + 26 (I Sin[x])^9 Cos[x]^6 + 26 (I Sin[x])^6 Cos[x]^9 + 5 (I Sin[x])^11 Cos[x]^4 + 5 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^3 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^3) + Exp[-8 I y] (109 (I Sin[x])^9 Cos[x]^6 + 109 (I Sin[x])^6 Cos[x]^9 + 129 (I Sin[x])^8 Cos[x]^7 + 129 (I Sin[x])^7 Cos[x]^8 + 71 (I Sin[x])^5 Cos[x]^10 + 71 (I Sin[x])^10 Cos[x]^5 + 39 (I Sin[x])^11 Cos[x]^4 + 39 (I Sin[x])^4 Cos[x]^11 + 14 (I Sin[x])^3 Cos[x]^12 + 14 (I Sin[x])^12 Cos[x]^3 + 2 (I Sin[x])^2 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^2) + Exp[-6 I y] (348 (I Sin[x])^7 Cos[x]^8 + 348 (I Sin[x])^8 Cos[x]^7 + 297 (I Sin[x])^9 Cos[x]^6 + 297 (I Sin[x])^6 Cos[x]^9 + 105 (I Sin[x])^11 Cos[x]^4 + 105 (I Sin[x])^4 Cos[x]^11 + 190 (I Sin[x])^10 Cos[x]^5 + 190 (I Sin[x])^5 Cos[x]^10 + 45 (I Sin[x])^12 Cos[x]^3 + 45 (I Sin[x])^3 Cos[x]^12 + 14 (I Sin[x])^2 Cos[x]^13 + 14 (I Sin[x])^13 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^1) + Exp[-4 I y] (783 (I Sin[x])^8 Cos[x]^7 + 783 (I Sin[x])^7 Cos[x]^8 + 383 (I Sin[x])^10 Cos[x]^5 + 383 (I Sin[x])^5 Cos[x]^10 + 624 (I Sin[x])^9 Cos[x]^6 + 624 (I Sin[x])^6 Cos[x]^9 + 158 (I Sin[x])^4 Cos[x]^11 + 158 (I Sin[x])^11 Cos[x]^4 + 44 (I Sin[x])^12 Cos[x]^3 + 44 (I Sin[x])^3 Cos[x]^12 + 9 (I Sin[x])^13 Cos[x]^2 + 9 (I Sin[x])^2 Cos[x]^13 + 1 (I Sin[x])^1 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^1) + Exp[-2 I y] (1072 (I Sin[x])^8 Cos[x]^7 + 1072 (I Sin[x])^7 Cos[x]^8 + 861 (I Sin[x])^6 Cos[x]^9 + 861 (I Sin[x])^9 Cos[x]^6 + 591 (I Sin[x])^10 Cos[x]^5 + 591 (I Sin[x])^5 Cos[x]^10 + 314 (I Sin[x])^11 Cos[x]^4 + 314 (I Sin[x])^4 Cos[x]^11 + 124 (I Sin[x])^12 Cos[x]^3 + 124 (I Sin[x])^3 Cos[x]^12 + 33 (I Sin[x])^13 Cos[x]^2 + 33 (I Sin[x])^2 Cos[x]^13 + 7 (I Sin[x])^1 Cos[x]^14 + 7 (I Sin[x])^14 Cos[x]^1 + 1 Cos[x]^15 + 1 (I Sin[x])^15) + Exp[0 I y] (1490 (I Sin[x])^7 Cos[x]^8 + 1490 (I Sin[x])^8 Cos[x]^7 + 1077 (I Sin[x])^6 Cos[x]^9 + 1077 (I Sin[x])^9 Cos[x]^6 + 226 (I Sin[x])^11 Cos[x]^4 + 226 (I Sin[x])^4 Cos[x]^11 + 563 (I Sin[x])^10 Cos[x]^5 + 563 (I Sin[x])^5 Cos[x]^10 + 64 (I Sin[x])^12 Cos[x]^3 + 64 (I Sin[x])^3 Cos[x]^12 + 11 (I Sin[x])^2 Cos[x]^13 + 11 (I Sin[x])^13 Cos[x]^2 + 1 (I Sin[x])^14 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^14) + Exp[2 I y] (919 (I Sin[x])^9 Cos[x]^6 + 919 (I Sin[x])^6 Cos[x]^9 + 1102 (I Sin[x])^7 Cos[x]^8 + 1102 (I Sin[x])^8 Cos[x]^7 + 576 (I Sin[x])^10 Cos[x]^5 + 576 (I Sin[x])^5 Cos[x]^10 + 275 (I Sin[x])^11 Cos[x]^4 + 275 (I Sin[x])^4 Cos[x]^11 + 99 (I Sin[x])^12 Cos[x]^3 + 99 (I Sin[x])^3 Cos[x]^12 + 28 (I Sin[x])^2 Cos[x]^13 + 28 (I Sin[x])^13 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^1) + Exp[4 I y] (864 (I Sin[x])^8 Cos[x]^7 + 864 (I Sin[x])^7 Cos[x]^8 + 638 (I Sin[x])^6 Cos[x]^9 + 638 (I Sin[x])^9 Cos[x]^6 + 343 (I Sin[x])^5 Cos[x]^10 + 343 (I Sin[x])^10 Cos[x]^5 + 123 (I Sin[x])^4 Cos[x]^11 + 123 (I Sin[x])^11 Cos[x]^4 + 30 (I Sin[x])^3 Cos[x]^12 + 30 (I Sin[x])^12 Cos[x]^3 + 4 (I Sin[x])^13 Cos[x]^2 + 4 (I Sin[x])^2 Cos[x]^13) + Exp[6 I y] (399 (I Sin[x])^8 Cos[x]^7 + 399 (I Sin[x])^7 Cos[x]^8 + 184 (I Sin[x])^10 Cos[x]^5 + 184 (I Sin[x])^5 Cos[x]^10 + 294 (I Sin[x])^6 Cos[x]^9 + 294 (I Sin[x])^9 Cos[x]^6 + 90 (I Sin[x])^4 Cos[x]^11 + 90 (I Sin[x])^11 Cos[x]^4 + 30 (I Sin[x])^3 Cos[x]^12 + 30 (I Sin[x])^12 Cos[x]^3 + 4 (I Sin[x])^2 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^2) + Exp[8 I y] (153 (I Sin[x])^7 Cos[x]^8 + 153 (I Sin[x])^8 Cos[x]^7 + 65 (I Sin[x])^5 Cos[x]^10 + 65 (I Sin[x])^10 Cos[x]^5 + 117 (I Sin[x])^6 Cos[x]^9 + 117 (I Sin[x])^9 Cos[x]^6 + 25 (I Sin[x])^11 Cos[x]^4 + 25 (I Sin[x])^4 Cos[x]^11 + 4 (I Sin[x])^12 Cos[x]^3 + 4 (I Sin[x])^3 Cos[x]^12) + Exp[10 I y] (38 (I Sin[x])^7 Cos[x]^8 + 38 (I Sin[x])^8 Cos[x]^7 + 33 (I Sin[x])^9 Cos[x]^6 + 33 (I Sin[x])^6 Cos[x]^9 + 16 (I Sin[x])^5 Cos[x]^10 + 16 (I Sin[x])^10 Cos[x]^5 + 4 (I Sin[x])^4 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^4) + Exp[12 I y] (5 (I Sin[x])^6 Cos[x]^9 + 5 (I Sin[x])^9 Cos[x]^6 + 7 (I Sin[x])^8 Cos[x]^7 + 7 (I Sin[x])^7 Cos[x]^8 + 2 (I Sin[x])^10 Cos[x]^5 + 2 (I Sin[x])^5 Cos[x]^10) + Exp[14 I y] (1 (I Sin[x])^8 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^8));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":630.0666666667,"max_line_length":4504,"alphanum_fraction":0.5004761401} {"size":7477,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 13;\nname = \"13v2 1 2 1 1 5 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-12 I y] (1 (I Sin[x])^7 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^7) + Exp[-10 I y] (4 (I Sin[x])^8 Cos[x]^5 + 4 (I Sin[x])^5 Cos[x]^8 + 2 (I Sin[x])^7 Cos[x]^6 + 2 (I Sin[x])^6 Cos[x]^7 + 4 (I Sin[x])^4 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^3) + Exp[-8 I y] (23 (I Sin[x])^6 Cos[x]^7 + 23 (I Sin[x])^7 Cos[x]^6 + 22 (I Sin[x])^8 Cos[x]^5 + 22 (I Sin[x])^5 Cos[x]^8 + 13 (I Sin[x])^4 Cos[x]^9 + 13 (I Sin[x])^9 Cos[x]^4 + 6 (I Sin[x])^3 Cos[x]^10 + 6 (I Sin[x])^10 Cos[x]^3 + 2 (I Sin[x])^2 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^2) + Exp[-6 I y] (87 (I Sin[x])^7 Cos[x]^6 + 87 (I Sin[x])^6 Cos[x]^7 + 44 (I Sin[x])^4 Cos[x]^9 + 44 (I Sin[x])^9 Cos[x]^4 + 14 (I Sin[x])^3 Cos[x]^10 + 14 (I Sin[x])^10 Cos[x]^3 + 72 (I Sin[x])^5 Cos[x]^8 + 72 (I Sin[x])^8 Cos[x]^5 + 3 (I Sin[x])^2 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^2) + Exp[-4 I y] (145 (I Sin[x])^5 Cos[x]^8 + 145 (I Sin[x])^8 Cos[x]^5 + 89 (I Sin[x])^9 Cos[x]^4 + 89 (I Sin[x])^4 Cos[x]^9 + 202 (I Sin[x])^7 Cos[x]^6 + 202 (I Sin[x])^6 Cos[x]^7 + 43 (I Sin[x])^10 Cos[x]^3 + 43 (I Sin[x])^3 Cos[x]^10 + 13 (I Sin[x])^2 Cos[x]^11 + 13 (I Sin[x])^11 Cos[x]^2 + 3 (I Sin[x])^1 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^1) + Exp[-2 I y] (378 (I Sin[x])^6 Cos[x]^7 + 378 (I Sin[x])^7 Cos[x]^6 + 256 (I Sin[x])^5 Cos[x]^8 + 256 (I Sin[x])^8 Cos[x]^5 + 111 (I Sin[x])^4 Cos[x]^9 + 111 (I Sin[x])^9 Cos[x]^4 + 38 (I Sin[x])^3 Cos[x]^10 + 38 (I Sin[x])^10 Cos[x]^3 + 8 (I Sin[x])^2 Cos[x]^11 + 8 (I Sin[x])^11 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^1) + Exp[0 I y] (179 (I Sin[x])^4 Cos[x]^9 + 179 (I Sin[x])^9 Cos[x]^4 + 293 (I Sin[x])^8 Cos[x]^5 + 293 (I Sin[x])^5 Cos[x]^8 + 346 (I Sin[x])^6 Cos[x]^7 + 346 (I Sin[x])^7 Cos[x]^6 + 75 (I Sin[x])^10 Cos[x]^3 + 75 (I Sin[x])^3 Cos[x]^10 + 25 (I Sin[x])^11 Cos[x]^2 + 25 (I Sin[x])^2 Cos[x]^11 + 5 (I Sin[x])^1 Cos[x]^12 + 5 (I Sin[x])^12 Cos[x]^1 + 1 Cos[x]^13 + 1 (I Sin[x])^13) + Exp[2 I y] (368 (I Sin[x])^7 Cos[x]^6 + 368 (I Sin[x])^6 Cos[x]^7 + 127 (I Sin[x])^4 Cos[x]^9 + 127 (I Sin[x])^9 Cos[x]^4 + 248 (I Sin[x])^5 Cos[x]^8 + 248 (I Sin[x])^8 Cos[x]^5 + 40 (I Sin[x])^3 Cos[x]^10 + 40 (I Sin[x])^10 Cos[x]^3 + 8 (I Sin[x])^2 Cos[x]^11 + 8 (I Sin[x])^11 Cos[x]^2 + 1 (I Sin[x])^12 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^12) + Exp[4 I y] (49 (I Sin[x])^3 Cos[x]^10 + 49 (I Sin[x])^10 Cos[x]^3 + 189 (I Sin[x])^7 Cos[x]^6 + 189 (I Sin[x])^6 Cos[x]^7 + 146 (I Sin[x])^5 Cos[x]^8 + 146 (I Sin[x])^8 Cos[x]^5 + 93 (I Sin[x])^9 Cos[x]^4 + 93 (I Sin[x])^4 Cos[x]^9 + 15 (I Sin[x])^2 Cos[x]^11 + 15 (I Sin[x])^11 Cos[x]^2 + 3 (I Sin[x])^1 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^1) + Exp[6 I y] (78 (I Sin[x])^8 Cos[x]^5 + 78 (I Sin[x])^5 Cos[x]^8 + 82 (I Sin[x])^6 Cos[x]^7 + 82 (I Sin[x])^7 Cos[x]^6 + 42 (I Sin[x])^9 Cos[x]^4 + 42 (I Sin[x])^4 Cos[x]^9 + 15 (I Sin[x])^3 Cos[x]^10 + 15 (I Sin[x])^10 Cos[x]^3 + 3 (I Sin[x])^11 Cos[x]^2 + 3 (I Sin[x])^2 Cos[x]^11) + Exp[8 I y] (11 (I Sin[x])^4 Cos[x]^9 + 11 (I Sin[x])^9 Cos[x]^4 + 31 (I Sin[x])^6 Cos[x]^7 + 31 (I Sin[x])^7 Cos[x]^6 + 1 (I Sin[x])^2 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^2 + 20 (I Sin[x])^8 Cos[x]^5 + 20 (I Sin[x])^5 Cos[x]^8 + 3 (I Sin[x])^3 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^3) + Exp[10 I y] (7 (I Sin[x])^7 Cos[x]^6 + 7 (I Sin[x])^6 Cos[x]^7 + 2 (I Sin[x])^9 Cos[x]^4 + 2 (I Sin[x])^4 Cos[x]^9 + 2 (I Sin[x])^8 Cos[x]^5 + 2 (I Sin[x])^5 Cos[x]^8 + 1 (I Sin[x])^10 Cos[x]^3 + 1 (I Sin[x])^3 Cos[x]^10) + Exp[12 I y] (1 (I Sin[x])^5 Cos[x]^8 + 1 (I Sin[x])^8 Cos[x]^5))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-12 I y] (1 (I Sin[x])^7 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^7) + Exp[-10 I y] (4 (I Sin[x])^8 Cos[x]^5 + 4 (I Sin[x])^5 Cos[x]^8 + 2 (I Sin[x])^7 Cos[x]^6 + 2 (I Sin[x])^6 Cos[x]^7 + 4 (I Sin[x])^4 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^3) + Exp[-8 I y] (23 (I Sin[x])^6 Cos[x]^7 + 23 (I Sin[x])^7 Cos[x]^6 + 22 (I Sin[x])^8 Cos[x]^5 + 22 (I Sin[x])^5 Cos[x]^8 + 13 (I Sin[x])^4 Cos[x]^9 + 13 (I Sin[x])^9 Cos[x]^4 + 6 (I Sin[x])^3 Cos[x]^10 + 6 (I Sin[x])^10 Cos[x]^3 + 2 (I Sin[x])^2 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^2) + Exp[-6 I y] (87 (I Sin[x])^7 Cos[x]^6 + 87 (I Sin[x])^6 Cos[x]^7 + 44 (I Sin[x])^4 Cos[x]^9 + 44 (I Sin[x])^9 Cos[x]^4 + 14 (I Sin[x])^3 Cos[x]^10 + 14 (I Sin[x])^10 Cos[x]^3 + 72 (I Sin[x])^5 Cos[x]^8 + 72 (I Sin[x])^8 Cos[x]^5 + 3 (I Sin[x])^2 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^2) + Exp[-4 I y] (145 (I Sin[x])^5 Cos[x]^8 + 145 (I Sin[x])^8 Cos[x]^5 + 89 (I Sin[x])^9 Cos[x]^4 + 89 (I Sin[x])^4 Cos[x]^9 + 202 (I Sin[x])^7 Cos[x]^6 + 202 (I Sin[x])^6 Cos[x]^7 + 43 (I Sin[x])^10 Cos[x]^3 + 43 (I Sin[x])^3 Cos[x]^10 + 13 (I Sin[x])^2 Cos[x]^11 + 13 (I Sin[x])^11 Cos[x]^2 + 3 (I Sin[x])^1 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^1) + Exp[-2 I y] (378 (I Sin[x])^6 Cos[x]^7 + 378 (I Sin[x])^7 Cos[x]^6 + 256 (I Sin[x])^5 Cos[x]^8 + 256 (I Sin[x])^8 Cos[x]^5 + 111 (I Sin[x])^4 Cos[x]^9 + 111 (I Sin[x])^9 Cos[x]^4 + 38 (I Sin[x])^3 Cos[x]^10 + 38 (I Sin[x])^10 Cos[x]^3 + 8 (I Sin[x])^2 Cos[x]^11 + 8 (I Sin[x])^11 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^1) + Exp[0 I y] (179 (I Sin[x])^4 Cos[x]^9 + 179 (I Sin[x])^9 Cos[x]^4 + 293 (I Sin[x])^8 Cos[x]^5 + 293 (I Sin[x])^5 Cos[x]^8 + 346 (I Sin[x])^6 Cos[x]^7 + 346 (I Sin[x])^7 Cos[x]^6 + 75 (I Sin[x])^10 Cos[x]^3 + 75 (I Sin[x])^3 Cos[x]^10 + 25 (I Sin[x])^11 Cos[x]^2 + 25 (I Sin[x])^2 Cos[x]^11 + 5 (I Sin[x])^1 Cos[x]^12 + 5 (I Sin[x])^12 Cos[x]^1 + 1 Cos[x]^13 + 1 (I Sin[x])^13) + Exp[2 I y] (368 (I Sin[x])^7 Cos[x]^6 + 368 (I Sin[x])^6 Cos[x]^7 + 127 (I Sin[x])^4 Cos[x]^9 + 127 (I Sin[x])^9 Cos[x]^4 + 248 (I Sin[x])^5 Cos[x]^8 + 248 (I Sin[x])^8 Cos[x]^5 + 40 (I Sin[x])^3 Cos[x]^10 + 40 (I Sin[x])^10 Cos[x]^3 + 8 (I Sin[x])^2 Cos[x]^11 + 8 (I Sin[x])^11 Cos[x]^2 + 1 (I Sin[x])^12 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^12) + Exp[4 I y] (49 (I Sin[x])^3 Cos[x]^10 + 49 (I Sin[x])^10 Cos[x]^3 + 189 (I Sin[x])^7 Cos[x]^6 + 189 (I Sin[x])^6 Cos[x]^7 + 146 (I Sin[x])^5 Cos[x]^8 + 146 (I Sin[x])^8 Cos[x]^5 + 93 (I Sin[x])^9 Cos[x]^4 + 93 (I Sin[x])^4 Cos[x]^9 + 15 (I Sin[x])^2 Cos[x]^11 + 15 (I Sin[x])^11 Cos[x]^2 + 3 (I Sin[x])^1 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^1) + Exp[6 I y] (78 (I Sin[x])^8 Cos[x]^5 + 78 (I Sin[x])^5 Cos[x]^8 + 82 (I Sin[x])^6 Cos[x]^7 + 82 (I Sin[x])^7 Cos[x]^6 + 42 (I Sin[x])^9 Cos[x]^4 + 42 (I Sin[x])^4 Cos[x]^9 + 15 (I Sin[x])^3 Cos[x]^10 + 15 (I Sin[x])^10 Cos[x]^3 + 3 (I Sin[x])^11 Cos[x]^2 + 3 (I Sin[x])^2 Cos[x]^11) + Exp[8 I y] (11 (I Sin[x])^4 Cos[x]^9 + 11 (I Sin[x])^9 Cos[x]^4 + 31 (I Sin[x])^6 Cos[x]^7 + 31 (I Sin[x])^7 Cos[x]^6 + 1 (I Sin[x])^2 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^2 + 20 (I Sin[x])^8 Cos[x]^5 + 20 (I Sin[x])^5 Cos[x]^8 + 3 (I Sin[x])^3 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^3) + Exp[10 I y] (7 (I Sin[x])^7 Cos[x]^6 + 7 (I Sin[x])^6 Cos[x]^7 + 2 (I Sin[x])^9 Cos[x]^4 + 2 (I Sin[x])^4 Cos[x]^9 + 2 (I Sin[x])^8 Cos[x]^5 + 2 (I Sin[x])^5 Cos[x]^8 + 1 (I Sin[x])^10 Cos[x]^3 + 1 (I Sin[x])^3 Cos[x]^10) + Exp[12 I y] (1 (I Sin[x])^5 Cos[x]^8 + 1 (I Sin[x])^8 Cos[x]^5));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":498.4666666667,"max_line_length":3517,"alphanum_fraction":0.4924434934} {"size":5944,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"(* Content-type: application\/vnd.wolfram.mathematica *)\r\n\r\n(*** Wolfram Notebook File ***)\r\n(* http:\/\/www.wolfram.com\/nb *)\r\n\r\n(* CreatedBy='Mathematica 11.3' *)\r\n\r\n(*CacheID: 234*)\r\n(* Internal cache information:\r\nNotebookFileLineBreakTest\r\nNotebookFileLineBreakTest\r\nNotebookDataPosition[ 158, 7]\r\nNotebookDataLength[ 5587, 149]\r\nNotebookOptionsPosition[ 3457, 99]\r\nNotebookOutlinePosition[ 5325, 147]\r\nCellTagsIndexPosition[ 5282, 144]\r\nWindowTitle->OutputWeights\r\nWindowFrame->Normal*)\r\n\r\n(* Beginning of 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If True it also output the \\\r\nSoS weights.\", \"synonyms\" -> {}, \"tabletags\" -> {}, \"title\" -> \r\n \"OutputWeights\", \"titlemodifier\" -> \"\", \"windowtitle\" -> \"OutputWeights\", \r\n \"type\" -> \"Symbol\", \"uri\" -> \"DTITools\/ref\/OutputWeights\"}},\r\nCellContext->\"Global`\",\r\nFrontEndVersion->\"11.3 for Microsoft Windows (64-bit) (March 6, 2018)\",\r\nStyleDefinitions->Notebook[{\r\n Cell[\r\n StyleData[\r\n StyleDefinitions -> FrontEnd`FileName[{\"Wolfram\"}, \"Reference.nb\"]]], \r\n Cell[\r\n StyleData[\"Input\"], CellContext -> \"Global`\"], \r\n Cell[\r\n StyleData[\"Output\"], CellContext -> \"Global`\"]}, Visible -> False, \r\n FrontEndVersion -> \"11.3 for Microsoft Windows (64-bit) (March 6, 2018)\", \r\n StyleDefinitions -> \"Default.nb\"]\r\n]\r\n(* End of Notebook Content *)\r\n\r\n(* Internal cache information 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(I Sin[x])^7 Cos[x]^8 + 4 (I Sin[x])^6 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^6 + 2 (I Sin[x])^5 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^5) + Exp[-10 I y] (33 (I Sin[x])^6 Cos[x]^9 + 33 (I Sin[x])^9 Cos[x]^6 + 39 (I Sin[x])^8 Cos[x]^7 + 39 (I Sin[x])^7 Cos[x]^8 + 15 (I Sin[x])^5 Cos[x]^10 + 15 (I Sin[x])^10 Cos[x]^5 + 4 (I Sin[x])^4 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^4) + Exp[-8 I y] (124 (I Sin[x])^9 Cos[x]^6 + 124 (I Sin[x])^6 Cos[x]^9 + 164 (I Sin[x])^8 Cos[x]^7 + 164 (I Sin[x])^7 Cos[x]^8 + 56 (I Sin[x])^5 Cos[x]^10 + 56 (I Sin[x])^10 Cos[x]^5 + 18 (I Sin[x])^4 Cos[x]^11 + 18 (I Sin[x])^11 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^3) + Exp[-6 I y] (189 (I Sin[x])^5 Cos[x]^10 + 189 (I Sin[x])^10 Cos[x]^5 + 394 (I Sin[x])^7 Cos[x]^8 + 394 (I Sin[x])^8 Cos[x]^7 + 295 (I Sin[x])^9 Cos[x]^6 + 295 (I Sin[x])^6 Cos[x]^9 + 89 (I Sin[x])^4 Cos[x]^11 + 89 (I Sin[x])^11 Cos[x]^4 + 30 (I Sin[x])^3 Cos[x]^12 + 30 (I Sin[x])^12 Cos[x]^3 + 4 (I Sin[x])^2 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^2) + Exp[-4 I y] (878 (I Sin[x])^8 Cos[x]^7 + 878 (I Sin[x])^7 Cos[x]^8 + 624 (I Sin[x])^6 Cos[x]^9 + 624 (I Sin[x])^9 Cos[x]^6 + 343 (I Sin[x])^5 Cos[x]^10 + 343 (I Sin[x])^10 Cos[x]^5 + 124 (I Sin[x])^4 Cos[x]^11 + 124 (I Sin[x])^11 Cos[x]^4 + 30 (I Sin[x])^3 Cos[x]^12 + 30 (I Sin[x])^12 Cos[x]^3 + 3 (I Sin[x])^2 Cos[x]^13 + 3 (I Sin[x])^13 Cos[x]^2) + Exp[-2 I y] (290 (I Sin[x])^4 Cos[x]^11 + 290 (I Sin[x])^11 Cos[x]^4 + 1084 (I Sin[x])^8 Cos[x]^7 + 1084 (I Sin[x])^7 Cos[x]^8 + 914 (I Sin[x])^6 Cos[x]^9 + 914 (I Sin[x])^9 Cos[x]^6 + 582 (I Sin[x])^10 Cos[x]^5 + 582 (I Sin[x])^5 Cos[x]^10 + 101 (I Sin[x])^3 Cos[x]^12 + 101 (I Sin[x])^12 Cos[x]^3 + 28 (I Sin[x])^2 Cos[x]^13 + 28 (I Sin[x])^13 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^1) + Exp[0 I y] (1095 (I Sin[x])^9 Cos[x]^6 + 1095 (I Sin[x])^6 Cos[x]^9 + 1416 (I Sin[x])^7 Cos[x]^8 + 1416 (I Sin[x])^8 Cos[x]^7 + 595 (I Sin[x])^5 Cos[x]^10 + 595 (I Sin[x])^10 Cos[x]^5 + 244 (I Sin[x])^4 Cos[x]^11 + 244 (I Sin[x])^11 Cos[x]^4 + 68 (I Sin[x])^3 Cos[x]^12 + 68 (I Sin[x])^12 Cos[x]^3 + 13 (I Sin[x])^13 Cos[x]^2 + 13 (I Sin[x])^2 Cos[x]^13 + 1 (I Sin[x])^1 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^1) + Exp[2 I y] (125 (I Sin[x])^3 Cos[x]^12 + 125 (I Sin[x])^12 Cos[x]^3 + 1104 (I Sin[x])^7 Cos[x]^8 + 1104 (I Sin[x])^8 Cos[x]^7 + 574 (I Sin[x])^5 Cos[x]^10 + 574 (I Sin[x])^10 Cos[x]^5 + 865 (I Sin[x])^9 Cos[x]^6 + 865 (I Sin[x])^6 Cos[x]^9 + 293 (I Sin[x])^11 Cos[x]^4 + 293 (I Sin[x])^4 Cos[x]^11 + 34 (I Sin[x])^2 Cos[x]^13 + 34 (I Sin[x])^13 Cos[x]^2 + 7 (I Sin[x])^1 Cos[x]^14 + 7 (I Sin[x])^14 Cos[x]^1 + 1 Cos[x]^15 + 1 (I Sin[x])^15) + Exp[4 I y] (356 (I Sin[x])^10 Cos[x]^5 + 356 (I Sin[x])^5 Cos[x]^10 + 838 (I Sin[x])^7 Cos[x]^8 + 838 (I Sin[x])^8 Cos[x]^7 + 605 (I Sin[x])^9 Cos[x]^6 + 605 (I Sin[x])^6 Cos[x]^9 + 149 (I Sin[x])^11 Cos[x]^4 + 149 (I Sin[x])^4 Cos[x]^11 + 45 (I Sin[x])^12 Cos[x]^3 + 45 (I Sin[x])^3 Cos[x]^12 + 8 (I Sin[x])^2 Cos[x]^13 + 8 (I Sin[x])^13 Cos[x]^2 + 1 (I Sin[x])^14 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^14) + Exp[6 I y] (107 (I Sin[x])^4 Cos[x]^11 + 107 (I Sin[x])^11 Cos[x]^4 + 299 (I Sin[x])^6 Cos[x]^9 + 299 (I Sin[x])^9 Cos[x]^6 + 353 (I Sin[x])^8 Cos[x]^7 + 353 (I Sin[x])^7 Cos[x]^8 + 191 (I Sin[x])^10 Cos[x]^5 + 191 (I Sin[x])^5 Cos[x]^10 + 12 (I Sin[x])^2 Cos[x]^13 + 12 (I Sin[x])^13 Cos[x]^2 + 37 (I Sin[x])^3 Cos[x]^12 + 37 (I Sin[x])^12 Cos[x]^3 + 2 (I Sin[x])^1 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^1) + Exp[8 I y] (34 (I Sin[x])^11 Cos[x]^4 + 34 (I Sin[x])^4 Cos[x]^11 + 120 (I Sin[x])^6 Cos[x]^9 + 120 (I Sin[x])^9 Cos[x]^6 + 124 (I Sin[x])^8 Cos[x]^7 + 124 (I Sin[x])^7 Cos[x]^8 + 74 (I Sin[x])^10 Cos[x]^5 + 74 (I Sin[x])^5 Cos[x]^10 + 10 (I Sin[x])^3 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^3 + 2 (I Sin[x])^13 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^13) + Exp[10 I y] (6 (I Sin[x])^3 Cos[x]^12 + 6 (I Sin[x])^12 Cos[x]^3 + 22 (I Sin[x])^5 Cos[x]^10 + 22 (I Sin[x])^10 Cos[x]^5 + 28 (I Sin[x])^7 Cos[x]^8 + 28 (I Sin[x])^8 Cos[x]^7 + 25 (I Sin[x])^9 Cos[x]^6 + 25 (I Sin[x])^6 Cos[x]^9 + 9 (I Sin[x])^11 Cos[x]^4 + 9 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^2 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^2) + Exp[12 I y] (4 (I Sin[x])^10 Cos[x]^5 + 4 (I Sin[x])^5 Cos[x]^10 + 1 (I Sin[x])^12 Cos[x]^3 + 1 (I Sin[x])^3 Cos[x]^12 + 4 (I Sin[x])^7 Cos[x]^8 + 4 (I Sin[x])^8 Cos[x]^7 + 2 (I Sin[x])^9 Cos[x]^6 + 2 (I Sin[x])^6 Cos[x]^9 + 3 (I Sin[x])^11 Cos[x]^4 + 3 (I Sin[x])^4 Cos[x]^11) + Exp[14 I y] (1 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^4))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-14 I y] (1 (I Sin[x])^7 Cos[x]^8 + 1 (I Sin[x])^8 Cos[x]^7) + Exp[-12 I y] (8 (I Sin[x])^8 Cos[x]^7 + 8 (I Sin[x])^7 Cos[x]^8 + 4 (I Sin[x])^6 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^6 + 2 (I Sin[x])^5 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^5) + Exp[-10 I y] (33 (I Sin[x])^6 Cos[x]^9 + 33 (I Sin[x])^9 Cos[x]^6 + 39 (I Sin[x])^8 Cos[x]^7 + 39 (I Sin[x])^7 Cos[x]^8 + 15 (I Sin[x])^5 Cos[x]^10 + 15 (I Sin[x])^10 Cos[x]^5 + 4 (I Sin[x])^4 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^4) + Exp[-8 I y] (124 (I Sin[x])^9 Cos[x]^6 + 124 (I Sin[x])^6 Cos[x]^9 + 164 (I Sin[x])^8 Cos[x]^7 + 164 (I Sin[x])^7 Cos[x]^8 + 56 (I Sin[x])^5 Cos[x]^10 + 56 (I Sin[x])^10 Cos[x]^5 + 18 (I Sin[x])^4 Cos[x]^11 + 18 (I Sin[x])^11 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^3) + Exp[-6 I y] (189 (I Sin[x])^5 Cos[x]^10 + 189 (I Sin[x])^10 Cos[x]^5 + 394 (I Sin[x])^7 Cos[x]^8 + 394 (I Sin[x])^8 Cos[x]^7 + 295 (I Sin[x])^9 Cos[x]^6 + 295 (I Sin[x])^6 Cos[x]^9 + 89 (I Sin[x])^4 Cos[x]^11 + 89 (I Sin[x])^11 Cos[x]^4 + 30 (I Sin[x])^3 Cos[x]^12 + 30 (I Sin[x])^12 Cos[x]^3 + 4 (I Sin[x])^2 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^2) + Exp[-4 I y] (878 (I Sin[x])^8 Cos[x]^7 + 878 (I Sin[x])^7 Cos[x]^8 + 624 (I Sin[x])^6 Cos[x]^9 + 624 (I Sin[x])^9 Cos[x]^6 + 343 (I Sin[x])^5 Cos[x]^10 + 343 (I Sin[x])^10 Cos[x]^5 + 124 (I Sin[x])^4 Cos[x]^11 + 124 (I Sin[x])^11 Cos[x]^4 + 30 (I Sin[x])^3 Cos[x]^12 + 30 (I Sin[x])^12 Cos[x]^3 + 3 (I Sin[x])^2 Cos[x]^13 + 3 (I Sin[x])^13 Cos[x]^2) + Exp[-2 I y] (290 (I Sin[x])^4 Cos[x]^11 + 290 (I Sin[x])^11 Cos[x]^4 + 1084 (I Sin[x])^8 Cos[x]^7 + 1084 (I Sin[x])^7 Cos[x]^8 + 914 (I Sin[x])^6 Cos[x]^9 + 914 (I Sin[x])^9 Cos[x]^6 + 582 (I Sin[x])^10 Cos[x]^5 + 582 (I Sin[x])^5 Cos[x]^10 + 101 (I Sin[x])^3 Cos[x]^12 + 101 (I Sin[x])^12 Cos[x]^3 + 28 (I Sin[x])^2 Cos[x]^13 + 28 (I Sin[x])^13 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^1) + Exp[0 I y] (1095 (I Sin[x])^9 Cos[x]^6 + 1095 (I Sin[x])^6 Cos[x]^9 + 1416 (I Sin[x])^7 Cos[x]^8 + 1416 (I Sin[x])^8 Cos[x]^7 + 595 (I Sin[x])^5 Cos[x]^10 + 595 (I Sin[x])^10 Cos[x]^5 + 244 (I Sin[x])^4 Cos[x]^11 + 244 (I Sin[x])^11 Cos[x]^4 + 68 (I Sin[x])^3 Cos[x]^12 + 68 (I Sin[x])^12 Cos[x]^3 + 13 (I Sin[x])^13 Cos[x]^2 + 13 (I Sin[x])^2 Cos[x]^13 + 1 (I Sin[x])^1 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^1) + Exp[2 I y] (125 (I Sin[x])^3 Cos[x]^12 + 125 (I Sin[x])^12 Cos[x]^3 + 1104 (I Sin[x])^7 Cos[x]^8 + 1104 (I Sin[x])^8 Cos[x]^7 + 574 (I Sin[x])^5 Cos[x]^10 + 574 (I Sin[x])^10 Cos[x]^5 + 865 (I Sin[x])^9 Cos[x]^6 + 865 (I Sin[x])^6 Cos[x]^9 + 293 (I Sin[x])^11 Cos[x]^4 + 293 (I Sin[x])^4 Cos[x]^11 + 34 (I Sin[x])^2 Cos[x]^13 + 34 (I Sin[x])^13 Cos[x]^2 + 7 (I Sin[x])^1 Cos[x]^14 + 7 (I Sin[x])^14 Cos[x]^1 + 1 Cos[x]^15 + 1 (I Sin[x])^15) + Exp[4 I y] (356 (I Sin[x])^10 Cos[x]^5 + 356 (I Sin[x])^5 Cos[x]^10 + 838 (I Sin[x])^7 Cos[x]^8 + 838 (I Sin[x])^8 Cos[x]^7 + 605 (I Sin[x])^9 Cos[x]^6 + 605 (I Sin[x])^6 Cos[x]^9 + 149 (I Sin[x])^11 Cos[x]^4 + 149 (I Sin[x])^4 Cos[x]^11 + 45 (I Sin[x])^12 Cos[x]^3 + 45 (I Sin[x])^3 Cos[x]^12 + 8 (I Sin[x])^2 Cos[x]^13 + 8 (I Sin[x])^13 Cos[x]^2 + 1 (I Sin[x])^14 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^14) + Exp[6 I y] (107 (I Sin[x])^4 Cos[x]^11 + 107 (I Sin[x])^11 Cos[x]^4 + 299 (I Sin[x])^6 Cos[x]^9 + 299 (I Sin[x])^9 Cos[x]^6 + 353 (I Sin[x])^8 Cos[x]^7 + 353 (I Sin[x])^7 Cos[x]^8 + 191 (I Sin[x])^10 Cos[x]^5 + 191 (I Sin[x])^5 Cos[x]^10 + 12 (I Sin[x])^2 Cos[x]^13 + 12 (I Sin[x])^13 Cos[x]^2 + 37 (I Sin[x])^3 Cos[x]^12 + 37 (I Sin[x])^12 Cos[x]^3 + 2 (I Sin[x])^1 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^1) + Exp[8 I y] (34 (I Sin[x])^11 Cos[x]^4 + 34 (I Sin[x])^4 Cos[x]^11 + 120 (I Sin[x])^6 Cos[x]^9 + 120 (I Sin[x])^9 Cos[x]^6 + 124 (I Sin[x])^8 Cos[x]^7 + 124 (I Sin[x])^7 Cos[x]^8 + 74 (I Sin[x])^10 Cos[x]^5 + 74 (I Sin[x])^5 Cos[x]^10 + 10 (I Sin[x])^3 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^3 + 2 (I Sin[x])^13 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^13) + Exp[10 I y] (6 (I Sin[x])^3 Cos[x]^12 + 6 (I Sin[x])^12 Cos[x]^3 + 22 (I Sin[x])^5 Cos[x]^10 + 22 (I Sin[x])^10 Cos[x]^5 + 28 (I Sin[x])^7 Cos[x]^8 + 28 (I Sin[x])^8 Cos[x]^7 + 25 (I Sin[x])^9 Cos[x]^6 + 25 (I Sin[x])^6 Cos[x]^9 + 9 (I Sin[x])^11 Cos[x]^4 + 9 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^2 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^2) + Exp[12 I y] (4 (I Sin[x])^10 Cos[x]^5 + 4 (I Sin[x])^5 Cos[x]^10 + 1 (I Sin[x])^12 Cos[x]^3 + 1 (I Sin[x])^3 Cos[x]^12 + 4 (I Sin[x])^7 Cos[x]^8 + 4 (I Sin[x])^8 Cos[x]^7 + 2 (I Sin[x])^9 Cos[x]^6 + 2 (I Sin[x])^6 Cos[x]^9 + 3 (I Sin[x])^11 Cos[x]^4 + 3 (I Sin[x])^4 Cos[x]^11) + Exp[14 I y] (1 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^4));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":645.2666666667,"max_line_length":4616,"alphanum_fraction":0.5004649241} {"size":9245,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 15;\nname = \"15v3 1 2 2 1 1 1 1 1 2\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-14 I y] (1 (I Sin[x])^7 Cos[x]^8 + 1 (I Sin[x])^8 Cos[x]^7) + Exp[-12 I y] (6 (I Sin[x])^6 Cos[x]^9 + 6 (I Sin[x])^9 Cos[x]^6 + 1 (I Sin[x])^7 Cos[x]^8 + 1 (I Sin[x])^8 Cos[x]^7 + 6 (I Sin[x])^5 Cos[x]^10 + 6 (I Sin[x])^10 Cos[x]^5 + 1 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^4) + Exp[-10 I y] (31 (I Sin[x])^6 Cos[x]^9 + 31 (I Sin[x])^9 Cos[x]^6 + 55 (I Sin[x])^8 Cos[x]^7 + 55 (I Sin[x])^7 Cos[x]^8 + 5 (I Sin[x])^10 Cos[x]^5 + 5 (I Sin[x])^5 Cos[x]^10) + Exp[-8 I y] (120 (I Sin[x])^7 Cos[x]^8 + 120 (I Sin[x])^8 Cos[x]^7 + 114 (I Sin[x])^6 Cos[x]^9 + 114 (I Sin[x])^9 Cos[x]^6 + 82 (I Sin[x])^5 Cos[x]^10 + 82 (I Sin[x])^10 Cos[x]^5 + 41 (I Sin[x])^4 Cos[x]^11 + 41 (I Sin[x])^11 Cos[x]^4 + 7 (I Sin[x])^3 Cos[x]^12 + 7 (I Sin[x])^12 Cos[x]^3) + Exp[-6 I y] (133 (I Sin[x])^5 Cos[x]^10 + 133 (I Sin[x])^10 Cos[x]^5 + 520 (I Sin[x])^7 Cos[x]^8 + 520 (I Sin[x])^8 Cos[x]^7 + 327 (I Sin[x])^9 Cos[x]^6 + 327 (I Sin[x])^6 Cos[x]^9 + 21 (I Sin[x])^11 Cos[x]^4 + 21 (I Sin[x])^4 Cos[x]^11) + Exp[-4 I y] (759 (I Sin[x])^8 Cos[x]^7 + 759 (I Sin[x])^7 Cos[x]^8 + 383 (I Sin[x])^5 Cos[x]^10 + 383 (I Sin[x])^10 Cos[x]^5 + 598 (I Sin[x])^6 Cos[x]^9 + 598 (I Sin[x])^9 Cos[x]^6 + 183 (I Sin[x])^4 Cos[x]^11 + 183 (I Sin[x])^11 Cos[x]^4 + 68 (I Sin[x])^3 Cos[x]^12 + 68 (I Sin[x])^12 Cos[x]^3 + 11 (I Sin[x])^2 Cos[x]^13 + 11 (I Sin[x])^13 Cos[x]^2) + Exp[-2 I y] (176 (I Sin[x])^4 Cos[x]^11 + 176 (I Sin[x])^11 Cos[x]^4 + 1312 (I Sin[x])^8 Cos[x]^7 + 1312 (I Sin[x])^7 Cos[x]^8 + 986 (I Sin[x])^6 Cos[x]^9 + 986 (I Sin[x])^9 Cos[x]^6 + 502 (I Sin[x])^10 Cos[x]^5 + 502 (I Sin[x])^5 Cos[x]^10 + 27 (I Sin[x])^12 Cos[x]^3 + 27 (I Sin[x])^3 Cos[x]^12) + Exp[0 I y] (1022 (I Sin[x])^9 Cos[x]^6 + 1022 (I Sin[x])^6 Cos[x]^9 + 1280 (I Sin[x])^7 Cos[x]^8 + 1280 (I Sin[x])^8 Cos[x]^7 + 638 (I Sin[x])^5 Cos[x]^10 + 638 (I Sin[x])^10 Cos[x]^5 + 122 (I Sin[x])^3 Cos[x]^12 + 122 (I Sin[x])^12 Cos[x]^3 + 38 (I Sin[x])^2 Cos[x]^13 + 38 (I Sin[x])^13 Cos[x]^2 + 326 (I Sin[x])^4 Cos[x]^11 + 326 (I Sin[x])^11 Cos[x]^4 + 6 (I Sin[x])^1 Cos[x]^14 + 6 (I Sin[x])^14 Cos[x]^1) + Exp[2 I y] (84 (I Sin[x])^3 Cos[x]^12 + 84 (I Sin[x])^12 Cos[x]^3 + 1157 (I Sin[x])^7 Cos[x]^8 + 1157 (I Sin[x])^8 Cos[x]^7 + 908 (I Sin[x])^9 Cos[x]^6 + 908 (I Sin[x])^6 Cos[x]^9 + 583 (I Sin[x])^5 Cos[x]^10 + 583 (I Sin[x])^10 Cos[x]^5 + 258 (I Sin[x])^4 Cos[x]^11 + 258 (I Sin[x])^11 Cos[x]^4 + 13 (I Sin[x])^2 Cos[x]^13 + 13 (I Sin[x])^13 Cos[x]^2) + Exp[4 I y] (720 (I Sin[x])^8 Cos[x]^7 + 720 (I Sin[x])^7 Cos[x]^8 + 389 (I Sin[x])^5 Cos[x]^10 + 389 (I Sin[x])^10 Cos[x]^5 + 586 (I Sin[x])^6 Cos[x]^9 + 586 (I Sin[x])^9 Cos[x]^6 + 195 (I Sin[x])^4 Cos[x]^11 + 195 (I Sin[x])^11 Cos[x]^4 + 82 (I Sin[x])^3 Cos[x]^12 + 82 (I Sin[x])^12 Cos[x]^3 + 23 (I Sin[x])^2 Cos[x]^13 + 23 (I Sin[x])^13 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^14 + 6 (I Sin[x])^14 Cos[x]^1 + 1 Cos[x]^15 + 1 (I Sin[x])^15) + Exp[6 I y] (105 (I Sin[x])^4 Cos[x]^11 + 105 (I Sin[x])^11 Cos[x]^4 + 297 (I Sin[x])^6 Cos[x]^9 + 297 (I Sin[x])^9 Cos[x]^6 + 365 (I Sin[x])^8 Cos[x]^7 + 365 (I Sin[x])^7 Cos[x]^8 + 181 (I Sin[x])^10 Cos[x]^5 + 181 (I Sin[x])^5 Cos[x]^10 + 39 (I Sin[x])^3 Cos[x]^12 + 39 (I Sin[x])^12 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^13 + 12 (I Sin[x])^13 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^1) + Exp[8 I y] (101 (I Sin[x])^9 Cos[x]^6 + 101 (I Sin[x])^6 Cos[x]^9 + 45 (I Sin[x])^4 Cos[x]^11 + 45 (I Sin[x])^11 Cos[x]^4 + 120 (I Sin[x])^7 Cos[x]^8 + 120 (I Sin[x])^8 Cos[x]^7 + 71 (I Sin[x])^5 Cos[x]^10 + 71 (I Sin[x])^10 Cos[x]^5 + 19 (I Sin[x])^3 Cos[x]^12 + 19 (I Sin[x])^12 Cos[x]^3 + 7 (I Sin[x])^2 Cos[x]^13 + 7 (I Sin[x])^13 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^1) + Exp[10 I y] (6 (I Sin[x])^3 Cos[x]^12 + 6 (I Sin[x])^12 Cos[x]^3 + 26 (I Sin[x])^5 Cos[x]^10 + 26 (I Sin[x])^10 Cos[x]^5 + 22 (I Sin[x])^7 Cos[x]^8 + 22 (I Sin[x])^8 Cos[x]^7 + 25 (I Sin[x])^9 Cos[x]^6 + 25 (I Sin[x])^6 Cos[x]^9 + 11 (I Sin[x])^11 Cos[x]^4 + 11 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^2 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^2) + Exp[12 I y] (4 (I Sin[x])^10 Cos[x]^5 + 4 (I Sin[x])^5 Cos[x]^10 + 1 (I Sin[x])^3 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^3 + 3 (I Sin[x])^8 Cos[x]^7 + 3 (I Sin[x])^7 Cos[x]^8 + 4 (I Sin[x])^9 Cos[x]^6 + 4 (I Sin[x])^6 Cos[x]^9 + 2 (I Sin[x])^4 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^4) + Exp[14 I y] (1 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^4))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-14 I y] (1 (I Sin[x])^7 Cos[x]^8 + 1 (I Sin[x])^8 Cos[x]^7) + Exp[-12 I y] (6 (I Sin[x])^6 Cos[x]^9 + 6 (I Sin[x])^9 Cos[x]^6 + 1 (I Sin[x])^7 Cos[x]^8 + 1 (I Sin[x])^8 Cos[x]^7 + 6 (I Sin[x])^5 Cos[x]^10 + 6 (I Sin[x])^10 Cos[x]^5 + 1 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^4) + Exp[-10 I y] (31 (I Sin[x])^6 Cos[x]^9 + 31 (I Sin[x])^9 Cos[x]^6 + 55 (I Sin[x])^8 Cos[x]^7 + 55 (I Sin[x])^7 Cos[x]^8 + 5 (I Sin[x])^10 Cos[x]^5 + 5 (I Sin[x])^5 Cos[x]^10) + Exp[-8 I y] (120 (I Sin[x])^7 Cos[x]^8 + 120 (I Sin[x])^8 Cos[x]^7 + 114 (I Sin[x])^6 Cos[x]^9 + 114 (I Sin[x])^9 Cos[x]^6 + 82 (I Sin[x])^5 Cos[x]^10 + 82 (I Sin[x])^10 Cos[x]^5 + 41 (I Sin[x])^4 Cos[x]^11 + 41 (I Sin[x])^11 Cos[x]^4 + 7 (I Sin[x])^3 Cos[x]^12 + 7 (I Sin[x])^12 Cos[x]^3) + Exp[-6 I y] (133 (I Sin[x])^5 Cos[x]^10 + 133 (I Sin[x])^10 Cos[x]^5 + 520 (I Sin[x])^7 Cos[x]^8 + 520 (I Sin[x])^8 Cos[x]^7 + 327 (I Sin[x])^9 Cos[x]^6 + 327 (I Sin[x])^6 Cos[x]^9 + 21 (I Sin[x])^11 Cos[x]^4 + 21 (I Sin[x])^4 Cos[x]^11) + Exp[-4 I y] (759 (I Sin[x])^8 Cos[x]^7 + 759 (I Sin[x])^7 Cos[x]^8 + 383 (I Sin[x])^5 Cos[x]^10 + 383 (I Sin[x])^10 Cos[x]^5 + 598 (I Sin[x])^6 Cos[x]^9 + 598 (I Sin[x])^9 Cos[x]^6 + 183 (I Sin[x])^4 Cos[x]^11 + 183 (I Sin[x])^11 Cos[x]^4 + 68 (I Sin[x])^3 Cos[x]^12 + 68 (I Sin[x])^12 Cos[x]^3 + 11 (I Sin[x])^2 Cos[x]^13 + 11 (I Sin[x])^13 Cos[x]^2) + Exp[-2 I y] (176 (I Sin[x])^4 Cos[x]^11 + 176 (I Sin[x])^11 Cos[x]^4 + 1312 (I Sin[x])^8 Cos[x]^7 + 1312 (I Sin[x])^7 Cos[x]^8 + 986 (I Sin[x])^6 Cos[x]^9 + 986 (I Sin[x])^9 Cos[x]^6 + 502 (I Sin[x])^10 Cos[x]^5 + 502 (I Sin[x])^5 Cos[x]^10 + 27 (I Sin[x])^12 Cos[x]^3 + 27 (I Sin[x])^3 Cos[x]^12) + Exp[0 I y] (1022 (I Sin[x])^9 Cos[x]^6 + 1022 (I Sin[x])^6 Cos[x]^9 + 1280 (I Sin[x])^7 Cos[x]^8 + 1280 (I Sin[x])^8 Cos[x]^7 + 638 (I Sin[x])^5 Cos[x]^10 + 638 (I Sin[x])^10 Cos[x]^5 + 122 (I Sin[x])^3 Cos[x]^12 + 122 (I Sin[x])^12 Cos[x]^3 + 38 (I Sin[x])^2 Cos[x]^13 + 38 (I Sin[x])^13 Cos[x]^2 + 326 (I Sin[x])^4 Cos[x]^11 + 326 (I Sin[x])^11 Cos[x]^4 + 6 (I Sin[x])^1 Cos[x]^14 + 6 (I Sin[x])^14 Cos[x]^1) + Exp[2 I y] (84 (I Sin[x])^3 Cos[x]^12 + 84 (I Sin[x])^12 Cos[x]^3 + 1157 (I Sin[x])^7 Cos[x]^8 + 1157 (I Sin[x])^8 Cos[x]^7 + 908 (I Sin[x])^9 Cos[x]^6 + 908 (I Sin[x])^6 Cos[x]^9 + 583 (I Sin[x])^5 Cos[x]^10 + 583 (I Sin[x])^10 Cos[x]^5 + 258 (I Sin[x])^4 Cos[x]^11 + 258 (I Sin[x])^11 Cos[x]^4 + 13 (I Sin[x])^2 Cos[x]^13 + 13 (I Sin[x])^13 Cos[x]^2) + Exp[4 I y] (720 (I Sin[x])^8 Cos[x]^7 + 720 (I Sin[x])^7 Cos[x]^8 + 389 (I Sin[x])^5 Cos[x]^10 + 389 (I Sin[x])^10 Cos[x]^5 + 586 (I Sin[x])^6 Cos[x]^9 + 586 (I Sin[x])^9 Cos[x]^6 + 195 (I Sin[x])^4 Cos[x]^11 + 195 (I Sin[x])^11 Cos[x]^4 + 82 (I Sin[x])^3 Cos[x]^12 + 82 (I Sin[x])^12 Cos[x]^3 + 23 (I Sin[x])^2 Cos[x]^13 + 23 (I Sin[x])^13 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^14 + 6 (I Sin[x])^14 Cos[x]^1 + 1 Cos[x]^15 + 1 (I Sin[x])^15) + Exp[6 I y] (105 (I Sin[x])^4 Cos[x]^11 + 105 (I Sin[x])^11 Cos[x]^4 + 297 (I Sin[x])^6 Cos[x]^9 + 297 (I Sin[x])^9 Cos[x]^6 + 365 (I Sin[x])^8 Cos[x]^7 + 365 (I Sin[x])^7 Cos[x]^8 + 181 (I Sin[x])^10 Cos[x]^5 + 181 (I Sin[x])^5 Cos[x]^10 + 39 (I Sin[x])^3 Cos[x]^12 + 39 (I Sin[x])^12 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^13 + 12 (I Sin[x])^13 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^1) + Exp[8 I y] (101 (I Sin[x])^9 Cos[x]^6 + 101 (I Sin[x])^6 Cos[x]^9 + 45 (I Sin[x])^4 Cos[x]^11 + 45 (I Sin[x])^11 Cos[x]^4 + 120 (I Sin[x])^7 Cos[x]^8 + 120 (I Sin[x])^8 Cos[x]^7 + 71 (I Sin[x])^5 Cos[x]^10 + 71 (I Sin[x])^10 Cos[x]^5 + 19 (I Sin[x])^3 Cos[x]^12 + 19 (I Sin[x])^12 Cos[x]^3 + 7 (I Sin[x])^2 Cos[x]^13 + 7 (I Sin[x])^13 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^1) + Exp[10 I y] (6 (I Sin[x])^3 Cos[x]^12 + 6 (I Sin[x])^12 Cos[x]^3 + 26 (I Sin[x])^5 Cos[x]^10 + 26 (I Sin[x])^10 Cos[x]^5 + 22 (I Sin[x])^7 Cos[x]^8 + 22 (I Sin[x])^8 Cos[x]^7 + 25 (I Sin[x])^9 Cos[x]^6 + 25 (I Sin[x])^6 Cos[x]^9 + 11 (I Sin[x])^11 Cos[x]^4 + 11 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^2 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^2) + Exp[12 I y] (4 (I Sin[x])^10 Cos[x]^5 + 4 (I Sin[x])^5 Cos[x]^10 + 1 (I Sin[x])^3 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^3 + 3 (I Sin[x])^8 Cos[x]^7 + 3 (I Sin[x])^7 Cos[x]^8 + 4 (I Sin[x])^9 Cos[x]^6 + 4 (I Sin[x])^6 Cos[x]^9 + 2 (I Sin[x])^4 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^4) + Exp[14 I y] (1 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^4));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":616.3333333333,"max_line_length":4398,"alphanum_fraction":0.5011357491} {"size":8023,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 14;\nname = \"14v1 3 1 4 4 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-13 I y] (1 (I Sin[x])^8 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^8) + Exp[-11 I y] (6 (I Sin[x])^7 Cos[x]^7 + 3 (I Sin[x])^5 Cos[x]^9 + 3 (I Sin[x])^9 Cos[x]^5 + 4 (I Sin[x])^8 Cos[x]^6 + 4 (I Sin[x])^6 Cos[x]^8 + 2 (I Sin[x])^10 Cos[x]^4 + 2 (I Sin[x])^4 Cos[x]^10 + 1 (I Sin[x])^11 Cos[x]^3 + 1 (I Sin[x])^3 Cos[x]^11) + Exp[-9 I y] (20 (I Sin[x])^9 Cos[x]^5 + 20 (I Sin[x])^5 Cos[x]^9 + 32 (I Sin[x])^7 Cos[x]^7 + 11 (I Sin[x])^10 Cos[x]^4 + 11 (I Sin[x])^4 Cos[x]^10 + 23 (I Sin[x])^6 Cos[x]^8 + 23 (I Sin[x])^8 Cos[x]^6 + 6 (I Sin[x])^11 Cos[x]^3 + 6 (I Sin[x])^3 Cos[x]^11 + 2 (I Sin[x])^12 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^12) + Exp[-7 I y] (101 (I Sin[x])^8 Cos[x]^6 + 101 (I Sin[x])^6 Cos[x]^8 + 73 (I Sin[x])^9 Cos[x]^5 + 73 (I Sin[x])^5 Cos[x]^9 + 104 (I Sin[x])^7 Cos[x]^7 + 40 (I Sin[x])^4 Cos[x]^10 + 40 (I Sin[x])^10 Cos[x]^4 + 14 (I Sin[x])^11 Cos[x]^3 + 14 (I Sin[x])^3 Cos[x]^11 + 5 (I Sin[x])^12 Cos[x]^2 + 5 (I Sin[x])^2 Cos[x]^12 + 1 (I Sin[x])^1 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^1) + Exp[-5 I y] (110 (I Sin[x])^10 Cos[x]^4 + 110 (I Sin[x])^4 Cos[x]^10 + 245 (I Sin[x])^6 Cos[x]^8 + 245 (I Sin[x])^8 Cos[x]^6 + 44 (I Sin[x])^11 Cos[x]^3 + 44 (I Sin[x])^3 Cos[x]^11 + 256 (I Sin[x])^7 Cos[x]^7 + 176 (I Sin[x])^9 Cos[x]^5 + 176 (I Sin[x])^5 Cos[x]^9 + 10 (I Sin[x])^2 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^1) + Exp[-3 I y] (309 (I Sin[x])^9 Cos[x]^5 + 309 (I Sin[x])^5 Cos[x]^9 + 508 (I Sin[x])^7 Cos[x]^7 + 439 (I Sin[x])^8 Cos[x]^6 + 439 (I Sin[x])^6 Cos[x]^8 + 169 (I Sin[x])^10 Cos[x]^4 + 169 (I Sin[x])^4 Cos[x]^10 + 82 (I Sin[x])^11 Cos[x]^3 + 82 (I Sin[x])^3 Cos[x]^11 + 27 (I Sin[x])^2 Cos[x]^12 + 27 (I Sin[x])^12 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^13 + 6 (I Sin[x])^13 Cos[x]^1 + 1 Cos[x]^14 + 1 (I Sin[x])^14) + Exp[-1 I y] (440 (I Sin[x])^9 Cos[x]^5 + 440 (I Sin[x])^5 Cos[x]^9 + 740 (I Sin[x])^7 Cos[x]^7 + 194 (I Sin[x])^10 Cos[x]^4 + 194 (I Sin[x])^4 Cos[x]^10 + 642 (I Sin[x])^6 Cos[x]^8 + 642 (I Sin[x])^8 Cos[x]^6 + 58 (I Sin[x])^3 Cos[x]^11 + 58 (I Sin[x])^11 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^12 + 12 (I Sin[x])^12 Cos[x]^2) + Exp[1 I y] (600 (I Sin[x])^8 Cos[x]^6 + 600 (I Sin[x])^6 Cos[x]^8 + 668 (I Sin[x])^7 Cos[x]^7 + 415 (I Sin[x])^9 Cos[x]^5 + 415 (I Sin[x])^5 Cos[x]^9 + 241 (I Sin[x])^10 Cos[x]^4 + 241 (I Sin[x])^4 Cos[x]^10 + 94 (I Sin[x])^3 Cos[x]^11 + 94 (I Sin[x])^11 Cos[x]^3 + 27 (I Sin[x])^2 Cos[x]^12 + 27 (I Sin[x])^12 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^13 + 5 (I Sin[x])^13 Cos[x]^1) + Exp[3 I y] (543 (I Sin[x])^8 Cos[x]^6 + 543 (I Sin[x])^6 Cos[x]^8 + 108 (I Sin[x])^4 Cos[x]^10 + 108 (I Sin[x])^10 Cos[x]^4 + 284 (I Sin[x])^9 Cos[x]^5 + 284 (I Sin[x])^5 Cos[x]^9 + 656 (I Sin[x])^7 Cos[x]^7 + 24 (I Sin[x])^3 Cos[x]^11 + 24 (I Sin[x])^11 Cos[x]^3) + Exp[5 I y] (270 (I Sin[x])^7 Cos[x]^7 + 193 (I Sin[x])^9 Cos[x]^5 + 193 (I Sin[x])^5 Cos[x]^9 + 248 (I Sin[x])^8 Cos[x]^6 + 248 (I Sin[x])^6 Cos[x]^8 + 94 (I Sin[x])^4 Cos[x]^10 + 94 (I Sin[x])^10 Cos[x]^4 + 37 (I Sin[x])^3 Cos[x]^11 + 37 (I Sin[x])^11 Cos[x]^3 + 8 (I Sin[x])^2 Cos[x]^12 + 8 (I Sin[x])^12 Cos[x]^2) + Exp[7 I y] (68 (I Sin[x])^9 Cos[x]^5 + 68 (I Sin[x])^5 Cos[x]^9 + 156 (I Sin[x])^7 Cos[x]^7 + 123 (I Sin[x])^8 Cos[x]^6 + 123 (I Sin[x])^6 Cos[x]^8 + 17 (I Sin[x])^4 Cos[x]^10 + 17 (I Sin[x])^10 Cos[x]^4) + Exp[9 I y] (27 (I Sin[x])^6 Cos[x]^8 + 27 (I Sin[x])^8 Cos[x]^6 + 15 (I Sin[x])^4 Cos[x]^10 + 15 (I Sin[x])^10 Cos[x]^4 + 28 (I Sin[x])^7 Cos[x]^7 + 18 (I Sin[x])^5 Cos[x]^9 + 18 (I Sin[x])^9 Cos[x]^5 + 4 (I Sin[x])^3 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^3) + Exp[11 I y] (7 (I Sin[x])^8 Cos[x]^6 + 7 (I Sin[x])^6 Cos[x]^8 + 8 (I Sin[x])^7 Cos[x]^7 + 2 (I Sin[x])^5 Cos[x]^9 + 2 (I Sin[x])^9 Cos[x]^5) + Exp[13 I y] (1 (I Sin[x])^5 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^5))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-13 I y] (1 (I Sin[x])^8 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^8) + Exp[-11 I y] (6 (I Sin[x])^7 Cos[x]^7 + 3 (I Sin[x])^5 Cos[x]^9 + 3 (I Sin[x])^9 Cos[x]^5 + 4 (I Sin[x])^8 Cos[x]^6 + 4 (I Sin[x])^6 Cos[x]^8 + 2 (I Sin[x])^10 Cos[x]^4 + 2 (I Sin[x])^4 Cos[x]^10 + 1 (I Sin[x])^11 Cos[x]^3 + 1 (I Sin[x])^3 Cos[x]^11) + Exp[-9 I y] (20 (I Sin[x])^9 Cos[x]^5 + 20 (I Sin[x])^5 Cos[x]^9 + 32 (I Sin[x])^7 Cos[x]^7 + 11 (I Sin[x])^10 Cos[x]^4 + 11 (I Sin[x])^4 Cos[x]^10 + 23 (I Sin[x])^6 Cos[x]^8 + 23 (I Sin[x])^8 Cos[x]^6 + 6 (I Sin[x])^11 Cos[x]^3 + 6 (I Sin[x])^3 Cos[x]^11 + 2 (I Sin[x])^12 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^12) + Exp[-7 I y] (101 (I Sin[x])^8 Cos[x]^6 + 101 (I Sin[x])^6 Cos[x]^8 + 73 (I Sin[x])^9 Cos[x]^5 + 73 (I Sin[x])^5 Cos[x]^9 + 104 (I Sin[x])^7 Cos[x]^7 + 40 (I Sin[x])^4 Cos[x]^10 + 40 (I Sin[x])^10 Cos[x]^4 + 14 (I Sin[x])^11 Cos[x]^3 + 14 (I Sin[x])^3 Cos[x]^11 + 5 (I Sin[x])^12 Cos[x]^2 + 5 (I Sin[x])^2 Cos[x]^12 + 1 (I Sin[x])^1 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^1) + Exp[-5 I y] (110 (I Sin[x])^10 Cos[x]^4 + 110 (I Sin[x])^4 Cos[x]^10 + 245 (I Sin[x])^6 Cos[x]^8 + 245 (I Sin[x])^8 Cos[x]^6 + 44 (I Sin[x])^11 Cos[x]^3 + 44 (I Sin[x])^3 Cos[x]^11 + 256 (I Sin[x])^7 Cos[x]^7 + 176 (I Sin[x])^9 Cos[x]^5 + 176 (I Sin[x])^5 Cos[x]^9 + 10 (I Sin[x])^2 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^1) + Exp[-3 I y] (309 (I Sin[x])^9 Cos[x]^5 + 309 (I Sin[x])^5 Cos[x]^9 + 508 (I Sin[x])^7 Cos[x]^7 + 439 (I Sin[x])^8 Cos[x]^6 + 439 (I Sin[x])^6 Cos[x]^8 + 169 (I Sin[x])^10 Cos[x]^4 + 169 (I Sin[x])^4 Cos[x]^10 + 82 (I Sin[x])^11 Cos[x]^3 + 82 (I Sin[x])^3 Cos[x]^11 + 27 (I Sin[x])^2 Cos[x]^12 + 27 (I Sin[x])^12 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^13 + 6 (I Sin[x])^13 Cos[x]^1 + 1 Cos[x]^14 + 1 (I Sin[x])^14) + Exp[-1 I y] (440 (I Sin[x])^9 Cos[x]^5 + 440 (I Sin[x])^5 Cos[x]^9 + 740 (I Sin[x])^7 Cos[x]^7 + 194 (I Sin[x])^10 Cos[x]^4 + 194 (I Sin[x])^4 Cos[x]^10 + 642 (I Sin[x])^6 Cos[x]^8 + 642 (I Sin[x])^8 Cos[x]^6 + 58 (I Sin[x])^3 Cos[x]^11 + 58 (I Sin[x])^11 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^12 + 12 (I Sin[x])^12 Cos[x]^2) + Exp[1 I y] (600 (I Sin[x])^8 Cos[x]^6 + 600 (I Sin[x])^6 Cos[x]^8 + 668 (I Sin[x])^7 Cos[x]^7 + 415 (I Sin[x])^9 Cos[x]^5 + 415 (I Sin[x])^5 Cos[x]^9 + 241 (I Sin[x])^10 Cos[x]^4 + 241 (I Sin[x])^4 Cos[x]^10 + 94 (I Sin[x])^3 Cos[x]^11 + 94 (I Sin[x])^11 Cos[x]^3 + 27 (I Sin[x])^2 Cos[x]^12 + 27 (I Sin[x])^12 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^13 + 5 (I Sin[x])^13 Cos[x]^1) + Exp[3 I y] (543 (I Sin[x])^8 Cos[x]^6 + 543 (I Sin[x])^6 Cos[x]^8 + 108 (I Sin[x])^4 Cos[x]^10 + 108 (I Sin[x])^10 Cos[x]^4 + 284 (I Sin[x])^9 Cos[x]^5 + 284 (I Sin[x])^5 Cos[x]^9 + 656 (I Sin[x])^7 Cos[x]^7 + 24 (I Sin[x])^3 Cos[x]^11 + 24 (I Sin[x])^11 Cos[x]^3) + Exp[5 I y] (270 (I Sin[x])^7 Cos[x]^7 + 193 (I Sin[x])^9 Cos[x]^5 + 193 (I Sin[x])^5 Cos[x]^9 + 248 (I Sin[x])^8 Cos[x]^6 + 248 (I Sin[x])^6 Cos[x]^8 + 94 (I Sin[x])^4 Cos[x]^10 + 94 (I Sin[x])^10 Cos[x]^4 + 37 (I Sin[x])^3 Cos[x]^11 + 37 (I Sin[x])^11 Cos[x]^3 + 8 (I Sin[x])^2 Cos[x]^12 + 8 (I Sin[x])^12 Cos[x]^2) + Exp[7 I y] (68 (I Sin[x])^9 Cos[x]^5 + 68 (I Sin[x])^5 Cos[x]^9 + 156 (I Sin[x])^7 Cos[x]^7 + 123 (I Sin[x])^8 Cos[x]^6 + 123 (I Sin[x])^6 Cos[x]^8 + 17 (I Sin[x])^4 Cos[x]^10 + 17 (I Sin[x])^10 Cos[x]^4) + Exp[9 I y] (27 (I Sin[x])^6 Cos[x]^8 + 27 (I Sin[x])^8 Cos[x]^6 + 15 (I Sin[x])^4 Cos[x]^10 + 15 (I Sin[x])^10 Cos[x]^4 + 28 (I Sin[x])^7 Cos[x]^7 + 18 (I Sin[x])^5 Cos[x]^9 + 18 (I Sin[x])^9 Cos[x]^5 + 4 (I Sin[x])^3 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^3) + Exp[11 I y] (7 (I Sin[x])^8 Cos[x]^6 + 7 (I Sin[x])^6 Cos[x]^8 + 8 (I Sin[x])^7 Cos[x]^7 + 2 (I Sin[x])^5 Cos[x]^9 + 2 (I Sin[x])^9 Cos[x]^5) + Exp[13 I y] (1 (I Sin[x])^5 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^5));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":534.8666666667,"max_line_length":3791,"alphanum_fraction":0.4971955628} {"size":9919,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 16;\nname = \"16v8 3 3 2\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^5 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^5) + Exp[-13 I y] (4 (I Sin[x])^4 Cos[x]^12 + 4 (I Sin[x])^12 Cos[x]^4 + 3 (I Sin[x])^10 Cos[x]^6 + 3 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3 + 2 (I Sin[x])^9 Cos[x]^7 + 2 (I Sin[x])^7 Cos[x]^9 + 2 (I Sin[x])^8 Cos[x]^8 + 3 (I Sin[x])^5 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^5) + Exp[-11 I y] (12 (I Sin[x])^4 Cos[x]^12 + 12 (I Sin[x])^12 Cos[x]^4 + 30 (I Sin[x])^6 Cos[x]^10 + 30 (I Sin[x])^10 Cos[x]^6 + 17 (I Sin[x])^5 Cos[x]^11 + 17 (I Sin[x])^11 Cos[x]^5 + 28 (I Sin[x])^7 Cos[x]^9 + 28 (I Sin[x])^9 Cos[x]^7 + 26 (I Sin[x])^8 Cos[x]^8 + 4 (I Sin[x])^3 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^3 + 1 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^2) + Exp[-9 I y] (81 (I Sin[x])^5 Cos[x]^11 + 81 (I Sin[x])^11 Cos[x]^5 + 118 (I Sin[x])^9 Cos[x]^7 + 118 (I Sin[x])^7 Cos[x]^9 + 46 (I Sin[x])^4 Cos[x]^12 + 46 (I Sin[x])^12 Cos[x]^4 + 122 (I Sin[x])^8 Cos[x]^8 + 99 (I Sin[x])^6 Cos[x]^10 + 99 (I Sin[x])^10 Cos[x]^6 + 26 (I Sin[x])^3 Cos[x]^13 + 26 (I Sin[x])^13 Cos[x]^3 + 17 (I Sin[x])^2 Cos[x]^14 + 17 (I Sin[x])^14 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^15 + 6 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[-7 I y] (214 (I Sin[x])^5 Cos[x]^11 + 214 (I Sin[x])^11 Cos[x]^5 + 431 (I Sin[x])^7 Cos[x]^9 + 431 (I Sin[x])^9 Cos[x]^7 + 316 (I Sin[x])^6 Cos[x]^10 + 316 (I Sin[x])^10 Cos[x]^6 + 476 (I Sin[x])^8 Cos[x]^8 + 46 (I Sin[x])^3 Cos[x]^13 + 46 (I Sin[x])^13 Cos[x]^3 + 106 (I Sin[x])^4 Cos[x]^12 + 106 (I Sin[x])^12 Cos[x]^4 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[-5 I y] (699 (I Sin[x])^6 Cos[x]^10 + 699 (I Sin[x])^10 Cos[x]^6 + 886 (I Sin[x])^8 Cos[x]^8 + 318 (I Sin[x])^4 Cos[x]^12 + 318 (I Sin[x])^12 Cos[x]^4 + 168 (I Sin[x])^3 Cos[x]^13 + 168 (I Sin[x])^13 Cos[x]^3 + 829 (I Sin[x])^7 Cos[x]^9 + 829 (I Sin[x])^9 Cos[x]^7 + 486 (I Sin[x])^5 Cos[x]^11 + 486 (I Sin[x])^11 Cos[x]^5 + 52 (I Sin[x])^2 Cos[x]^14 + 52 (I Sin[x])^14 Cos[x]^2 + 8 (I Sin[x])^1 Cos[x]^15 + 8 (I Sin[x])^15 Cos[x]^1) + Exp[-3 I y] (332 (I Sin[x])^4 Cos[x]^12 + 332 (I Sin[x])^12 Cos[x]^4 + 1834 (I Sin[x])^8 Cos[x]^8 + 1256 (I Sin[x])^6 Cos[x]^10 + 1256 (I Sin[x])^10 Cos[x]^6 + 726 (I Sin[x])^5 Cos[x]^11 + 726 (I Sin[x])^11 Cos[x]^5 + 1667 (I Sin[x])^9 Cos[x]^7 + 1667 (I Sin[x])^7 Cos[x]^9 + 92 (I Sin[x])^3 Cos[x]^13 + 92 (I Sin[x])^13 Cos[x]^3 + 15 (I Sin[x])^2 Cos[x]^14 + 15 (I Sin[x])^14 Cos[x]^2) + Exp[-1 I y] (1054 (I Sin[x])^5 Cos[x]^11 + 1054 (I Sin[x])^11 Cos[x]^5 + 2029 (I Sin[x])^7 Cos[x]^9 + 2029 (I Sin[x])^9 Cos[x]^7 + 152 (I Sin[x])^3 Cos[x]^13 + 152 (I Sin[x])^13 Cos[x]^3 + 23 (I Sin[x])^2 Cos[x]^14 + 23 (I Sin[x])^14 Cos[x]^2 + 1569 (I Sin[x])^6 Cos[x]^10 + 1569 (I Sin[x])^10 Cos[x]^6 + 516 (I Sin[x])^4 Cos[x]^12 + 516 (I Sin[x])^12 Cos[x]^4 + 2184 (I Sin[x])^8 Cos[x]^8) + Exp[1 I y] (40 (I Sin[x])^3 Cos[x]^13 + 40 (I Sin[x])^13 Cos[x]^3 + 2410 (I Sin[x])^9 Cos[x]^7 + 2410 (I Sin[x])^7 Cos[x]^9 + 785 (I Sin[x])^5 Cos[x]^11 + 785 (I Sin[x])^11 Cos[x]^5 + 1600 (I Sin[x])^6 Cos[x]^10 + 1600 (I Sin[x])^10 Cos[x]^6 + 2740 (I Sin[x])^8 Cos[x]^8 + 230 (I Sin[x])^4 Cos[x]^12 + 230 (I Sin[x])^12 Cos[x]^4) + Exp[3 I y] (1305 (I Sin[x])^6 Cos[x]^10 + 1305 (I Sin[x])^10 Cos[x]^6 + 2050 (I Sin[x])^8 Cos[x]^8 + 190 (I Sin[x])^4 Cos[x]^12 + 190 (I Sin[x])^12 Cos[x]^4 + 30 (I Sin[x])^3 Cos[x]^13 + 30 (I Sin[x])^13 Cos[x]^3 + 1820 (I Sin[x])^7 Cos[x]^9 + 1820 (I Sin[x])^9 Cos[x]^7 + 635 (I Sin[x])^5 Cos[x]^11 + 635 (I Sin[x])^11 Cos[x]^5) + Exp[5 I y] (48 (I Sin[x])^4 Cos[x]^12 + 48 (I Sin[x])^12 Cos[x]^4 + 1510 (I Sin[x])^8 Cos[x]^8 + 709 (I Sin[x])^6 Cos[x]^10 + 709 (I Sin[x])^10 Cos[x]^6 + 1258 (I Sin[x])^7 Cos[x]^9 + 1258 (I Sin[x])^9 Cos[x]^7 + 233 (I Sin[x])^5 Cos[x]^11 + 233 (I Sin[x])^11 Cos[x]^5) + Exp[7 I y] (590 (I Sin[x])^7 Cos[x]^9 + 590 (I Sin[x])^9 Cos[x]^7 + 103 (I Sin[x])^5 Cos[x]^11 + 103 (I Sin[x])^11 Cos[x]^5 + 18 (I Sin[x])^4 Cos[x]^12 + 18 (I Sin[x])^12 Cos[x]^4 + 308 (I Sin[x])^6 Cos[x]^10 + 308 (I Sin[x])^10 Cos[x]^6 + 692 (I Sin[x])^8 Cos[x]^8) + Exp[9 I y] (26 (I Sin[x])^5 Cos[x]^11 + 26 (I Sin[x])^11 Cos[x]^5 + 205 (I Sin[x])^9 Cos[x]^7 + 205 (I Sin[x])^7 Cos[x]^9 + 272 (I Sin[x])^8 Cos[x]^8 + 88 (I Sin[x])^6 Cos[x]^10 + 88 (I Sin[x])^10 Cos[x]^6) + Exp[11 I y] (70 (I Sin[x])^8 Cos[x]^8 + 21 (I Sin[x])^6 Cos[x]^10 + 21 (I Sin[x])^10 Cos[x]^6 + 4 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^5 + 45 (I Sin[x])^7 Cos[x]^9 + 45 (I Sin[x])^9 Cos[x]^7) + Exp[13 I y] (5 (I Sin[x])^6 Cos[x]^10 + 5 (I Sin[x])^10 Cos[x]^6 + 6 (I Sin[x])^8 Cos[x]^8 + 7 (I Sin[x])^9 Cos[x]^7 + 7 (I Sin[x])^7 Cos[x]^9) + Exp[15 I y] (1 (I Sin[x])^9 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^9))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^5 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^5) + Exp[-13 I y] (4 (I Sin[x])^4 Cos[x]^12 + 4 (I Sin[x])^12 Cos[x]^4 + 3 (I Sin[x])^10 Cos[x]^6 + 3 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3 + 2 (I Sin[x])^9 Cos[x]^7 + 2 (I Sin[x])^7 Cos[x]^9 + 2 (I Sin[x])^8 Cos[x]^8 + 3 (I Sin[x])^5 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^5) + Exp[-11 I y] (12 (I Sin[x])^4 Cos[x]^12 + 12 (I Sin[x])^12 Cos[x]^4 + 30 (I Sin[x])^6 Cos[x]^10 + 30 (I Sin[x])^10 Cos[x]^6 + 17 (I Sin[x])^5 Cos[x]^11 + 17 (I Sin[x])^11 Cos[x]^5 + 28 (I Sin[x])^7 Cos[x]^9 + 28 (I Sin[x])^9 Cos[x]^7 + 26 (I Sin[x])^8 Cos[x]^8 + 4 (I Sin[x])^3 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^3 + 1 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^2) + Exp[-9 I y] (81 (I Sin[x])^5 Cos[x]^11 + 81 (I Sin[x])^11 Cos[x]^5 + 118 (I Sin[x])^9 Cos[x]^7 + 118 (I Sin[x])^7 Cos[x]^9 + 46 (I Sin[x])^4 Cos[x]^12 + 46 (I Sin[x])^12 Cos[x]^4 + 122 (I Sin[x])^8 Cos[x]^8 + 99 (I Sin[x])^6 Cos[x]^10 + 99 (I Sin[x])^10 Cos[x]^6 + 26 (I Sin[x])^3 Cos[x]^13 + 26 (I Sin[x])^13 Cos[x]^3 + 17 (I Sin[x])^2 Cos[x]^14 + 17 (I Sin[x])^14 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^15 + 6 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[-7 I y] (214 (I Sin[x])^5 Cos[x]^11 + 214 (I Sin[x])^11 Cos[x]^5 + 431 (I Sin[x])^7 Cos[x]^9 + 431 (I Sin[x])^9 Cos[x]^7 + 316 (I Sin[x])^6 Cos[x]^10 + 316 (I Sin[x])^10 Cos[x]^6 + 476 (I Sin[x])^8 Cos[x]^8 + 46 (I Sin[x])^3 Cos[x]^13 + 46 (I Sin[x])^13 Cos[x]^3 + 106 (I Sin[x])^4 Cos[x]^12 + 106 (I Sin[x])^12 Cos[x]^4 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[-5 I y] (699 (I Sin[x])^6 Cos[x]^10 + 699 (I Sin[x])^10 Cos[x]^6 + 886 (I Sin[x])^8 Cos[x]^8 + 318 (I Sin[x])^4 Cos[x]^12 + 318 (I Sin[x])^12 Cos[x]^4 + 168 (I Sin[x])^3 Cos[x]^13 + 168 (I Sin[x])^13 Cos[x]^3 + 829 (I Sin[x])^7 Cos[x]^9 + 829 (I Sin[x])^9 Cos[x]^7 + 486 (I Sin[x])^5 Cos[x]^11 + 486 (I Sin[x])^11 Cos[x]^5 + 52 (I Sin[x])^2 Cos[x]^14 + 52 (I Sin[x])^14 Cos[x]^2 + 8 (I Sin[x])^1 Cos[x]^15 + 8 (I Sin[x])^15 Cos[x]^1) + Exp[-3 I y] (332 (I Sin[x])^4 Cos[x]^12 + 332 (I Sin[x])^12 Cos[x]^4 + 1834 (I Sin[x])^8 Cos[x]^8 + 1256 (I Sin[x])^6 Cos[x]^10 + 1256 (I Sin[x])^10 Cos[x]^6 + 726 (I Sin[x])^5 Cos[x]^11 + 726 (I Sin[x])^11 Cos[x]^5 + 1667 (I Sin[x])^9 Cos[x]^7 + 1667 (I Sin[x])^7 Cos[x]^9 + 92 (I Sin[x])^3 Cos[x]^13 + 92 (I Sin[x])^13 Cos[x]^3 + 15 (I Sin[x])^2 Cos[x]^14 + 15 (I Sin[x])^14 Cos[x]^2) + Exp[-1 I y] (1054 (I Sin[x])^5 Cos[x]^11 + 1054 (I Sin[x])^11 Cos[x]^5 + 2029 (I Sin[x])^7 Cos[x]^9 + 2029 (I Sin[x])^9 Cos[x]^7 + 152 (I Sin[x])^3 Cos[x]^13 + 152 (I Sin[x])^13 Cos[x]^3 + 23 (I Sin[x])^2 Cos[x]^14 + 23 (I Sin[x])^14 Cos[x]^2 + 1569 (I Sin[x])^6 Cos[x]^10 + 1569 (I Sin[x])^10 Cos[x]^6 + 516 (I Sin[x])^4 Cos[x]^12 + 516 (I Sin[x])^12 Cos[x]^4 + 2184 (I Sin[x])^8 Cos[x]^8) + Exp[1 I y] (40 (I Sin[x])^3 Cos[x]^13 + 40 (I Sin[x])^13 Cos[x]^3 + 2410 (I Sin[x])^9 Cos[x]^7 + 2410 (I Sin[x])^7 Cos[x]^9 + 785 (I Sin[x])^5 Cos[x]^11 + 785 (I Sin[x])^11 Cos[x]^5 + 1600 (I Sin[x])^6 Cos[x]^10 + 1600 (I Sin[x])^10 Cos[x]^6 + 2740 (I Sin[x])^8 Cos[x]^8 + 230 (I Sin[x])^4 Cos[x]^12 + 230 (I Sin[x])^12 Cos[x]^4) + Exp[3 I y] (1305 (I Sin[x])^6 Cos[x]^10 + 1305 (I Sin[x])^10 Cos[x]^6 + 2050 (I Sin[x])^8 Cos[x]^8 + 190 (I Sin[x])^4 Cos[x]^12 + 190 (I Sin[x])^12 Cos[x]^4 + 30 (I Sin[x])^3 Cos[x]^13 + 30 (I Sin[x])^13 Cos[x]^3 + 1820 (I Sin[x])^7 Cos[x]^9 + 1820 (I Sin[x])^9 Cos[x]^7 + 635 (I Sin[x])^5 Cos[x]^11 + 635 (I Sin[x])^11 Cos[x]^5) + Exp[5 I y] (48 (I Sin[x])^4 Cos[x]^12 + 48 (I Sin[x])^12 Cos[x]^4 + 1510 (I Sin[x])^8 Cos[x]^8 + 709 (I Sin[x])^6 Cos[x]^10 + 709 (I Sin[x])^10 Cos[x]^6 + 1258 (I Sin[x])^7 Cos[x]^9 + 1258 (I Sin[x])^9 Cos[x]^7 + 233 (I Sin[x])^5 Cos[x]^11 + 233 (I Sin[x])^11 Cos[x]^5) + Exp[7 I y] (590 (I Sin[x])^7 Cos[x]^9 + 590 (I Sin[x])^9 Cos[x]^7 + 103 (I Sin[x])^5 Cos[x]^11 + 103 (I Sin[x])^11 Cos[x]^5 + 18 (I Sin[x])^4 Cos[x]^12 + 18 (I Sin[x])^12 Cos[x]^4 + 308 (I Sin[x])^6 Cos[x]^10 + 308 (I Sin[x])^10 Cos[x]^6 + 692 (I Sin[x])^8 Cos[x]^8) + Exp[9 I y] (26 (I Sin[x])^5 Cos[x]^11 + 26 (I Sin[x])^11 Cos[x]^5 + 205 (I Sin[x])^9 Cos[x]^7 + 205 (I Sin[x])^7 Cos[x]^9 + 272 (I Sin[x])^8 Cos[x]^8 + 88 (I Sin[x])^6 Cos[x]^10 + 88 (I Sin[x])^10 Cos[x]^6) + Exp[11 I y] (70 (I Sin[x])^8 Cos[x]^8 + 21 (I Sin[x])^6 Cos[x]^10 + 21 (I Sin[x])^10 Cos[x]^6 + 4 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^5 + 45 (I Sin[x])^7 Cos[x]^9 + 45 (I Sin[x])^9 Cos[x]^7) + Exp[13 I y] (5 (I Sin[x])^6 Cos[x]^10 + 5 (I Sin[x])^10 Cos[x]^6 + 6 (I Sin[x])^8 Cos[x]^8 + 7 (I Sin[x])^9 Cos[x]^7 + 7 (I Sin[x])^7 Cos[x]^9) + Exp[15 I y] (1 (I Sin[x])^9 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^9));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":661.2666666667,"max_line_length":4741,"alphanum_fraction":0.5057969553} {"size":8116,"ext":"wlt","lang":"Mathematica","max_stars_count":6.0,"content":"<|\n \"GenerateTagSystemHistory\" -> <|\n \"init\" -> (\n Attributes[Global`testUnevaluated] = Attributes[Global`testSymbolLeak] = {HoldAll};\n Global`testUnevaluated[args___] := PostTagSystem`PackageScope`testUnevaluated[VerificationTest, args];\n Global`testSymbolLeak[args___] := PostTagSystem`PackageScope`testSymbolLeak[VerificationTest, args];\n ),\n \"tests\" -> {\n testSymbolLeak[GenerateTagSystemHistory[\"Post\", {0, {0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0}}, 20858048]],\n\n With[{nineZeros = ConstantArray[0, 9]}, {\n testUnevaluated[GenerateTagSystemHistory[], {GenerateTagSystemHistory::invalidArgumentCountRange}],\n testUnevaluated[GenerateTagSystemHistory[\"invalid\", 1, 2], GenerateTagSystemHistory::invalidSystem],\n testUnevaluated[GenerateTagSystemHistory[\"Post\", 1, 2, 3],\n {GenerateTagSystemHistory::invalidStateFormat}],\n testUnevaluated[GenerateTagSystemHistory[\"Post\", #, 8],\n {GenerateTagSystemHistory::invalidStateFormat}] & \/@ {1, {1, 2, 3}, {1}},\n testUnevaluated[GenerateTagSystemHistory[\"Post\", {#, nineZeros}, 8],\n {GenerateTagSystemHistory::invalidInitPhase}] & \/@ {-1, 3, \"x\"},\n testUnevaluated[GenerateTagSystemHistory[\"Post\", {0, #}, 8],\n {GenerateTagSystemHistory::invalidInitTape}] & \/@ {0, \"x\", {\"x\"}, {-1}, {2}, {0, 1, 2}},\n testUnevaluated[GenerateTagSystemHistory[\"Post\", {0, nineZeros}, #],\n {GenerateTagSystemHistory::eventCountNotInteger}] & \/@ {\"x\", 2.3},\n testUnevaluated[GenerateTagSystemHistory[\"Post\", {0, nineZeros}, -1],\n {GenerateTagSystemHistory::eventCountNegative}],\n testUnevaluated[GenerateTagSystemHistory[\"Post\", {0, nineZeros}, 9223372036854775808 (* 2^63 *)],\n {GenerateTagSystemHistory::eventCountTooLarge}],\n testUnevaluated[GenerateTagSystemHistory[\"Post\", {0, nineZeros}, #],\n {GenerateTagSystemHistory::eventCountUneven}] & \/@ {1, 2, 3, 4, 5, 6, 7, 9, 100},\n testUnevaluated[GenerateTagSystemHistory[\"Post\", {0, nineZeros}, 8, #],\n {GenerateTagSystemHistory::invalidCheckpoints}] & \/@ {0, {0, 0}, {{0, nineZeros}, 0}},\n\n VerificationTest[GenerateTagSystemHistory[\"Post\", {0, {0, 0, 0, 0, 0, 0, 0, 0, 0}}, 8],\n <|\"EventCount\" -> 8, \"MaxTapeLength\" -> 9, \"FinalState\" -> {1, {0, 0, 0, 0, 0, 0, 0}}|>],\n VerificationTest[\n GenerateTagSystemHistory[\"Post\", {2, {1, 1, 1, 1, 1, 1, 1, 1, 1}}, 8],\n <|\"EventCount\" -> 8, \"MaxTapeLength\" -> 12, \"FinalState\" -> {1, {1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1}}|>],\n VerificationTest[GenerateTagSystemHistory[\"Post\", {0, {}}, 8],\n <|\"EventCount\" -> 0, \"MaxTapeLength\" -> 0, \"FinalState\" -> {0, {}}|>],\n VerificationTest[GenerateTagSystemHistory[\"Post\", {0, {0}}, 8],\n <|\"EventCount\" -> 0, \"MaxTapeLength\" -> 1, \"FinalState\" -> {0, {0}}|>],\n VerificationTest[GenerateTagSystemHistory[\"Post\", {0, nineZeros}, 0],\n <|\"EventCount\" -> 0, \"MaxTapeLength\" -> 9, \"FinalState\" -> {0, nineZeros}|>],\n\n VerificationTest[GenerateTagSystemHistory[\"Post\", {0, {0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0}}, 20858040],\n <|\"EventCount\" -> 20858040,\n \"MaxTapeLength\" -> 6783,\n \"FinalState\" -> {2, {0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}|>],\n VerificationTest[GenerateTagSystemHistory[\"Post\", {0, {0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0}}, #],\n <|\"EventCount\" -> 20858048,\n \"MaxTapeLength\" -> 6783,\n \"FinalState\" -> {0, {0, 0, 0, 0, 0, 0, 0}}|>] & \/@\n {20858048, 20858048 + 8, 2^32 - 8, 2^63 - 8},\n\n VerificationTest[GenerateTagSystemHistory[\"Post\",\n {0, {0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0}},\n 208570000,\n {2, {0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0}}],\n <|\"EventCount\" -> 20858000,\n \"MaxTapeLength\" -> 6783,\n \"FinalState\" -> {2, {0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0}}|>],\n VerificationTest[\n GenerateTagSystemHistory[\"Post\",\n {0, {0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0}},\n 208570000,\n {{2, {0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0}},\n {1, {1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1,\n 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1}}}],\n <|\"EventCount\" -> 20857000,\n \"MaxTapeLength\" -> 6783,\n \"FinalState\" -> {1, {1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1,\n 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1}}|>],\n\n VerificationTest[\n GenerateTagSystemHistory[\"002211\",\n {0, {0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0}},\n 600],\n <|\"EventCount\" -> 600,\n \"MaxTapeLength\" -> 40,\n \"FinalState\" -> {1, {1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1}}|>\n ],\n\n VerificationTest[\n GenerateTagSystemHistory[\"002211\",\n {0, {0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0}},\n 656],\n <|\"EventCount\" -> 656, \"MaxTapeLength\" -> 40, \"FinalState\" -> {1, {0, 0, 1, 0, 0, 0, 0, 0, 0, 0}}|>\n ],\n\n VerificationTest[\n GenerateTagSystemHistory[\"000010111\", {0, IntegerDigits[716, 2, 10]}, 10^9],\n <|\"EventCount\" -> 100280, \"MaxTapeLength\" -> 992, \"FinalState\" -> {0, {0, 0, 0, 0, 0, 0}}|>\n ],\n\n VerificationTest[\n GenerateTagSystemHistory[\"000010111\", {0, IntegerDigits[345, 2, 9]}, 10^9],\n <|\"EventCount\" -> 26760, \"MaxTapeLength\" -> 557, \"FinalState\" -> {0, {0, 0, 0, 0, 0, 0, 0}}|>\n ],\n\n VerificationTest[\n GenerateTagSystemHistory[\"Post\", {0, {1, 1, 1, 1, 1, 1, 1, 1, 1}}, 88][\"MaxTapeLength\"],\n 20\n ],\n\n VerificationTest[\n GenerateTagSystemHistory[\"Post\", {0, {1, 1, 1, 1, 1, 1, 1, 1, 1}}, 96][\"MaxTapeLength\"],\n 20\n ],\n\n VerificationTest[\n GenerateTagSystemHistory[\"Post\", {1, {1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1}}, 128, {\"PowerOfTwoEventCounts\"}][[\n {\"EventCount\", \"FinalState\"}]],\n <|\"EventCount\" -> 40, \"FinalState\" -> {1, {1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1}}|>\n ],\n\n VerificationTest[\n GenerateTagSystemHistory[\"Post\", {1, {1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1}}, 128, {}][\"EventCount\"],\n 128\n ],\n\n VerificationTest[\n GenerateTagSystemHistory[\"Post\", {0, {0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1}}, 128, {\"PowerOfTwoEventCounts\"}][\n \"EventCount\"],\n 48\n ],\n\n VerificationTest[\n GenerateTagSystemHistory[\"Post\", {2, {0, 1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 0}}, 128, {\"PowerOfTwoEventCounts\"}][[\n {\"EventCount\", \"FinalState\"}]],\n <|\"EventCount\" -> 88,\n \"FinalState\" -> GenerateTagSystemHistory[\n \"Post\", {2, {0, 1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 0}}, 64, {\"PowerOfTwoEventCounts\"}][\"FinalState\"]|>\n ],\n\n VerificationTest[\n Max @ BlockRandom[\n Table[\n GenerateTagSystemHistory[\n \"Post\", {RandomInteger[2], RandomInteger[1, 32]}, 10^12, {\"PowerOfTwoEventCounts\"}],\n 1000]\n , RandomSeeding -> 0][[All, \"EventCount\"]] < 10^12\n ]\n }]\n }\n |>\n|>\n","avg_line_length":55.2108843537,"max_line_length":120,"alphanum_fraction":0.4714144899} {"size":7848,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"(* Content-type: application\/vnd.wolfram.mathematica *)\n\n(*** Wolfram Notebook File ***)\n(* http:\/\/www.wolfram.com\/nb *)\n\n(* CreatedBy='Mathematica 11.0' *)\n\n(*CacheID: 234*)\n(* Internal cache information:\nNotebookFileLineBreakTest\nNotebookFileLineBreakTest\nNotebookDataPosition[ 158, 7]\nNotebookDataLength[ 7689, 224]\nNotebookOptionsPosition[ 6930, 194]\nNotebookOutlinePosition[ 7271, 209]\nCellTagsIndexPosition[ 7228, 206]\nWindowFrame->Normal*)\n\n(* Beginning of Notebook Content 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+ 118 (I Sin[x])^6 Cos[x]^10 + 192 (I Sin[x])^8 Cos[x]^8 + 165 (I Sin[x])^7 Cos[x]^9 + 165 (I Sin[x])^9 Cos[x]^7 + 56 (I Sin[x])^11 Cos[x]^5 + 56 (I Sin[x])^5 Cos[x]^11 + 17 (I Sin[x])^4 Cos[x]^12 + 17 (I Sin[x])^12 Cos[x]^4 + 3 (I Sin[x])^13 Cos[x]^3 + 3 (I Sin[x])^3 Cos[x]^13) + Exp[11 I y] (12 (I Sin[x])^5 Cos[x]^11 + 12 (I Sin[x])^11 Cos[x]^5 + 43 (I Sin[x])^7 Cos[x]^9 + 43 (I Sin[x])^9 Cos[x]^7 + 1 (I Sin[x])^3 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^3 + 48 (I Sin[x])^8 Cos[x]^8 + 21 (I Sin[x])^6 Cos[x]^10 + 21 (I Sin[x])^10 Cos[x]^6 + 4 (I Sin[x])^4 Cos[x]^12 + 4 (I Sin[x])^12 Cos[x]^4) + Exp[13 I y] (5 (I Sin[x])^9 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^9 + 3 (I Sin[x])^11 Cos[x]^5 + 3 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^8 Cos[x]^8 + 4 (I Sin[x])^10 Cos[x]^6 + 4 (I Sin[x])^6 Cos[x]^10 + 1 (I Sin[x])^12 Cos[x]^4 + 1 (I Sin[x])^4 Cos[x]^12) + Exp[15 I y] (1 (I Sin[x])^6 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^6))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-15 I y] (2 (I Sin[x])^8 Cos[x]^8) + Exp[-13 I y] (6 (I Sin[x])^7 Cos[x]^9 + 6 (I Sin[x])^9 Cos[x]^7 + 4 (I Sin[x])^8 Cos[x]^8 + 5 (I Sin[x])^6 Cos[x]^10 + 5 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^5 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^5) + Exp[-11 I y] (52 (I Sin[x])^9 Cos[x]^7 + 52 (I Sin[x])^7 Cos[x]^9 + 54 (I Sin[x])^8 Cos[x]^8 + 22 (I Sin[x])^6 Cos[x]^10 + 22 (I Sin[x])^10 Cos[x]^6 + 4 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^5) + Exp[-9 I y] (108 (I Sin[x])^6 Cos[x]^10 + 108 (I Sin[x])^10 Cos[x]^6 + 188 (I Sin[x])^8 Cos[x]^8 + 155 (I Sin[x])^7 Cos[x]^9 + 155 (I Sin[x])^9 Cos[x]^7 + 62 (I Sin[x])^5 Cos[x]^11 + 62 (I Sin[x])^11 Cos[x]^5 + 28 (I Sin[x])^4 Cos[x]^12 + 28 (I Sin[x])^12 Cos[x]^4 + 7 (I Sin[x])^3 Cos[x]^13 + 7 (I Sin[x])^13 Cos[x]^3 + 1 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^2) + Exp[-7 I y] (588 (I Sin[x])^8 Cos[x]^8 + 341 (I Sin[x])^10 Cos[x]^6 + 341 (I Sin[x])^6 Cos[x]^10 + 489 (I Sin[x])^7 Cos[x]^9 + 489 (I Sin[x])^9 Cos[x]^7 + 172 (I Sin[x])^11 Cos[x]^5 + 172 (I Sin[x])^5 Cos[x]^11 + 57 (I Sin[x])^12 Cos[x]^4 + 57 (I Sin[x])^4 Cos[x]^12 + 11 (I Sin[x])^3 Cos[x]^13 + 11 (I Sin[x])^13 Cos[x]^3 + 1 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^2) + Exp[-5 I y] (446 (I Sin[x])^5 Cos[x]^11 + 446 (I Sin[x])^11 Cos[x]^5 + 993 (I Sin[x])^7 Cos[x]^9 + 993 (I Sin[x])^9 Cos[x]^7 + 1052 (I Sin[x])^8 Cos[x]^8 + 747 (I Sin[x])^6 Cos[x]^10 + 747 (I Sin[x])^10 Cos[x]^6 + 202 (I Sin[x])^4 Cos[x]^12 + 202 (I Sin[x])^12 Cos[x]^4 + 71 (I Sin[x])^3 Cos[x]^13 + 71 (I Sin[x])^13 Cos[x]^3 + 16 (I Sin[x])^2 Cos[x]^14 + 16 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[-3 I y] (1788 (I Sin[x])^9 Cos[x]^7 + 1788 (I Sin[x])^7 Cos[x]^9 + 1960 (I Sin[x])^8 Cos[x]^8 + 1227 (I Sin[x])^10 Cos[x]^6 + 1227 (I Sin[x])^6 Cos[x]^10 + 656 (I Sin[x])^11 Cos[x]^5 + 656 (I Sin[x])^5 Cos[x]^11 + 265 (I Sin[x])^12 Cos[x]^4 + 265 (I Sin[x])^4 Cos[x]^12 + 75 (I Sin[x])^13 Cos[x]^3 + 75 (I Sin[x])^3 Cos[x]^13 + 13 (I Sin[x])^14 Cos[x]^2 + 13 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[-1 I y] (1543 (I Sin[x])^6 Cos[x]^10 + 1543 (I Sin[x])^10 Cos[x]^6 + 2378 (I Sin[x])^8 Cos[x]^8 + 2097 (I Sin[x])^9 Cos[x]^7 + 2097 (I Sin[x])^7 Cos[x]^9 + 454 (I Sin[x])^4 Cos[x]^12 + 454 (I Sin[x])^12 Cos[x]^4 + 925 (I Sin[x])^5 Cos[x]^11 + 925 (I Sin[x])^11 Cos[x]^5 + 169 (I Sin[x])^3 Cos[x]^13 + 169 (I Sin[x])^13 Cos[x]^3 + 48 (I Sin[x])^2 Cos[x]^14 + 48 (I Sin[x])^14 Cos[x]^2 + 9 (I Sin[x])^1 Cos[x]^15 + 9 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[1 I y] (1577 (I Sin[x])^10 Cos[x]^6 + 1577 (I Sin[x])^6 Cos[x]^10 + 2738 (I Sin[x])^8 Cos[x]^8 + 2349 (I Sin[x])^7 Cos[x]^9 + 2349 (I Sin[x])^9 Cos[x]^7 + 781 (I Sin[x])^11 Cos[x]^5 + 781 (I Sin[x])^5 Cos[x]^11 + 278 (I Sin[x])^12 Cos[x]^4 + 278 (I Sin[x])^4 Cos[x]^12 + 69 (I Sin[x])^13 Cos[x]^3 + 69 (I Sin[x])^3 Cos[x]^13 + 11 (I Sin[x])^2 Cos[x]^14 + 11 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^15 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^15) + Exp[3 I y] (737 (I Sin[x])^5 Cos[x]^11 + 737 (I Sin[x])^11 Cos[x]^5 + 1669 (I Sin[x])^7 Cos[x]^9 + 1669 (I Sin[x])^9 Cos[x]^7 + 1792 (I Sin[x])^8 Cos[x]^8 + 1235 (I Sin[x])^6 Cos[x]^10 + 1235 (I Sin[x])^10 Cos[x]^6 + 330 (I Sin[x])^4 Cos[x]^12 + 330 (I Sin[x])^12 Cos[x]^4 + 111 (I Sin[x])^3 Cos[x]^13 + 111 (I Sin[x])^13 Cos[x]^3 + 24 (I Sin[x])^2 Cos[x]^14 + 24 (I Sin[x])^14 Cos[x]^2 + 3 (I Sin[x])^1 Cos[x]^15 + 3 (I Sin[x])^15 Cos[x]^1) + Exp[5 I y] (1158 (I Sin[x])^9 Cos[x]^7 + 1158 (I Sin[x])^7 Cos[x]^9 + 330 (I Sin[x])^11 Cos[x]^5 + 330 (I Sin[x])^5 Cos[x]^11 + 715 (I Sin[x])^6 Cos[x]^10 + 715 (I Sin[x])^10 Cos[x]^6 + 110 (I Sin[x])^12 Cos[x]^4 + 110 (I Sin[x])^4 Cos[x]^12 + 1326 (I Sin[x])^8 Cos[x]^8 + 24 (I Sin[x])^3 Cos[x]^13 + 24 (I Sin[x])^13 Cos[x]^3 + 3 (I Sin[x])^14 Cos[x]^2 + 3 (I Sin[x])^2 Cos[x]^14) + Exp[7 I y] (74 (I Sin[x])^4 Cos[x]^12 + 74 (I Sin[x])^12 Cos[x]^4 + 344 (I Sin[x])^6 Cos[x]^10 + 344 (I Sin[x])^10 Cos[x]^6 + 544 (I Sin[x])^8 Cos[x]^8 + 471 (I Sin[x])^9 Cos[x]^7 + 471 (I Sin[x])^7 Cos[x]^9 + 182 (I Sin[x])^5 Cos[x]^11 + 182 (I Sin[x])^11 Cos[x]^5 + 19 (I Sin[x])^3 Cos[x]^13 + 19 (I Sin[x])^13 Cos[x]^3 + 3 (I Sin[x])^2 Cos[x]^14 + 3 (I Sin[x])^14 Cos[x]^2) + Exp[9 I y] (118 (I Sin[x])^10 Cos[x]^6 + 118 (I Sin[x])^6 Cos[x]^10 + 192 (I Sin[x])^8 Cos[x]^8 + 165 (I Sin[x])^7 Cos[x]^9 + 165 (I Sin[x])^9 Cos[x]^7 + 56 (I Sin[x])^11 Cos[x]^5 + 56 (I Sin[x])^5 Cos[x]^11 + 17 (I Sin[x])^4 Cos[x]^12 + 17 (I Sin[x])^12 Cos[x]^4 + 3 (I Sin[x])^13 Cos[x]^3 + 3 (I Sin[x])^3 Cos[x]^13) + Exp[11 I y] (12 (I Sin[x])^5 Cos[x]^11 + 12 (I Sin[x])^11 Cos[x]^5 + 43 (I Sin[x])^7 Cos[x]^9 + 43 (I Sin[x])^9 Cos[x]^7 + 1 (I Sin[x])^3 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^3 + 48 (I Sin[x])^8 Cos[x]^8 + 21 (I Sin[x])^6 Cos[x]^10 + 21 (I Sin[x])^10 Cos[x]^6 + 4 (I Sin[x])^4 Cos[x]^12 + 4 (I Sin[x])^12 Cos[x]^4) + Exp[13 I y] (5 (I Sin[x])^9 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^9 + 3 (I Sin[x])^11 Cos[x]^5 + 3 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^8 Cos[x]^8 + 4 (I Sin[x])^10 Cos[x]^6 + 4 (I Sin[x])^6 Cos[x]^10 + 1 (I Sin[x])^12 Cos[x]^4 + 1 (I Sin[x])^4 Cos[x]^12) + Exp[15 I y] (1 (I Sin[x])^6 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^6));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":723.8,"max_line_length":5206,"alphanum_fraction":0.5042829511} {"size":5147,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 11;\nname = \"11v3 2 4 1 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-10 I y] (1 (I Sin[x])^3 Cos[x]^8 + 1 (I Sin[x])^8 Cos[x]^3) + Exp[-8 I y] (4 (I Sin[x])^4 Cos[x]^7 + 4 (I Sin[x])^7 Cos[x]^4 + 1 (I Sin[x])^3 Cos[x]^8 + 1 (I Sin[x])^8 Cos[x]^3 + 5 (I Sin[x])^6 Cos[x]^5 + 5 (I Sin[x])^5 Cos[x]^6) + Exp[-6 I y] (5 (I Sin[x])^2 Cos[x]^9 + 5 (I Sin[x])^9 Cos[x]^2 + 15 (I Sin[x])^4 Cos[x]^7 + 15 (I Sin[x])^7 Cos[x]^4 + 6 (I Sin[x])^3 Cos[x]^8 + 6 (I Sin[x])^8 Cos[x]^3 + 18 (I Sin[x])^5 Cos[x]^6 + 18 (I Sin[x])^6 Cos[x]^5 + 1 (I Sin[x])^1 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^1) + Exp[-4 I y] (54 (I Sin[x])^5 Cos[x]^6 + 54 (I Sin[x])^6 Cos[x]^5 + 21 (I Sin[x])^8 Cos[x]^3 + 21 (I Sin[x])^3 Cos[x]^8 + 37 (I Sin[x])^4 Cos[x]^7 + 37 (I Sin[x])^7 Cos[x]^4 + 7 (I Sin[x])^9 Cos[x]^2 + 7 (I Sin[x])^2 Cos[x]^9 + 1 (I Sin[x])^1 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^1) + Exp[-2 I y] (45 (I Sin[x])^3 Cos[x]^8 + 45 (I Sin[x])^8 Cos[x]^3 + 80 (I Sin[x])^5 Cos[x]^6 + 80 (I Sin[x])^6 Cos[x]^5 + 64 (I Sin[x])^4 Cos[x]^7 + 64 (I Sin[x])^7 Cos[x]^4 + 15 (I Sin[x])^2 Cos[x]^9 + 15 (I Sin[x])^9 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^10 + 5 (I Sin[x])^10 Cos[x]^1 + 1 Cos[x]^11 + 1 (I Sin[x])^11) + Exp[0 I y] (122 (I Sin[x])^6 Cos[x]^5 + 122 (I Sin[x])^5 Cos[x]^6 + 85 (I Sin[x])^7 Cos[x]^4 + 85 (I Sin[x])^4 Cos[x]^7 + 35 (I Sin[x])^3 Cos[x]^8 + 35 (I Sin[x])^8 Cos[x]^3 + 9 (I Sin[x])^2 Cos[x]^9 + 9 (I Sin[x])^9 Cos[x]^2 + 1 (I Sin[x])^10 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^10) + Exp[2 I y] (68 (I Sin[x])^4 Cos[x]^7 + 68 (I Sin[x])^7 Cos[x]^4 + 15 (I Sin[x])^2 Cos[x]^9 + 15 (I Sin[x])^9 Cos[x]^2 + 30 (I Sin[x])^3 Cos[x]^8 + 30 (I Sin[x])^8 Cos[x]^3 + 94 (I Sin[x])^5 Cos[x]^6 + 94 (I Sin[x])^6 Cos[x]^5 + 3 (I Sin[x])^1 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^1) + Exp[4 I y] (64 (I Sin[x])^5 Cos[x]^6 + 64 (I Sin[x])^6 Cos[x]^5 + 39 (I Sin[x])^4 Cos[x]^7 + 39 (I Sin[x])^7 Cos[x]^4 + 15 (I Sin[x])^8 Cos[x]^3 + 15 (I Sin[x])^3 Cos[x]^8 + 2 (I Sin[x])^9 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^9) + Exp[6 I y] (11 (I Sin[x])^3 Cos[x]^8 + 11 (I Sin[x])^8 Cos[x]^3 + 18 (I Sin[x])^5 Cos[x]^6 + 18 (I Sin[x])^6 Cos[x]^5 + 14 (I Sin[x])^4 Cos[x]^7 + 14 (I Sin[x])^7 Cos[x]^4 + 2 (I Sin[x])^2 Cos[x]^9 + 2 (I Sin[x])^9 Cos[x]^2) + Exp[8 I y] (7 (I Sin[x])^6 Cos[x]^5 + 7 (I Sin[x])^5 Cos[x]^6 + 3 (I Sin[x])^7 Cos[x]^4 + 3 (I Sin[x])^4 Cos[x]^7) + Exp[10 I y] (1 (I Sin[x])^4 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^4))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-10 I y] (1 (I Sin[x])^3 Cos[x]^8 + 1 (I Sin[x])^8 Cos[x]^3) + Exp[-8 I y] (4 (I Sin[x])^4 Cos[x]^7 + 4 (I Sin[x])^7 Cos[x]^4 + 1 (I Sin[x])^3 Cos[x]^8 + 1 (I Sin[x])^8 Cos[x]^3 + 5 (I Sin[x])^6 Cos[x]^5 + 5 (I Sin[x])^5 Cos[x]^6) + Exp[-6 I y] (5 (I Sin[x])^2 Cos[x]^9 + 5 (I Sin[x])^9 Cos[x]^2 + 15 (I Sin[x])^4 Cos[x]^7 + 15 (I Sin[x])^7 Cos[x]^4 + 6 (I Sin[x])^3 Cos[x]^8 + 6 (I Sin[x])^8 Cos[x]^3 + 18 (I Sin[x])^5 Cos[x]^6 + 18 (I Sin[x])^6 Cos[x]^5 + 1 (I Sin[x])^1 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^1) + Exp[-4 I y] (54 (I Sin[x])^5 Cos[x]^6 + 54 (I Sin[x])^6 Cos[x]^5 + 21 (I Sin[x])^8 Cos[x]^3 + 21 (I Sin[x])^3 Cos[x]^8 + 37 (I Sin[x])^4 Cos[x]^7 + 37 (I Sin[x])^7 Cos[x]^4 + 7 (I Sin[x])^9 Cos[x]^2 + 7 (I Sin[x])^2 Cos[x]^9 + 1 (I Sin[x])^1 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^1) + Exp[-2 I y] (45 (I Sin[x])^3 Cos[x]^8 + 45 (I Sin[x])^8 Cos[x]^3 + 80 (I Sin[x])^5 Cos[x]^6 + 80 (I Sin[x])^6 Cos[x]^5 + 64 (I Sin[x])^4 Cos[x]^7 + 64 (I Sin[x])^7 Cos[x]^4 + 15 (I Sin[x])^2 Cos[x]^9 + 15 (I Sin[x])^9 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^10 + 5 (I Sin[x])^10 Cos[x]^1 + 1 Cos[x]^11 + 1 (I Sin[x])^11) + Exp[0 I y] (122 (I Sin[x])^6 Cos[x]^5 + 122 (I Sin[x])^5 Cos[x]^6 + 85 (I Sin[x])^7 Cos[x]^4 + 85 (I Sin[x])^4 Cos[x]^7 + 35 (I Sin[x])^3 Cos[x]^8 + 35 (I Sin[x])^8 Cos[x]^3 + 9 (I Sin[x])^2 Cos[x]^9 + 9 (I Sin[x])^9 Cos[x]^2 + 1 (I Sin[x])^10 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^10) + Exp[2 I y] (68 (I Sin[x])^4 Cos[x]^7 + 68 (I Sin[x])^7 Cos[x]^4 + 15 (I Sin[x])^2 Cos[x]^9 + 15 (I Sin[x])^9 Cos[x]^2 + 30 (I Sin[x])^3 Cos[x]^8 + 30 (I Sin[x])^8 Cos[x]^3 + 94 (I Sin[x])^5 Cos[x]^6 + 94 (I Sin[x])^6 Cos[x]^5 + 3 (I Sin[x])^1 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^1) + Exp[4 I y] (64 (I Sin[x])^5 Cos[x]^6 + 64 (I Sin[x])^6 Cos[x]^5 + 39 (I Sin[x])^4 Cos[x]^7 + 39 (I Sin[x])^7 Cos[x]^4 + 15 (I Sin[x])^8 Cos[x]^3 + 15 (I Sin[x])^3 Cos[x]^8 + 2 (I Sin[x])^9 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^9) + Exp[6 I y] (11 (I Sin[x])^3 Cos[x]^8 + 11 (I Sin[x])^8 Cos[x]^3 + 18 (I Sin[x])^5 Cos[x]^6 + 18 (I Sin[x])^6 Cos[x]^5 + 14 (I Sin[x])^4 Cos[x]^7 + 14 (I Sin[x])^7 Cos[x]^4 + 2 (I Sin[x])^2 Cos[x]^9 + 2 (I Sin[x])^9 Cos[x]^2) + Exp[8 I y] (7 (I Sin[x])^6 Cos[x]^5 + 7 (I Sin[x])^5 Cos[x]^6 + 3 (I Sin[x])^7 Cos[x]^4 + 3 (I Sin[x])^4 Cos[x]^7) + Exp[10 I y] (1 (I Sin[x])^4 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^4));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":343.1333333333,"max_line_length":2354,"alphanum_fraction":0.4864969885} {"size":4081,"ext":"nb","lang":"Mathematica","max_stars_count":2.0,"content":"Beat 0 4\nBeat 245 0\nBeat 490 1\nBeat 735 0\nBeat 1015 2\nBeat 1260 0\nBeat 1505 1\nBeat 1750 0\nBeat 1995 3\nBeat 2240 0\nBeat 2485 1\nBeat 2730 0\nBeat 3010 2\nBeat 3255 0\nBeat 3500 1\nBeat 3745 0\nBeat 3990 4\nBeat 4235 0\nBeat 4480 1\nBeat 4725 0\nBeat 5005 2\nBeat 5250 0\nBeat 5495 1\nBeat 5740 0\nBeat 5985 3\nBeat 6230 0\nBeat 6475 1\nBeat 6720 0\nBeat 7000 2\nBeat 7245 0\nBeat 7490 1\nBeat 7735 0\nBeat 8015 4\nBeat 8260 0\nBeat 8505 1\nBeat 8750 0\nBeat 8995 2\nBeat 9240 0\nBeat 9485 1\nBeat 9730 0\nBeat 10010 3\nBeat 10255 0\nBeat 10500 1\nBeat 10745 0\nBeat 10990 2\nBeat 11235 0\nBeat 11480 1\nBeat 11725 0\nBeat 12005 4\nBeat 12250 0\nBeat 12495 1\nBeat 12740 0\nBeat 12985 2\nBeat 13230 0\nBeat 13475 1\nBeat 13720 0\nBeat 14000 3\nBeat 14245 0\nBeat 14490 1\nBeat 14735 0\nBeat 14980 2\nBeat 15225 0\nBeat 15470 1\nBeat 15715 0\nBeat 15995 4\nBeat 16240 0\nBeat 16485 1\nBeat 16730 0\nBeat 17010 2\nBeat 17255 0\nBeat 17500 1\nBeat 17745 0\nBeat 17990 3\nBeat 18235 0\nBeat 18480 1\nBeat 18725 0\nBeat 19005 2\nBeat 19250 0\nBeat 19495 1\nBeat 19740 0\nBeat 19985 4\nBeat 20230 0\nBeat 20475 1\nBeat 20720 0\nBeat 21000 2\nBeat 21245 0\nBeat 21490 1\nBeat 21735 0\nBeat 22015 3\nBeat 22260 0\nBeat 22505 1\nBeat 22750 0\nBeat 22995 2\nBeat 23240 0\nBeat 23485 1\nBeat 23730 0\nBeat 24010 4\nBeat 24255 0\nBeat 24500 1\nBeat 24745 0\nBeat 24990 2\nBeat 25235 0\nBeat 25480 1\nBeat 25725 0\nBeat 26005 3\nBeat 26250 0\nBeat 26495 1\nBeat 26740 0\nBeat 26985 2\nBeat 27230 0\nBeat 27475 1\nBeat 27720 0\nBeat 28000 4\nBeat 28245 0\nBeat 28490 1\nBeat 28735 0\nBeat 29015 2\nBeat 29260 0\nBeat 29505 1\nBeat 29750 0\nBeat 29995 3\nBeat 30240 0\nBeat 30485 1\nBeat 30730 0\nBeat 30975 2\nBeat 31220 0\nBeat 31465 1\nBeat 31710 0\nBeat 31990 4\nBeat 32235 0\nBeat 32480 1\nBeat 32725 0\nBeat 33005 2\nBeat 33250 0\nBeat 33495 1\nBeat 33740 0\nBeat 33985 3\nBeat 34230 0\nBeat 34475 1\nBeat 34720 0\nBeat 35000 2\nBeat 35245 0\nBeat 35490 1\nBeat 35735 0\nBeat 36015 4\nBeat 36260 0\nBeat 36505 1\nBeat 36750 0\nBeat 36995 2\nBeat 37240 0\nBeat 37485 1\nBeat 37730 0\nBeat 38010 3\nBeat 38255 0\nBeat 38500 1\nBeat 38745 0\nBeat 38990 2\nBeat 39235 0\nBeat 39480 1\nBeat 39725 0\nBeat 40005 4\nBeat 40250 0\nBeat 40495 1\nBeat 40740 0\nBeat 40985 2\nBeat 41230 0\nBeat 41510 1\nBeat 41755 0\nBeat 42000 3\nBeat 42245 0\nBeat 42490 1\nBeat 42735 0\nBeat 43015 2\nBeat 43260 0\nBeat 43505 1\nBeat 43750 0\nBeat 43995 4\nBeat 44240 0\nBeat 44485 1\nBeat 44730 0\nBeat 45010 2\nBeat 45255 0\nBeat 45500 1\nBeat 45745 0\nBeat 45990 3\nBeat 46235 0\nBeat 46480 1\nBeat 46725 0\nBeat 47005 2\nBeat 47250 0\nBeat 47495 1\nBeat 47740 0\nBeat 47985 4\nNote 0 1015 67\nNote 1015 1995 69\nNote 1995 3010 71\nNote 3010 3990 72\nNote 3990 5005 71\nNote 5005 5985 69\nNote 5985 7000 67\n|\nNote 7000 7490 62\nNote 7490 8015 62\nNote 8015 8505 67\nNote 8505 8995 67\nNote 8995 10010 69\nNote 10010 10990 71\nNote 10990 12005 72\nNote 12005 12985 71\nNote 12985 14000 69\nNote 14000 15995 67\n|\nNote 15995 17010 67\nNote 17010 17990 69\nNote 17990 19005 71\nNote 19005 19985 72\nNote 19985 21000 71\nNote 21000 21490 69\nNote 21490 22015 69\nNote 22015 22995 67\n|\nNote 22995 23485 62\nNote 23485 24010 62\nNote 24010 24990 67\nNote 24990 26005 69\nNote 26005 26985 71\nNote 26985 28000 72\nNote 28000 29015 71\nNote 29015 29995 69\nNote 29995 31990 67\n|\nNote 31990 33005 71\nNote 33005 33985 72\nNote 33985 36015 74\nNote 36015 36995 71\nNote 36995 38010 72\nNote 38010 40005 74\n|\nNote 40005 40495 72\nNote 40495 40985 72\nNote 40985 41510 72\nNote 41510 42000 72\nNote 42000 42490 71\nNote 42490 43015 71\nNote 43015 43505 71\nNote 43505 43995 71\nNote 43995 45010 69\nNote 45010 45990 69\nNote 45990 47985 67\n|\n\n","avg_line_length":16.1944444444,"max_line_length":22,"alphanum_fraction":0.6552315609} {"size":6556,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"$Conjugate[x_] := x \/. Complex[a_, b_] :> a - I b;\nfunction[x_, y_] := $Conjugate[Exp[-13 I y] (1 (I Sin[x])^7 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^7) + Exp[-9 I y] (28 (I Sin[x])^6 Cos[x]^7 + 28 (I Sin[x])^7 Cos[x]^6 + 26 (I Sin[x])^8 Cos[x]^5 + 26 (I Sin[x])^5 Cos[x]^8 + 15 (I Sin[x])^9 Cos[x]^4 + 15 (I Sin[x])^4 Cos[x]^9 + 7 (I Sin[x])^3 Cos[x]^10 + 7 (I Sin[x])^10 Cos[x]^3 + 2 (I Sin[x])^2 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^2) + Exp[-5 I y] (217 (I Sin[x])^5 Cos[x]^8 + 217 (I Sin[x])^8 Cos[x]^5 + 288 (I Sin[x])^7 Cos[x]^6 + 288 (I Sin[x])^6 Cos[x]^7 + 135 (I Sin[x])^9 Cos[x]^4 + 135 (I Sin[x])^4 Cos[x]^9 + 57 (I Sin[x])^3 Cos[x]^10 + 57 (I Sin[x])^10 Cos[x]^3 + 15 (I Sin[x])^11 Cos[x]^2 + 15 (I Sin[x])^2 Cos[x]^11 + 3 (I Sin[x])^1 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^1) + Exp[-1 I y] (294 (I Sin[x])^4 Cos[x]^9 + 294 (I Sin[x])^9 Cos[x]^4 + 712 (I Sin[x])^6 Cos[x]^7 + 712 (I Sin[x])^7 Cos[x]^6 + 549 (I Sin[x])^8 Cos[x]^5 + 549 (I Sin[x])^5 Cos[x]^8 + 118 (I Sin[x])^10 Cos[x]^3 + 118 (I Sin[x])^3 Cos[x]^10 + 36 (I Sin[x])^2 Cos[x]^11 + 36 (I Sin[x])^11 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^12 + 6 (I Sin[x])^12 Cos[x]^1 + 1 Cos[x]^13 + 1 (I Sin[x])^13) + Exp[3 I y] (84 (I Sin[x])^3 Cos[x]^10 + 84 (I Sin[x])^10 Cos[x]^3 + 569 (I Sin[x])^7 Cos[x]^6 + 569 (I Sin[x])^6 Cos[x]^7 + 216 (I Sin[x])^9 Cos[x]^4 + 216 (I Sin[x])^4 Cos[x]^9 + 394 (I Sin[x])^5 Cos[x]^8 + 394 (I Sin[x])^8 Cos[x]^5 + 20 (I Sin[x])^2 Cos[x]^11 + 20 (I Sin[x])^11 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^12 + 4 (I Sin[x])^12 Cos[x]^1) + Exp[7 I y] (5 (I Sin[x])^2 Cos[x]^11 + 5 (I Sin[x])^11 Cos[x]^2 + 98 (I Sin[x])^8 Cos[x]^5 + 98 (I Sin[x])^5 Cos[x]^8 + 51 (I Sin[x])^4 Cos[x]^9 + 51 (I Sin[x])^9 Cos[x]^4 + 114 (I Sin[x])^6 Cos[x]^7 + 114 (I Sin[x])^7 Cos[x]^6 + 18 (I Sin[x])^10 Cos[x]^3 + 18 (I Sin[x])^3 Cos[x]^10) + Exp[11 I y] (2 (I Sin[x])^3 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^3 + 3 (I Sin[x])^5 Cos[x]^8 + 3 (I Sin[x])^8 Cos[x]^5 + 4 (I Sin[x])^7 Cos[x]^6 + 4 (I Sin[x])^6 Cos[x]^7 + 4 (I Sin[x])^9 Cos[x]^4 + 4 (I Sin[x])^4 Cos[x]^9)]*\n(Exp[-13 I y] (1 (I Sin[x])^7 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^7) + Exp[-9 I y] (28 (I Sin[x])^6 Cos[x]^7 + 28 (I Sin[x])^7 Cos[x]^6 + 26 (I Sin[x])^8 Cos[x]^5 + 26 (I Sin[x])^5 Cos[x]^8 + 15 (I Sin[x])^9 Cos[x]^4 + 15 (I Sin[x])^4 Cos[x]^9 + 7 (I Sin[x])^3 Cos[x]^10 + 7 (I Sin[x])^10 Cos[x]^3 + 2 (I Sin[x])^2 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^2) + Exp[-5 I y] (217 (I Sin[x])^5 Cos[x]^8 + 217 (I Sin[x])^8 Cos[x]^5 + 288 (I Sin[x])^7 Cos[x]^6 + 288 (I Sin[x])^6 Cos[x]^7 + 135 (I Sin[x])^9 Cos[x]^4 + 135 (I Sin[x])^4 Cos[x]^9 + 57 (I Sin[x])^3 Cos[x]^10 + 57 (I Sin[x])^10 Cos[x]^3 + 15 (I Sin[x])^11 Cos[x]^2 + 15 (I Sin[x])^2 Cos[x]^11 + 3 (I Sin[x])^1 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^1) + Exp[-1 I y] (294 (I Sin[x])^4 Cos[x]^9 + 294 (I Sin[x])^9 Cos[x]^4 + 712 (I Sin[x])^6 Cos[x]^7 + 712 (I Sin[x])^7 Cos[x]^6 + 549 (I Sin[x])^8 Cos[x]^5 + 549 (I Sin[x])^5 Cos[x]^8 + 118 (I Sin[x])^10 Cos[x]^3 + 118 (I Sin[x])^3 Cos[x]^10 + 36 (I Sin[x])^2 Cos[x]^11 + 36 (I Sin[x])^11 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^12 + 6 (I Sin[x])^12 Cos[x]^1 + 1 Cos[x]^13 + 1 (I Sin[x])^13) + Exp[3 I y] (84 (I Sin[x])^3 Cos[x]^10 + 84 (I Sin[x])^10 Cos[x]^3 + 569 (I Sin[x])^7 Cos[x]^6 + 569 (I Sin[x])^6 Cos[x]^7 + 216 (I Sin[x])^9 Cos[x]^4 + 216 (I Sin[x])^4 Cos[x]^9 + 394 (I Sin[x])^5 Cos[x]^8 + 394 (I Sin[x])^8 Cos[x]^5 + 20 (I Sin[x])^2 Cos[x]^11 + 20 (I Sin[x])^11 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^12 + 4 (I Sin[x])^12 Cos[x]^1) + Exp[7 I y] (5 (I Sin[x])^2 Cos[x]^11 + 5 (I Sin[x])^11 Cos[x]^2 + 98 (I Sin[x])^8 Cos[x]^5 + 98 (I Sin[x])^5 Cos[x]^8 + 51 (I Sin[x])^4 Cos[x]^9 + 51 (I Sin[x])^9 Cos[x]^4 + 114 (I Sin[x])^6 Cos[x]^7 + 114 (I Sin[x])^7 Cos[x]^6 + 18 (I Sin[x])^10 Cos[x]^3 + 18 (I Sin[x])^3 Cos[x]^10) + Exp[11 I y] (2 (I Sin[x])^3 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^3 + 3 (I Sin[x])^5 Cos[x]^8 + 3 (I Sin[x])^8 Cos[x]^5 + 4 (I Sin[x])^7 Cos[x]^6 + 4 (I Sin[x])^6 Cos[x]^7 + 4 (I Sin[x])^9 Cos[x]^4 + 4 (I Sin[x])^4 Cos[x]^9))\n\namplitude[x_,y_] := Exp[-13 I y] (1 (I Sin[x])^7 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^7) + Exp[-9 I y] (28 (I Sin[x])^6 Cos[x]^7 + 28 (I Sin[x])^7 Cos[x]^6 + 26 (I Sin[x])^8 Cos[x]^5 + 26 (I Sin[x])^5 Cos[x]^8 + 15 (I Sin[x])^9 Cos[x]^4 + 15 (I Sin[x])^4 Cos[x]^9 + 7 (I Sin[x])^3 Cos[x]^10 + 7 (I Sin[x])^10 Cos[x]^3 + 2 (I Sin[x])^2 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^2) + Exp[-5 I y] (217 (I Sin[x])^5 Cos[x]^8 + 217 (I Sin[x])^8 Cos[x]^5 + 288 (I Sin[x])^7 Cos[x]^6 + 288 (I Sin[x])^6 Cos[x]^7 + 135 (I Sin[x])^9 Cos[x]^4 + 135 (I Sin[x])^4 Cos[x]^9 + 57 (I Sin[x])^3 Cos[x]^10 + 57 (I Sin[x])^10 Cos[x]^3 + 15 (I Sin[x])^11 Cos[x]^2 + 15 (I Sin[x])^2 Cos[x]^11 + 3 (I Sin[x])^1 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^1) + Exp[-1 I y] (294 (I Sin[x])^4 Cos[x]^9 + 294 (I Sin[x])^9 Cos[x]^4 + 712 (I Sin[x])^6 Cos[x]^7 + 712 (I Sin[x])^7 Cos[x]^6 + 549 (I Sin[x])^8 Cos[x]^5 + 549 (I Sin[x])^5 Cos[x]^8 + 118 (I Sin[x])^10 Cos[x]^3 + 118 (I Sin[x])^3 Cos[x]^10 + 36 (I Sin[x])^2 Cos[x]^11 + 36 (I Sin[x])^11 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^12 + 6 (I Sin[x])^12 Cos[x]^1 + 1 Cos[x]^13 + 1 (I Sin[x])^13) + Exp[3 I y] (84 (I Sin[x])^3 Cos[x]^10 + 84 (I Sin[x])^10 Cos[x]^3 + 569 (I Sin[x])^7 Cos[x]^6 + 569 (I Sin[x])^6 Cos[x]^7 + 216 (I Sin[x])^9 Cos[x]^4 + 216 (I Sin[x])^4 Cos[x]^9 + 394 (I Sin[x])^5 Cos[x]^8 + 394 (I Sin[x])^8 Cos[x]^5 + 20 (I Sin[x])^2 Cos[x]^11 + 20 (I Sin[x])^11 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^12 + 4 (I Sin[x])^12 Cos[x]^1) + Exp[7 I y] (5 (I Sin[x])^2 Cos[x]^11 + 5 (I Sin[x])^11 Cos[x]^2 + 98 (I Sin[x])^8 Cos[x]^5 + 98 (I Sin[x])^5 Cos[x]^8 + 51 (I Sin[x])^4 Cos[x]^9 + 51 (I Sin[x])^9 Cos[x]^4 + 114 (I Sin[x])^6 Cos[x]^7 + 114 (I Sin[x])^7 Cos[x]^6 + 18 (I Sin[x])^10 Cos[x]^3 + 18 (I Sin[x])^3 Cos[x]^10) + Exp[11 I y] (2 (I Sin[x])^3 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^3 + 3 (I Sin[x])^5 Cos[x]^8 + 3 (I Sin[x])^8 Cos[x]^5 + 4 (I Sin[x])^7 Cos[x]^6 + 4 (I Sin[x])^6 Cos[x]^7 + 4 (I Sin[x])^9 Cos[x]^4 + 4 (I Sin[x])^4 Cos[x]^9)\n\namount = 13;\nname = \"13v4 1 1 3 1 3\";\nstates = 52;\n\n\nk = 0.1;\n\n\nmax = function[0, 0];\nx = 0;\ny = 0;\n\n\nFor[\u03b2 = 0 , \u03b2 <= Pi\/2, \u03b2 = \u03b2 + k,\n \tFor[\u03b3 = 0 , \u03b3 <= Pi\/2 - \u03b2, \u03b3 = \u03b3 + k,\n \t\n \t\tmax2 = function[\u03b2, \u03b3];\n \t\tIf[max2 > max, {x = \u03b2, y = \u03b3}];\n \t\tmax = Max[max, max2];\n \t]\n ]\n\nresult = NMaximize[{Re[states*function[a, b]\/(2^amount)], x - k < a < x + k, y - k < b < y + k}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 3}];\n\nPrint[name, \": \", result]\n\nf = function[c, d]; n = Pi;\nPlot3D[f,{c,0,n},{d,0,n}, PlotRange -> All]\n\nContourPlot[function[x, y], {x, 0, n}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":177.1891891892,"max_line_length":1969,"alphanum_fraction":0.49023795} {"size":10821,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 16;\nname = \"16v3 1 3 2 1 1 2 1 1 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^6 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^6) + Exp[-13 I y] (3 (I Sin[x])^5 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^5 + 5 (I Sin[x])^9 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^9 + 5 (I Sin[x])^6 Cos[x]^10 + 5 (I Sin[x])^10 Cos[x]^6 + 4 (I Sin[x])^8 Cos[x]^8) + Exp[-11 I y] (45 (I Sin[x])^7 Cos[x]^9 + 45 (I Sin[x])^9 Cos[x]^7 + 11 (I Sin[x])^5 Cos[x]^11 + 11 (I Sin[x])^11 Cos[x]^5 + 23 (I Sin[x])^6 Cos[x]^10 + 23 (I Sin[x])^10 Cos[x]^6 + 48 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^4 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^4) + Exp[-9 I y] (26 (I Sin[x])^4 Cos[x]^12 + 26 (I Sin[x])^12 Cos[x]^4 + 184 (I Sin[x])^8 Cos[x]^8 + 113 (I Sin[x])^6 Cos[x]^10 + 113 (I Sin[x])^10 Cos[x]^6 + 161 (I Sin[x])^7 Cos[x]^9 + 161 (I Sin[x])^9 Cos[x]^7 + 59 (I Sin[x])^5 Cos[x]^11 + 59 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^3 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^3) + Exp[-7 I y] (662 (I Sin[x])^8 Cos[x]^8 + 327 (I Sin[x])^6 Cos[x]^10 + 327 (I Sin[x])^10 Cos[x]^6 + 537 (I Sin[x])^7 Cos[x]^9 + 537 (I Sin[x])^9 Cos[x]^7 + 35 (I Sin[x])^4 Cos[x]^12 + 35 (I Sin[x])^12 Cos[x]^4 + 130 (I Sin[x])^5 Cos[x]^11 + 130 (I Sin[x])^11 Cos[x]^5 + 5 (I Sin[x])^3 Cos[x]^13 + 5 (I Sin[x])^13 Cos[x]^3) + Exp[-5 I y] (428 (I Sin[x])^5 Cos[x]^11 + 428 (I Sin[x])^11 Cos[x]^5 + 1032 (I Sin[x])^7 Cos[x]^9 + 1032 (I Sin[x])^9 Cos[x]^7 + 52 (I Sin[x])^3 Cos[x]^13 + 52 (I Sin[x])^13 Cos[x]^3 + 747 (I Sin[x])^6 Cos[x]^10 + 747 (I Sin[x])^10 Cos[x]^6 + 1134 (I Sin[x])^8 Cos[x]^8 + 169 (I Sin[x])^4 Cos[x]^12 + 169 (I Sin[x])^12 Cos[x]^4 + 8 (I Sin[x])^2 Cos[x]^14 + 8 (I Sin[x])^14 Cos[x]^2) + Exp[-3 I y] (1908 (I Sin[x])^7 Cos[x]^9 + 1908 (I Sin[x])^9 Cos[x]^7 + 2144 (I Sin[x])^8 Cos[x]^8 + 1225 (I Sin[x])^10 Cos[x]^6 + 1225 (I Sin[x])^6 Cos[x]^10 + 575 (I Sin[x])^5 Cos[x]^11 + 575 (I Sin[x])^11 Cos[x]^5 + 37 (I Sin[x])^3 Cos[x]^13 + 37 (I Sin[x])^13 Cos[x]^3 + 184 (I Sin[x])^4 Cos[x]^12 + 184 (I Sin[x])^12 Cos[x]^4 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2) + Exp[-1 I y] (1573 (I Sin[x])^6 Cos[x]^10 + 1573 (I Sin[x])^10 Cos[x]^6 + 420 (I Sin[x])^4 Cos[x]^12 + 420 (I Sin[x])^12 Cos[x]^4 + 2416 (I Sin[x])^8 Cos[x]^8 + 34 (I Sin[x])^2 Cos[x]^14 + 34 (I Sin[x])^14 Cos[x]^2 + 898 (I Sin[x])^5 Cos[x]^11 + 898 (I Sin[x])^11 Cos[x]^5 + 2159 (I Sin[x])^9 Cos[x]^7 + 2159 (I Sin[x])^7 Cos[x]^9 + 138 (I Sin[x])^3 Cos[x]^13 + 138 (I Sin[x])^13 Cos[x]^3 + 5 (I Sin[x])^1 Cos[x]^15 + 5 (I Sin[x])^15 Cos[x]^1) + Exp[1 I y] (1562 (I Sin[x])^6 Cos[x]^10 + 1562 (I Sin[x])^10 Cos[x]^6 + 2704 (I Sin[x])^8 Cos[x]^8 + 2311 (I Sin[x])^7 Cos[x]^9 + 2311 (I Sin[x])^9 Cos[x]^7 + 806 (I Sin[x])^5 Cos[x]^11 + 806 (I Sin[x])^11 Cos[x]^5 + 308 (I Sin[x])^4 Cos[x]^12 + 308 (I Sin[x])^12 Cos[x]^4 + 82 (I Sin[x])^3 Cos[x]^13 + 82 (I Sin[x])^13 Cos[x]^3 + 13 (I Sin[x])^2 Cos[x]^14 + 13 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[3 I y] (737 (I Sin[x])^5 Cos[x]^11 + 737 (I Sin[x])^11 Cos[x]^5 + 1640 (I Sin[x])^7 Cos[x]^9 + 1640 (I Sin[x])^9 Cos[x]^7 + 136 (I Sin[x])^3 Cos[x]^13 + 136 (I Sin[x])^13 Cos[x]^3 + 1198 (I Sin[x])^6 Cos[x]^10 + 1198 (I Sin[x])^10 Cos[x]^6 + 1802 (I Sin[x])^8 Cos[x]^8 + 348 (I Sin[x])^4 Cos[x]^12 + 348 (I Sin[x])^12 Cos[x]^4 + 37 (I Sin[x])^2 Cos[x]^14 + 37 (I Sin[x])^14 Cos[x]^2 + 7 (I Sin[x])^1 Cos[x]^15 + 7 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[5 I y] (1050 (I Sin[x])^7 Cos[x]^9 + 1050 (I Sin[x])^9 Cos[x]^7 + 411 (I Sin[x])^5 Cos[x]^11 + 411 (I Sin[x])^11 Cos[x]^5 + 1120 (I Sin[x])^8 Cos[x]^8 + 751 (I Sin[x])^10 Cos[x]^6 + 751 (I Sin[x])^6 Cos[x]^10 + 170 (I Sin[x])^4 Cos[x]^12 + 170 (I Sin[x])^12 Cos[x]^4 + 50 (I Sin[x])^3 Cos[x]^13 + 50 (I Sin[x])^13 Cos[x]^3 + 10 (I Sin[x])^2 Cos[x]^14 + 10 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^15 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^15) + Exp[7 I y] (347 (I Sin[x])^6 Cos[x]^10 + 347 (I Sin[x])^10 Cos[x]^6 + 432 (I Sin[x])^8 Cos[x]^8 + 118 (I Sin[x])^4 Cos[x]^12 + 118 (I Sin[x])^12 Cos[x]^4 + 405 (I Sin[x])^7 Cos[x]^9 + 405 (I Sin[x])^9 Cos[x]^7 + 222 (I Sin[x])^5 Cos[x]^11 + 222 (I Sin[x])^11 Cos[x]^5 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2 + 43 (I Sin[x])^3 Cos[x]^13 + 43 (I Sin[x])^13 Cos[x]^3 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[9 I y] (178 (I Sin[x])^8 Cos[x]^8 + 112 (I Sin[x])^6 Cos[x]^10 + 112 (I Sin[x])^10 Cos[x]^6 + 147 (I Sin[x])^7 Cos[x]^9 + 147 (I Sin[x])^9 Cos[x]^7 + 69 (I Sin[x])^5 Cos[x]^11 + 69 (I Sin[x])^11 Cos[x]^5 + 29 (I Sin[x])^4 Cos[x]^12 + 29 (I Sin[x])^12 Cos[x]^4 + 8 (I Sin[x])^3 Cos[x]^13 + 8 (I Sin[x])^13 Cos[x]^3 + 1 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^2 Cos[x]^14) + Exp[11 I y] (19 (I Sin[x])^5 Cos[x]^11 + 19 (I Sin[x])^11 Cos[x]^5 + 32 (I Sin[x])^7 Cos[x]^9 + 32 (I Sin[x])^9 Cos[x]^7 + 34 (I Sin[x])^8 Cos[x]^8 + 20 (I Sin[x])^6 Cos[x]^10 + 20 (I Sin[x])^10 Cos[x]^6 + 5 (I Sin[x])^3 Cos[x]^13 + 5 (I Sin[x])^13 Cos[x]^3 + 11 (I Sin[x])^4 Cos[x]^12 + 11 (I Sin[x])^12 Cos[x]^4 + 1 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^2) + Exp[13 I y] (8 (I Sin[x])^9 Cos[x]^7 + 8 (I Sin[x])^7 Cos[x]^9 + 8 (I Sin[x])^8 Cos[x]^8 + 3 (I Sin[x])^10 Cos[x]^6 + 3 (I Sin[x])^6 Cos[x]^10) + Exp[15 I y] (1 (I Sin[x])^6 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^6))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^6 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^6) + Exp[-13 I y] (3 (I Sin[x])^5 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^5 + 5 (I Sin[x])^9 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^9 + 5 (I Sin[x])^6 Cos[x]^10 + 5 (I Sin[x])^10 Cos[x]^6 + 4 (I Sin[x])^8 Cos[x]^8) + Exp[-11 I y] (45 (I Sin[x])^7 Cos[x]^9 + 45 (I Sin[x])^9 Cos[x]^7 + 11 (I Sin[x])^5 Cos[x]^11 + 11 (I Sin[x])^11 Cos[x]^5 + 23 (I Sin[x])^6 Cos[x]^10 + 23 (I Sin[x])^10 Cos[x]^6 + 48 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^4 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^4) + Exp[-9 I y] (26 (I Sin[x])^4 Cos[x]^12 + 26 (I Sin[x])^12 Cos[x]^4 + 184 (I Sin[x])^8 Cos[x]^8 + 113 (I Sin[x])^6 Cos[x]^10 + 113 (I Sin[x])^10 Cos[x]^6 + 161 (I Sin[x])^7 Cos[x]^9 + 161 (I Sin[x])^9 Cos[x]^7 + 59 (I Sin[x])^5 Cos[x]^11 + 59 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^3 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^3) + Exp[-7 I y] (662 (I Sin[x])^8 Cos[x]^8 + 327 (I Sin[x])^6 Cos[x]^10 + 327 (I Sin[x])^10 Cos[x]^6 + 537 (I Sin[x])^7 Cos[x]^9 + 537 (I Sin[x])^9 Cos[x]^7 + 35 (I Sin[x])^4 Cos[x]^12 + 35 (I Sin[x])^12 Cos[x]^4 + 130 (I Sin[x])^5 Cos[x]^11 + 130 (I Sin[x])^11 Cos[x]^5 + 5 (I Sin[x])^3 Cos[x]^13 + 5 (I Sin[x])^13 Cos[x]^3) + Exp[-5 I y] (428 (I Sin[x])^5 Cos[x]^11 + 428 (I Sin[x])^11 Cos[x]^5 + 1032 (I Sin[x])^7 Cos[x]^9 + 1032 (I Sin[x])^9 Cos[x]^7 + 52 (I Sin[x])^3 Cos[x]^13 + 52 (I Sin[x])^13 Cos[x]^3 + 747 (I Sin[x])^6 Cos[x]^10 + 747 (I Sin[x])^10 Cos[x]^6 + 1134 (I Sin[x])^8 Cos[x]^8 + 169 (I Sin[x])^4 Cos[x]^12 + 169 (I Sin[x])^12 Cos[x]^4 + 8 (I Sin[x])^2 Cos[x]^14 + 8 (I Sin[x])^14 Cos[x]^2) + Exp[-3 I y] (1908 (I Sin[x])^7 Cos[x]^9 + 1908 (I Sin[x])^9 Cos[x]^7 + 2144 (I Sin[x])^8 Cos[x]^8 + 1225 (I Sin[x])^10 Cos[x]^6 + 1225 (I Sin[x])^6 Cos[x]^10 + 575 (I Sin[x])^5 Cos[x]^11 + 575 (I Sin[x])^11 Cos[x]^5 + 37 (I Sin[x])^3 Cos[x]^13 + 37 (I Sin[x])^13 Cos[x]^3 + 184 (I Sin[x])^4 Cos[x]^12 + 184 (I Sin[x])^12 Cos[x]^4 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2) + Exp[-1 I y] (1573 (I Sin[x])^6 Cos[x]^10 + 1573 (I Sin[x])^10 Cos[x]^6 + 420 (I Sin[x])^4 Cos[x]^12 + 420 (I Sin[x])^12 Cos[x]^4 + 2416 (I Sin[x])^8 Cos[x]^8 + 34 (I Sin[x])^2 Cos[x]^14 + 34 (I Sin[x])^14 Cos[x]^2 + 898 (I Sin[x])^5 Cos[x]^11 + 898 (I Sin[x])^11 Cos[x]^5 + 2159 (I Sin[x])^9 Cos[x]^7 + 2159 (I Sin[x])^7 Cos[x]^9 + 138 (I Sin[x])^3 Cos[x]^13 + 138 (I Sin[x])^13 Cos[x]^3 + 5 (I Sin[x])^1 Cos[x]^15 + 5 (I Sin[x])^15 Cos[x]^1) + Exp[1 I y] (1562 (I Sin[x])^6 Cos[x]^10 + 1562 (I Sin[x])^10 Cos[x]^6 + 2704 (I Sin[x])^8 Cos[x]^8 + 2311 (I Sin[x])^7 Cos[x]^9 + 2311 (I Sin[x])^9 Cos[x]^7 + 806 (I Sin[x])^5 Cos[x]^11 + 806 (I Sin[x])^11 Cos[x]^5 + 308 (I Sin[x])^4 Cos[x]^12 + 308 (I Sin[x])^12 Cos[x]^4 + 82 (I Sin[x])^3 Cos[x]^13 + 82 (I Sin[x])^13 Cos[x]^3 + 13 (I Sin[x])^2 Cos[x]^14 + 13 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[3 I y] (737 (I Sin[x])^5 Cos[x]^11 + 737 (I Sin[x])^11 Cos[x]^5 + 1640 (I Sin[x])^7 Cos[x]^9 + 1640 (I Sin[x])^9 Cos[x]^7 + 136 (I Sin[x])^3 Cos[x]^13 + 136 (I Sin[x])^13 Cos[x]^3 + 1198 (I Sin[x])^6 Cos[x]^10 + 1198 (I Sin[x])^10 Cos[x]^6 + 1802 (I Sin[x])^8 Cos[x]^8 + 348 (I Sin[x])^4 Cos[x]^12 + 348 (I Sin[x])^12 Cos[x]^4 + 37 (I Sin[x])^2 Cos[x]^14 + 37 (I Sin[x])^14 Cos[x]^2 + 7 (I Sin[x])^1 Cos[x]^15 + 7 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[5 I y] (1050 (I Sin[x])^7 Cos[x]^9 + 1050 (I Sin[x])^9 Cos[x]^7 + 411 (I Sin[x])^5 Cos[x]^11 + 411 (I Sin[x])^11 Cos[x]^5 + 1120 (I Sin[x])^8 Cos[x]^8 + 751 (I Sin[x])^10 Cos[x]^6 + 751 (I Sin[x])^6 Cos[x]^10 + 170 (I Sin[x])^4 Cos[x]^12 + 170 (I Sin[x])^12 Cos[x]^4 + 50 (I Sin[x])^3 Cos[x]^13 + 50 (I Sin[x])^13 Cos[x]^3 + 10 (I Sin[x])^2 Cos[x]^14 + 10 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^15 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^15) + Exp[7 I y] (347 (I Sin[x])^6 Cos[x]^10 + 347 (I Sin[x])^10 Cos[x]^6 + 432 (I Sin[x])^8 Cos[x]^8 + 118 (I Sin[x])^4 Cos[x]^12 + 118 (I Sin[x])^12 Cos[x]^4 + 405 (I Sin[x])^7 Cos[x]^9 + 405 (I Sin[x])^9 Cos[x]^7 + 222 (I Sin[x])^5 Cos[x]^11 + 222 (I Sin[x])^11 Cos[x]^5 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2 + 43 (I Sin[x])^3 Cos[x]^13 + 43 (I Sin[x])^13 Cos[x]^3 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[9 I y] (178 (I Sin[x])^8 Cos[x]^8 + 112 (I Sin[x])^6 Cos[x]^10 + 112 (I Sin[x])^10 Cos[x]^6 + 147 (I Sin[x])^7 Cos[x]^9 + 147 (I Sin[x])^9 Cos[x]^7 + 69 (I Sin[x])^5 Cos[x]^11 + 69 (I Sin[x])^11 Cos[x]^5 + 29 (I Sin[x])^4 Cos[x]^12 + 29 (I Sin[x])^12 Cos[x]^4 + 8 (I Sin[x])^3 Cos[x]^13 + 8 (I Sin[x])^13 Cos[x]^3 + 1 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^2 Cos[x]^14) + Exp[11 I y] (19 (I Sin[x])^5 Cos[x]^11 + 19 (I Sin[x])^11 Cos[x]^5 + 32 (I Sin[x])^7 Cos[x]^9 + 32 (I Sin[x])^9 Cos[x]^7 + 34 (I Sin[x])^8 Cos[x]^8 + 20 (I Sin[x])^6 Cos[x]^10 + 20 (I Sin[x])^10 Cos[x]^6 + 5 (I Sin[x])^3 Cos[x]^13 + 5 (I Sin[x])^13 Cos[x]^3 + 11 (I Sin[x])^4 Cos[x]^12 + 11 (I Sin[x])^12 Cos[x]^4 + 1 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^2) + Exp[13 I y] (8 (I Sin[x])^9 Cos[x]^7 + 8 (I Sin[x])^7 Cos[x]^9 + 8 (I Sin[x])^8 Cos[x]^8 + 3 (I Sin[x])^10 Cos[x]^6 + 3 (I Sin[x])^6 Cos[x]^10) + Exp[15 I y] (1 (I Sin[x])^6 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^6));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":721.4,"max_line_length":5186,"alphanum_fraction":0.5050365031} {"size":10483,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 16;\nname = \"16v2 1 1 4 1 1 1 1 2 2\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^9 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^9) + Exp[-13 I y] (10 (I Sin[x])^8 Cos[x]^8 + 3 (I Sin[x])^6 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^6 + 5 (I Sin[x])^7 Cos[x]^9 + 5 (I Sin[x])^9 Cos[x]^7 + 2 (I Sin[x])^5 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^5) + Exp[-11 I y] (42 (I Sin[x])^8 Cos[x]^8 + 35 (I Sin[x])^10 Cos[x]^6 + 35 (I Sin[x])^6 Cos[x]^10 + 40 (I Sin[x])^9 Cos[x]^7 + 40 (I Sin[x])^7 Cos[x]^9 + 9 (I Sin[x])^11 Cos[x]^5 + 9 (I Sin[x])^5 Cos[x]^11) + Exp[-9 I y] (153 (I Sin[x])^9 Cos[x]^7 + 153 (I Sin[x])^7 Cos[x]^9 + 72 (I Sin[x])^5 Cos[x]^11 + 72 (I Sin[x])^11 Cos[x]^5 + 156 (I Sin[x])^8 Cos[x]^8 + 36 (I Sin[x])^4 Cos[x]^12 + 36 (I Sin[x])^12 Cos[x]^4 + 110 (I Sin[x])^10 Cos[x]^6 + 110 (I Sin[x])^6 Cos[x]^10 + 6 (I Sin[x])^3 Cos[x]^13 + 6 (I Sin[x])^13 Cos[x]^3) + Exp[-7 I y] (553 (I Sin[x])^9 Cos[x]^7 + 553 (I Sin[x])^7 Cos[x]^9 + 140 (I Sin[x])^11 Cos[x]^5 + 140 (I Sin[x])^5 Cos[x]^11 + 664 (I Sin[x])^8 Cos[x]^8 + 310 (I Sin[x])^10 Cos[x]^6 + 310 (I Sin[x])^6 Cos[x]^10 + 30 (I Sin[x])^12 Cos[x]^4 + 30 (I Sin[x])^4 Cos[x]^12) + Exp[-5 I y] (1074 (I Sin[x])^8 Cos[x]^8 + 778 (I Sin[x])^10 Cos[x]^6 + 778 (I Sin[x])^6 Cos[x]^10 + 981 (I Sin[x])^9 Cos[x]^7 + 981 (I Sin[x])^7 Cos[x]^9 + 443 (I Sin[x])^5 Cos[x]^11 + 443 (I Sin[x])^11 Cos[x]^5 + 186 (I Sin[x])^4 Cos[x]^12 + 186 (I Sin[x])^12 Cos[x]^4 + 67 (I Sin[x])^3 Cos[x]^13 + 67 (I Sin[x])^13 Cos[x]^3 + 11 (I Sin[x])^2 Cos[x]^14 + 11 (I Sin[x])^14 Cos[x]^2) + Exp[-3 I y] (1197 (I Sin[x])^10 Cos[x]^6 + 1197 (I Sin[x])^6 Cos[x]^10 + 2306 (I Sin[x])^8 Cos[x]^8 + 1950 (I Sin[x])^7 Cos[x]^9 + 1950 (I Sin[x])^9 Cos[x]^7 + 170 (I Sin[x])^12 Cos[x]^4 + 170 (I Sin[x])^4 Cos[x]^12 + 502 (I Sin[x])^11 Cos[x]^5 + 502 (I Sin[x])^5 Cos[x]^11 + 33 (I Sin[x])^13 Cos[x]^3 + 33 (I Sin[x])^3 Cos[x]^13) + Exp[-1 I y] (2151 (I Sin[x])^7 Cos[x]^9 + 2151 (I Sin[x])^9 Cos[x]^7 + 945 (I Sin[x])^11 Cos[x]^5 + 945 (I Sin[x])^5 Cos[x]^11 + 1551 (I Sin[x])^10 Cos[x]^6 + 1551 (I Sin[x])^6 Cos[x]^10 + 434 (I Sin[x])^12 Cos[x]^4 + 434 (I Sin[x])^4 Cos[x]^12 + 2356 (I Sin[x])^8 Cos[x]^8 + 133 (I Sin[x])^3 Cos[x]^13 + 133 (I Sin[x])^13 Cos[x]^3 + 37 (I Sin[x])^2 Cos[x]^14 + 37 (I Sin[x])^14 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^15 + 6 (I Sin[x])^15 Cos[x]^1) + Exp[1 I y] (821 (I Sin[x])^11 Cos[x]^5 + 821 (I Sin[x])^5 Cos[x]^11 + 2341 (I Sin[x])^9 Cos[x]^7 + 2341 (I Sin[x])^7 Cos[x]^9 + 1606 (I Sin[x])^6 Cos[x]^10 + 1606 (I Sin[x])^10 Cos[x]^6 + 2616 (I Sin[x])^8 Cos[x]^8 + 272 (I Sin[x])^12 Cos[x]^4 + 272 (I Sin[x])^4 Cos[x]^12 + 73 (I Sin[x])^13 Cos[x]^3 + 73 (I Sin[x])^3 Cos[x]^13 + 14 (I Sin[x])^2 Cos[x]^14 + 14 (I Sin[x])^14 Cos[x]^2) + Exp[3 I y] (1198 (I Sin[x])^6 Cos[x]^10 + 1198 (I Sin[x])^10 Cos[x]^6 + 1920 (I Sin[x])^8 Cos[x]^8 + 1671 (I Sin[x])^9 Cos[x]^7 + 1671 (I Sin[x])^7 Cos[x]^9 + 673 (I Sin[x])^11 Cos[x]^5 + 673 (I Sin[x])^5 Cos[x]^11 + 330 (I Sin[x])^4 Cos[x]^12 + 330 (I Sin[x])^12 Cos[x]^4 + 135 (I Sin[x])^3 Cos[x]^13 + 135 (I Sin[x])^13 Cos[x]^3 + 31 (I Sin[x])^2 Cos[x]^14 + 31 (I Sin[x])^14 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^15 + 6 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[5 I y] (739 (I Sin[x])^10 Cos[x]^6 + 739 (I Sin[x])^6 Cos[x]^10 + 1094 (I Sin[x])^8 Cos[x]^8 + 216 (I Sin[x])^12 Cos[x]^4 + 216 (I Sin[x])^4 Cos[x]^12 + 452 (I Sin[x])^5 Cos[x]^11 + 452 (I Sin[x])^11 Cos[x]^5 + 980 (I Sin[x])^9 Cos[x]^7 + 980 (I Sin[x])^7 Cos[x]^9 + 57 (I Sin[x])^3 Cos[x]^13 + 57 (I Sin[x])^13 Cos[x]^3 + 10 (I Sin[x])^14 Cos[x]^2 + 10 (I Sin[x])^2 Cos[x]^14 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[7 I y] (211 (I Sin[x])^5 Cos[x]^11 + 211 (I Sin[x])^11 Cos[x]^5 + 447 (I Sin[x])^7 Cos[x]^9 + 447 (I Sin[x])^9 Cos[x]^7 + 456 (I Sin[x])^8 Cos[x]^8 + 337 (I Sin[x])^10 Cos[x]^6 + 337 (I Sin[x])^6 Cos[x]^10 + 94 (I Sin[x])^12 Cos[x]^4 + 94 (I Sin[x])^4 Cos[x]^12 + 33 (I Sin[x])^3 Cos[x]^13 + 33 (I Sin[x])^13 Cos[x]^3 + 13 (I Sin[x])^2 Cos[x]^14 + 13 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[9 I y] (137 (I Sin[x])^9 Cos[x]^7 + 137 (I Sin[x])^7 Cos[x]^9 + 75 (I Sin[x])^11 Cos[x]^5 + 75 (I Sin[x])^5 Cos[x]^11 + 19 (I Sin[x])^13 Cos[x]^3 + 19 (I Sin[x])^3 Cos[x]^13 + 114 (I Sin[x])^6 Cos[x]^10 + 114 (I Sin[x])^10 Cos[x]^6 + 38 (I Sin[x])^12 Cos[x]^4 + 38 (I Sin[x])^4 Cos[x]^12 + 136 (I Sin[x])^8 Cos[x]^8 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2) + Exp[11 I y] (27 (I Sin[x])^6 Cos[x]^10 + 27 (I Sin[x])^10 Cos[x]^6 + 12 (I Sin[x])^4 Cos[x]^12 + 12 (I Sin[x])^12 Cos[x]^4 + 34 (I Sin[x])^8 Cos[x]^8 + 25 (I Sin[x])^7 Cos[x]^9 + 25 (I Sin[x])^9 Cos[x]^7 + 20 (I Sin[x])^11 Cos[x]^5 + 20 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^3 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^3) + Exp[13 I y] (6 (I Sin[x])^8 Cos[x]^8 + 3 (I Sin[x])^10 Cos[x]^6 + 3 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^4 Cos[x]^12 + 4 (I Sin[x])^7 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^7 + 3 (I Sin[x])^11 Cos[x]^5 + 3 (I Sin[x])^5 Cos[x]^11) + Exp[15 I y] (1 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^7))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^9 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^9) + Exp[-13 I y] (10 (I Sin[x])^8 Cos[x]^8 + 3 (I Sin[x])^6 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^6 + 5 (I Sin[x])^7 Cos[x]^9 + 5 (I Sin[x])^9 Cos[x]^7 + 2 (I Sin[x])^5 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^5) + Exp[-11 I y] (42 (I Sin[x])^8 Cos[x]^8 + 35 (I Sin[x])^10 Cos[x]^6 + 35 (I Sin[x])^6 Cos[x]^10 + 40 (I Sin[x])^9 Cos[x]^7 + 40 (I Sin[x])^7 Cos[x]^9 + 9 (I Sin[x])^11 Cos[x]^5 + 9 (I Sin[x])^5 Cos[x]^11) + Exp[-9 I y] (153 (I Sin[x])^9 Cos[x]^7 + 153 (I Sin[x])^7 Cos[x]^9 + 72 (I Sin[x])^5 Cos[x]^11 + 72 (I Sin[x])^11 Cos[x]^5 + 156 (I Sin[x])^8 Cos[x]^8 + 36 (I Sin[x])^4 Cos[x]^12 + 36 (I Sin[x])^12 Cos[x]^4 + 110 (I Sin[x])^10 Cos[x]^6 + 110 (I Sin[x])^6 Cos[x]^10 + 6 (I Sin[x])^3 Cos[x]^13 + 6 (I Sin[x])^13 Cos[x]^3) + Exp[-7 I y] (553 (I Sin[x])^9 Cos[x]^7 + 553 (I Sin[x])^7 Cos[x]^9 + 140 (I Sin[x])^11 Cos[x]^5 + 140 (I Sin[x])^5 Cos[x]^11 + 664 (I Sin[x])^8 Cos[x]^8 + 310 (I Sin[x])^10 Cos[x]^6 + 310 (I Sin[x])^6 Cos[x]^10 + 30 (I Sin[x])^12 Cos[x]^4 + 30 (I Sin[x])^4 Cos[x]^12) + Exp[-5 I y] (1074 (I Sin[x])^8 Cos[x]^8 + 778 (I Sin[x])^10 Cos[x]^6 + 778 (I Sin[x])^6 Cos[x]^10 + 981 (I Sin[x])^9 Cos[x]^7 + 981 (I Sin[x])^7 Cos[x]^9 + 443 (I Sin[x])^5 Cos[x]^11 + 443 (I Sin[x])^11 Cos[x]^5 + 186 (I Sin[x])^4 Cos[x]^12 + 186 (I Sin[x])^12 Cos[x]^4 + 67 (I Sin[x])^3 Cos[x]^13 + 67 (I Sin[x])^13 Cos[x]^3 + 11 (I Sin[x])^2 Cos[x]^14 + 11 (I Sin[x])^14 Cos[x]^2) + Exp[-3 I y] (1197 (I Sin[x])^10 Cos[x]^6 + 1197 (I Sin[x])^6 Cos[x]^10 + 2306 (I Sin[x])^8 Cos[x]^8 + 1950 (I Sin[x])^7 Cos[x]^9 + 1950 (I Sin[x])^9 Cos[x]^7 + 170 (I Sin[x])^12 Cos[x]^4 + 170 (I Sin[x])^4 Cos[x]^12 + 502 (I Sin[x])^11 Cos[x]^5 + 502 (I Sin[x])^5 Cos[x]^11 + 33 (I Sin[x])^13 Cos[x]^3 + 33 (I Sin[x])^3 Cos[x]^13) + Exp[-1 I y] (2151 (I Sin[x])^7 Cos[x]^9 + 2151 (I Sin[x])^9 Cos[x]^7 + 945 (I Sin[x])^11 Cos[x]^5 + 945 (I Sin[x])^5 Cos[x]^11 + 1551 (I Sin[x])^10 Cos[x]^6 + 1551 (I Sin[x])^6 Cos[x]^10 + 434 (I Sin[x])^12 Cos[x]^4 + 434 (I Sin[x])^4 Cos[x]^12 + 2356 (I Sin[x])^8 Cos[x]^8 + 133 (I Sin[x])^3 Cos[x]^13 + 133 (I Sin[x])^13 Cos[x]^3 + 37 (I Sin[x])^2 Cos[x]^14 + 37 (I Sin[x])^14 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^15 + 6 (I Sin[x])^15 Cos[x]^1) + Exp[1 I y] (821 (I Sin[x])^11 Cos[x]^5 + 821 (I Sin[x])^5 Cos[x]^11 + 2341 (I Sin[x])^9 Cos[x]^7 + 2341 (I Sin[x])^7 Cos[x]^9 + 1606 (I Sin[x])^6 Cos[x]^10 + 1606 (I Sin[x])^10 Cos[x]^6 + 2616 (I Sin[x])^8 Cos[x]^8 + 272 (I Sin[x])^12 Cos[x]^4 + 272 (I Sin[x])^4 Cos[x]^12 + 73 (I Sin[x])^13 Cos[x]^3 + 73 (I Sin[x])^3 Cos[x]^13 + 14 (I Sin[x])^2 Cos[x]^14 + 14 (I Sin[x])^14 Cos[x]^2) + Exp[3 I y] (1198 (I Sin[x])^6 Cos[x]^10 + 1198 (I Sin[x])^10 Cos[x]^6 + 1920 (I Sin[x])^8 Cos[x]^8 + 1671 (I Sin[x])^9 Cos[x]^7 + 1671 (I Sin[x])^7 Cos[x]^9 + 673 (I Sin[x])^11 Cos[x]^5 + 673 (I Sin[x])^5 Cos[x]^11 + 330 (I Sin[x])^4 Cos[x]^12 + 330 (I Sin[x])^12 Cos[x]^4 + 135 (I Sin[x])^3 Cos[x]^13 + 135 (I Sin[x])^13 Cos[x]^3 + 31 (I Sin[x])^2 Cos[x]^14 + 31 (I Sin[x])^14 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^15 + 6 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[5 I y] (739 (I Sin[x])^10 Cos[x]^6 + 739 (I Sin[x])^6 Cos[x]^10 + 1094 (I Sin[x])^8 Cos[x]^8 + 216 (I Sin[x])^12 Cos[x]^4 + 216 (I Sin[x])^4 Cos[x]^12 + 452 (I Sin[x])^5 Cos[x]^11 + 452 (I Sin[x])^11 Cos[x]^5 + 980 (I Sin[x])^9 Cos[x]^7 + 980 (I Sin[x])^7 Cos[x]^9 + 57 (I Sin[x])^3 Cos[x]^13 + 57 (I Sin[x])^13 Cos[x]^3 + 10 (I Sin[x])^14 Cos[x]^2 + 10 (I Sin[x])^2 Cos[x]^14 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[7 I y] (211 (I Sin[x])^5 Cos[x]^11 + 211 (I Sin[x])^11 Cos[x]^5 + 447 (I Sin[x])^7 Cos[x]^9 + 447 (I Sin[x])^9 Cos[x]^7 + 456 (I Sin[x])^8 Cos[x]^8 + 337 (I Sin[x])^10 Cos[x]^6 + 337 (I Sin[x])^6 Cos[x]^10 + 94 (I Sin[x])^12 Cos[x]^4 + 94 (I Sin[x])^4 Cos[x]^12 + 33 (I Sin[x])^3 Cos[x]^13 + 33 (I Sin[x])^13 Cos[x]^3 + 13 (I Sin[x])^2 Cos[x]^14 + 13 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[9 I y] (137 (I Sin[x])^9 Cos[x]^7 + 137 (I Sin[x])^7 Cos[x]^9 + 75 (I Sin[x])^11 Cos[x]^5 + 75 (I Sin[x])^5 Cos[x]^11 + 19 (I Sin[x])^13 Cos[x]^3 + 19 (I Sin[x])^3 Cos[x]^13 + 114 (I Sin[x])^6 Cos[x]^10 + 114 (I Sin[x])^10 Cos[x]^6 + 38 (I Sin[x])^12 Cos[x]^4 + 38 (I Sin[x])^4 Cos[x]^12 + 136 (I Sin[x])^8 Cos[x]^8 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2) + Exp[11 I y] (27 (I Sin[x])^6 Cos[x]^10 + 27 (I Sin[x])^10 Cos[x]^6 + 12 (I Sin[x])^4 Cos[x]^12 + 12 (I Sin[x])^12 Cos[x]^4 + 34 (I Sin[x])^8 Cos[x]^8 + 25 (I Sin[x])^7 Cos[x]^9 + 25 (I Sin[x])^9 Cos[x]^7 + 20 (I Sin[x])^11 Cos[x]^5 + 20 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^3 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^3) + Exp[13 I y] (6 (I Sin[x])^8 Cos[x]^8 + 3 (I Sin[x])^10 Cos[x]^6 + 3 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^4 Cos[x]^12 + 4 (I Sin[x])^7 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^7 + 3 (I Sin[x])^11 Cos[x]^5 + 3 (I Sin[x])^5 Cos[x]^11) + Exp[15 I y] (1 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^7));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":698.8666666667,"max_line_length":5017,"alphanum_fraction":0.5051035009} {"size":7363,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 13;\nname = \"13v4 1 2 4 1 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-12 I y] (1 (I Sin[x])^6 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^6) + Exp[-10 I y] (3 (I Sin[x])^5 Cos[x]^8 + 3 (I Sin[x])^8 Cos[x]^5 + 2 (I Sin[x])^6 Cos[x]^7 + 2 (I Sin[x])^7 Cos[x]^6 + 3 (I Sin[x])^4 Cos[x]^9 + 3 (I Sin[x])^9 Cos[x]^4 + 3 (I Sin[x])^3 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^3 + 1 (I Sin[x])^2 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^2) + Exp[-8 I y] (24 (I Sin[x])^7 Cos[x]^6 + 24 (I Sin[x])^6 Cos[x]^7 + 21 (I Sin[x])^5 Cos[x]^8 + 21 (I Sin[x])^8 Cos[x]^5 + 14 (I Sin[x])^4 Cos[x]^9 + 14 (I Sin[x])^9 Cos[x]^4 + 6 (I Sin[x])^3 Cos[x]^10 + 6 (I Sin[x])^10 Cos[x]^3 + 1 (I Sin[x])^2 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^2) + Exp[-6 I y] (47 (I Sin[x])^4 Cos[x]^9 + 47 (I Sin[x])^9 Cos[x]^4 + 65 (I Sin[x])^5 Cos[x]^8 + 65 (I Sin[x])^8 Cos[x]^5 + 21 (I Sin[x])^3 Cos[x]^10 + 21 (I Sin[x])^10 Cos[x]^3 + 77 (I Sin[x])^7 Cos[x]^6 + 77 (I Sin[x])^6 Cos[x]^7 + 8 (I Sin[x])^2 Cos[x]^11 + 8 (I Sin[x])^11 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^1) + Exp[-4 I y] (207 (I Sin[x])^6 Cos[x]^7 + 207 (I Sin[x])^7 Cos[x]^6 + 162 (I Sin[x])^8 Cos[x]^5 + 162 (I Sin[x])^5 Cos[x]^8 + 86 (I Sin[x])^4 Cos[x]^9 + 86 (I Sin[x])^9 Cos[x]^4 + 31 (I Sin[x])^3 Cos[x]^10 + 31 (I Sin[x])^10 Cos[x]^3 + 8 (I Sin[x])^11 Cos[x]^2 + 8 (I Sin[x])^2 Cos[x]^11 + 1 (I Sin[x])^1 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^1) + Exp[-2 I y] (72 (I Sin[x])^3 Cos[x]^10 + 72 (I Sin[x])^10 Cos[x]^3 + 305 (I Sin[x])^6 Cos[x]^7 + 305 (I Sin[x])^7 Cos[x]^6 + 144 (I Sin[x])^4 Cos[x]^9 + 144 (I Sin[x])^9 Cos[x]^4 + 23 (I Sin[x])^2 Cos[x]^11 + 23 (I Sin[x])^11 Cos[x]^2 + 242 (I Sin[x])^5 Cos[x]^8 + 242 (I Sin[x])^8 Cos[x]^5 + 5 (I Sin[x])^1 Cos[x]^12 + 5 (I Sin[x])^12 Cos[x]^1 + 1 Cos[x]^13 + 1 (I Sin[x])^13) + Exp[0 I y] (287 (I Sin[x])^5 Cos[x]^8 + 287 (I Sin[x])^8 Cos[x]^5 + 146 (I Sin[x])^9 Cos[x]^4 + 146 (I Sin[x])^4 Cos[x]^9 + 429 (I Sin[x])^7 Cos[x]^6 + 429 (I Sin[x])^6 Cos[x]^7 + 51 (I Sin[x])^10 Cos[x]^3 + 51 (I Sin[x])^3 Cos[x]^10 + 10 (I Sin[x])^2 Cos[x]^11 + 10 (I Sin[x])^11 Cos[x]^2 + 1 (I Sin[x])^12 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^12) + Exp[2 I y] (145 (I Sin[x])^4 Cos[x]^9 + 145 (I Sin[x])^9 Cos[x]^4 + 243 (I Sin[x])^5 Cos[x]^8 + 243 (I Sin[x])^8 Cos[x]^5 + 321 (I Sin[x])^7 Cos[x]^6 + 321 (I Sin[x])^6 Cos[x]^7 + 59 (I Sin[x])^3 Cos[x]^10 + 59 (I Sin[x])^10 Cos[x]^3 + 20 (I Sin[x])^2 Cos[x]^11 + 20 (I Sin[x])^11 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^12 + 4 (I Sin[x])^12 Cos[x]^1) + Exp[4 I y] (226 (I Sin[x])^6 Cos[x]^7 + 226 (I Sin[x])^7 Cos[x]^6 + 171 (I Sin[x])^8 Cos[x]^5 + 171 (I Sin[x])^5 Cos[x]^8 + 75 (I Sin[x])^4 Cos[x]^9 + 75 (I Sin[x])^9 Cos[x]^4 + 20 (I Sin[x])^3 Cos[x]^10 + 20 (I Sin[x])^10 Cos[x]^3 + 3 (I Sin[x])^11 Cos[x]^2 + 3 (I Sin[x])^2 Cos[x]^11) + Exp[6 I y] (21 (I Sin[x])^3 Cos[x]^10 + 21 (I Sin[x])^10 Cos[x]^3 + 81 (I Sin[x])^6 Cos[x]^7 + 81 (I Sin[x])^7 Cos[x]^6 + 70 (I Sin[x])^5 Cos[x]^8 + 70 (I Sin[x])^8 Cos[x]^5 + 44 (I Sin[x])^4 Cos[x]^9 + 44 (I Sin[x])^9 Cos[x]^4 + 4 (I Sin[x])^2 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^2) + Exp[8 I y] (37 (I Sin[x])^7 Cos[x]^6 + 37 (I Sin[x])^6 Cos[x]^7 + 18 (I Sin[x])^5 Cos[x]^8 + 18 (I Sin[x])^8 Cos[x]^5 + 9 (I Sin[x])^9 Cos[x]^4 + 9 (I Sin[x])^4 Cos[x]^9 + 2 (I Sin[x])^10 Cos[x]^3 + 2 (I Sin[x])^3 Cos[x]^10) + Exp[10 I y] (2 (I Sin[x])^4 Cos[x]^9 + 2 (I Sin[x])^9 Cos[x]^4 + 6 (I Sin[x])^7 Cos[x]^6 + 6 (I Sin[x])^6 Cos[x]^7 + 4 (I Sin[x])^5 Cos[x]^8 + 4 (I Sin[x])^8 Cos[x]^5) + Exp[12 I y] (1 (I Sin[x])^8 Cos[x]^5 + 1 (I Sin[x])^5 Cos[x]^8))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-12 I y] (1 (I Sin[x])^6 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^6) + Exp[-10 I y] (3 (I Sin[x])^5 Cos[x]^8 + 3 (I Sin[x])^8 Cos[x]^5 + 2 (I Sin[x])^6 Cos[x]^7 + 2 (I Sin[x])^7 Cos[x]^6 + 3 (I Sin[x])^4 Cos[x]^9 + 3 (I Sin[x])^9 Cos[x]^4 + 3 (I Sin[x])^3 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^3 + 1 (I Sin[x])^2 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^2) + Exp[-8 I y] (24 (I Sin[x])^7 Cos[x]^6 + 24 (I Sin[x])^6 Cos[x]^7 + 21 (I Sin[x])^5 Cos[x]^8 + 21 (I Sin[x])^8 Cos[x]^5 + 14 (I Sin[x])^4 Cos[x]^9 + 14 (I Sin[x])^9 Cos[x]^4 + 6 (I Sin[x])^3 Cos[x]^10 + 6 (I Sin[x])^10 Cos[x]^3 + 1 (I Sin[x])^2 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^2) + Exp[-6 I y] (47 (I Sin[x])^4 Cos[x]^9 + 47 (I Sin[x])^9 Cos[x]^4 + 65 (I Sin[x])^5 Cos[x]^8 + 65 (I Sin[x])^8 Cos[x]^5 + 21 (I Sin[x])^3 Cos[x]^10 + 21 (I Sin[x])^10 Cos[x]^3 + 77 (I Sin[x])^7 Cos[x]^6 + 77 (I Sin[x])^6 Cos[x]^7 + 8 (I Sin[x])^2 Cos[x]^11 + 8 (I Sin[x])^11 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^1) + Exp[-4 I y] (207 (I Sin[x])^6 Cos[x]^7 + 207 (I Sin[x])^7 Cos[x]^6 + 162 (I Sin[x])^8 Cos[x]^5 + 162 (I Sin[x])^5 Cos[x]^8 + 86 (I Sin[x])^4 Cos[x]^9 + 86 (I Sin[x])^9 Cos[x]^4 + 31 (I Sin[x])^3 Cos[x]^10 + 31 (I Sin[x])^10 Cos[x]^3 + 8 (I Sin[x])^11 Cos[x]^2 + 8 (I Sin[x])^2 Cos[x]^11 + 1 (I Sin[x])^1 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^1) + Exp[-2 I y] (72 (I Sin[x])^3 Cos[x]^10 + 72 (I Sin[x])^10 Cos[x]^3 + 305 (I Sin[x])^6 Cos[x]^7 + 305 (I Sin[x])^7 Cos[x]^6 + 144 (I Sin[x])^4 Cos[x]^9 + 144 (I Sin[x])^9 Cos[x]^4 + 23 (I Sin[x])^2 Cos[x]^11 + 23 (I Sin[x])^11 Cos[x]^2 + 242 (I Sin[x])^5 Cos[x]^8 + 242 (I Sin[x])^8 Cos[x]^5 + 5 (I Sin[x])^1 Cos[x]^12 + 5 (I Sin[x])^12 Cos[x]^1 + 1 Cos[x]^13 + 1 (I Sin[x])^13) + Exp[0 I y] (287 (I Sin[x])^5 Cos[x]^8 + 287 (I Sin[x])^8 Cos[x]^5 + 146 (I Sin[x])^9 Cos[x]^4 + 146 (I Sin[x])^4 Cos[x]^9 + 429 (I Sin[x])^7 Cos[x]^6 + 429 (I Sin[x])^6 Cos[x]^7 + 51 (I Sin[x])^10 Cos[x]^3 + 51 (I Sin[x])^3 Cos[x]^10 + 10 (I Sin[x])^2 Cos[x]^11 + 10 (I Sin[x])^11 Cos[x]^2 + 1 (I Sin[x])^12 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^12) + Exp[2 I y] (145 (I Sin[x])^4 Cos[x]^9 + 145 (I Sin[x])^9 Cos[x]^4 + 243 (I Sin[x])^5 Cos[x]^8 + 243 (I Sin[x])^8 Cos[x]^5 + 321 (I Sin[x])^7 Cos[x]^6 + 321 (I Sin[x])^6 Cos[x]^7 + 59 (I Sin[x])^3 Cos[x]^10 + 59 (I Sin[x])^10 Cos[x]^3 + 20 (I Sin[x])^2 Cos[x]^11 + 20 (I Sin[x])^11 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^12 + 4 (I Sin[x])^12 Cos[x]^1) + Exp[4 I y] (226 (I Sin[x])^6 Cos[x]^7 + 226 (I Sin[x])^7 Cos[x]^6 + 171 (I Sin[x])^8 Cos[x]^5 + 171 (I Sin[x])^5 Cos[x]^8 + 75 (I Sin[x])^4 Cos[x]^9 + 75 (I Sin[x])^9 Cos[x]^4 + 20 (I Sin[x])^3 Cos[x]^10 + 20 (I Sin[x])^10 Cos[x]^3 + 3 (I Sin[x])^11 Cos[x]^2 + 3 (I Sin[x])^2 Cos[x]^11) + Exp[6 I y] (21 (I Sin[x])^3 Cos[x]^10 + 21 (I Sin[x])^10 Cos[x]^3 + 81 (I Sin[x])^6 Cos[x]^7 + 81 (I Sin[x])^7 Cos[x]^6 + 70 (I Sin[x])^5 Cos[x]^8 + 70 (I Sin[x])^8 Cos[x]^5 + 44 (I Sin[x])^4 Cos[x]^9 + 44 (I Sin[x])^9 Cos[x]^4 + 4 (I Sin[x])^2 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^2) + Exp[8 I y] (37 (I Sin[x])^7 Cos[x]^6 + 37 (I Sin[x])^6 Cos[x]^7 + 18 (I Sin[x])^5 Cos[x]^8 + 18 (I Sin[x])^8 Cos[x]^5 + 9 (I Sin[x])^9 Cos[x]^4 + 9 (I Sin[x])^4 Cos[x]^9 + 2 (I Sin[x])^10 Cos[x]^3 + 2 (I Sin[x])^3 Cos[x]^10) + Exp[10 I y] (2 (I Sin[x])^4 Cos[x]^9 + 2 (I Sin[x])^9 Cos[x]^4 + 6 (I Sin[x])^7 Cos[x]^6 + 6 (I Sin[x])^6 Cos[x]^7 + 4 (I Sin[x])^5 Cos[x]^8 + 4 (I Sin[x])^8 Cos[x]^5) + Exp[12 I y] (1 (I Sin[x])^8 Cos[x]^5 + 1 (I Sin[x])^5 Cos[x]^8));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":490.8666666667,"max_line_length":3461,"alphanum_fraction":0.4923264974} {"size":8399,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 14;\nname = \"14v2 4 1 1 1 2 1 1 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-13 I y] (1 (I Sin[x])^8 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^8) + Exp[-11 I y] (4 (I Sin[x])^9 Cos[x]^5 + 4 (I Sin[x])^5 Cos[x]^9 + 5 (I Sin[x])^8 Cos[x]^6 + 5 (I Sin[x])^6 Cos[x]^8 + 1 (I Sin[x])^4 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^4 + 6 (I Sin[x])^7 Cos[x]^7) + Exp[-9 I y] (44 (I Sin[x])^7 Cos[x]^7 + 18 (I Sin[x])^9 Cos[x]^5 + 18 (I Sin[x])^5 Cos[x]^9 + 28 (I Sin[x])^8 Cos[x]^6 + 28 (I Sin[x])^6 Cos[x]^8 + 8 (I Sin[x])^4 Cos[x]^10 + 8 (I Sin[x])^10 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^3) + Exp[-7 I y] (27 (I Sin[x])^10 Cos[x]^4 + 27 (I Sin[x])^4 Cos[x]^10 + 119 (I Sin[x])^6 Cos[x]^8 + 119 (I Sin[x])^8 Cos[x]^6 + 128 (I Sin[x])^7 Cos[x]^7 + 72 (I Sin[x])^5 Cos[x]^9 + 72 (I Sin[x])^9 Cos[x]^5 + 4 (I Sin[x])^3 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^3) + Exp[-5 I y] (261 (I Sin[x])^6 Cos[x]^8 + 261 (I Sin[x])^8 Cos[x]^6 + 264 (I Sin[x])^7 Cos[x]^7 + 182 (I Sin[x])^5 Cos[x]^9 + 182 (I Sin[x])^9 Cos[x]^5 + 97 (I Sin[x])^10 Cos[x]^4 + 97 (I Sin[x])^4 Cos[x]^10 + 36 (I Sin[x])^3 Cos[x]^11 + 36 (I Sin[x])^11 Cos[x]^3 + 7 (I Sin[x])^2 Cos[x]^12 + 7 (I Sin[x])^12 Cos[x]^2) + Exp[-3 I y] (292 (I Sin[x])^9 Cos[x]^5 + 292 (I Sin[x])^5 Cos[x]^9 + 648 (I Sin[x])^7 Cos[x]^7 + 35 (I Sin[x])^11 Cos[x]^3 + 35 (I Sin[x])^3 Cos[x]^11 + 510 (I Sin[x])^8 Cos[x]^6 + 510 (I Sin[x])^6 Cos[x]^8 + 122 (I Sin[x])^10 Cos[x]^4 + 122 (I Sin[x])^4 Cos[x]^10 + 4 (I Sin[x])^2 Cos[x]^12 + 4 (I Sin[x])^12 Cos[x]^2) + Exp[-1 I y] (702 (I Sin[x])^7 Cos[x]^7 + 427 (I Sin[x])^5 Cos[x]^9 + 427 (I Sin[x])^9 Cos[x]^5 + 600 (I Sin[x])^6 Cos[x]^8 + 600 (I Sin[x])^8 Cos[x]^6 + 222 (I Sin[x])^4 Cos[x]^10 + 222 (I Sin[x])^10 Cos[x]^4 + 85 (I Sin[x])^11 Cos[x]^3 + 85 (I Sin[x])^3 Cos[x]^11 + 26 (I Sin[x])^2 Cos[x]^12 + 26 (I Sin[x])^12 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^13 + 5 (I Sin[x])^13 Cos[x]^1) + Exp[1 I y] (682 (I Sin[x])^8 Cos[x]^6 + 682 (I Sin[x])^6 Cos[x]^8 + 174 (I Sin[x])^10 Cos[x]^4 + 174 (I Sin[x])^4 Cos[x]^10 + 12 (I Sin[x])^12 Cos[x]^2 + 12 (I Sin[x])^2 Cos[x]^12 + 419 (I Sin[x])^9 Cos[x]^5 + 419 (I Sin[x])^5 Cos[x]^9 + 754 (I Sin[x])^7 Cos[x]^7 + 51 (I Sin[x])^11 Cos[x]^3 + 51 (I Sin[x])^3 Cos[x]^11 + 1 (I Sin[x])^1 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^1) + Exp[3 I y] (440 (I Sin[x])^8 Cos[x]^6 + 440 (I Sin[x])^6 Cos[x]^8 + 186 (I Sin[x])^4 Cos[x]^10 + 186 (I Sin[x])^10 Cos[x]^4 + 307 (I Sin[x])^5 Cos[x]^9 + 307 (I Sin[x])^9 Cos[x]^5 + 85 (I Sin[x])^3 Cos[x]^11 + 85 (I Sin[x])^11 Cos[x]^3 + 478 (I Sin[x])^7 Cos[x]^7 + 24 (I Sin[x])^2 Cos[x]^12 + 24 (I Sin[x])^12 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^13 + 5 (I Sin[x])^13 Cos[x]^1 + 1 Cos[x]^14 + 1 (I Sin[x])^14) + Exp[5 I y] (292 (I Sin[x])^7 Cos[x]^7 + 183 (I Sin[x])^5 Cos[x]^9 + 183 (I Sin[x])^9 Cos[x]^5 + 35 (I Sin[x])^11 Cos[x]^3 + 35 (I Sin[x])^3 Cos[x]^11 + 241 (I Sin[x])^8 Cos[x]^6 + 241 (I Sin[x])^6 Cos[x]^8 + 103 (I Sin[x])^10 Cos[x]^4 + 103 (I Sin[x])^4 Cos[x]^10 + 6 (I Sin[x])^2 Cos[x]^12 + 6 (I Sin[x])^12 Cos[x]^2 + 1 (I Sin[x])^13 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^13) + Exp[7 I y] (90 (I Sin[x])^7 Cos[x]^7 + 76 (I Sin[x])^5 Cos[x]^9 + 76 (I Sin[x])^9 Cos[x]^5 + 23 (I Sin[x])^3 Cos[x]^11 + 23 (I Sin[x])^11 Cos[x]^3 + 46 (I Sin[x])^4 Cos[x]^10 + 46 (I Sin[x])^10 Cos[x]^4 + 84 (I Sin[x])^8 Cos[x]^6 + 84 (I Sin[x])^6 Cos[x]^8 + 10 (I Sin[x])^2 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^1) + Exp[9 I y] (27 (I Sin[x])^6 Cos[x]^8 + 27 (I Sin[x])^8 Cos[x]^6 + 13 (I Sin[x])^4 Cos[x]^10 + 13 (I Sin[x])^10 Cos[x]^4 + 18 (I Sin[x])^7 Cos[x]^7 + 20 (I Sin[x])^9 Cos[x]^5 + 20 (I Sin[x])^5 Cos[x]^9 + 2 (I Sin[x])^12 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^12 + 7 (I Sin[x])^11 Cos[x]^3 + 7 (I Sin[x])^3 Cos[x]^11) + Exp[11 I y] (5 (I Sin[x])^6 Cos[x]^8 + 5 (I Sin[x])^8 Cos[x]^6 + 2 (I Sin[x])^4 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^4 + 2 (I Sin[x])^5 Cos[x]^9 + 2 (I Sin[x])^9 Cos[x]^5 + 6 (I Sin[x])^7 Cos[x]^7 + 1 (I Sin[x])^3 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^3) + Exp[13 I y] (2 (I Sin[x])^7 Cos[x]^7))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-13 I y] (1 (I Sin[x])^8 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^8) + Exp[-11 I y] (4 (I Sin[x])^9 Cos[x]^5 + 4 (I Sin[x])^5 Cos[x]^9 + 5 (I Sin[x])^8 Cos[x]^6 + 5 (I Sin[x])^6 Cos[x]^8 + 1 (I Sin[x])^4 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^4 + 6 (I Sin[x])^7 Cos[x]^7) + Exp[-9 I y] (44 (I Sin[x])^7 Cos[x]^7 + 18 (I Sin[x])^9 Cos[x]^5 + 18 (I Sin[x])^5 Cos[x]^9 + 28 (I Sin[x])^8 Cos[x]^6 + 28 (I Sin[x])^6 Cos[x]^8 + 8 (I Sin[x])^4 Cos[x]^10 + 8 (I Sin[x])^10 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^3) + Exp[-7 I y] (27 (I Sin[x])^10 Cos[x]^4 + 27 (I Sin[x])^4 Cos[x]^10 + 119 (I Sin[x])^6 Cos[x]^8 + 119 (I Sin[x])^8 Cos[x]^6 + 128 (I Sin[x])^7 Cos[x]^7 + 72 (I Sin[x])^5 Cos[x]^9 + 72 (I Sin[x])^9 Cos[x]^5 + 4 (I Sin[x])^3 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^3) + Exp[-5 I y] (261 (I Sin[x])^6 Cos[x]^8 + 261 (I Sin[x])^8 Cos[x]^6 + 264 (I Sin[x])^7 Cos[x]^7 + 182 (I Sin[x])^5 Cos[x]^9 + 182 (I Sin[x])^9 Cos[x]^5 + 97 (I Sin[x])^10 Cos[x]^4 + 97 (I Sin[x])^4 Cos[x]^10 + 36 (I Sin[x])^3 Cos[x]^11 + 36 (I Sin[x])^11 Cos[x]^3 + 7 (I Sin[x])^2 Cos[x]^12 + 7 (I Sin[x])^12 Cos[x]^2) + Exp[-3 I y] (292 (I Sin[x])^9 Cos[x]^5 + 292 (I Sin[x])^5 Cos[x]^9 + 648 (I Sin[x])^7 Cos[x]^7 + 35 (I Sin[x])^11 Cos[x]^3 + 35 (I Sin[x])^3 Cos[x]^11 + 510 (I Sin[x])^8 Cos[x]^6 + 510 (I Sin[x])^6 Cos[x]^8 + 122 (I Sin[x])^10 Cos[x]^4 + 122 (I Sin[x])^4 Cos[x]^10 + 4 (I Sin[x])^2 Cos[x]^12 + 4 (I Sin[x])^12 Cos[x]^2) + Exp[-1 I y] (702 (I Sin[x])^7 Cos[x]^7 + 427 (I Sin[x])^5 Cos[x]^9 + 427 (I Sin[x])^9 Cos[x]^5 + 600 (I Sin[x])^6 Cos[x]^8 + 600 (I Sin[x])^8 Cos[x]^6 + 222 (I Sin[x])^4 Cos[x]^10 + 222 (I Sin[x])^10 Cos[x]^4 + 85 (I Sin[x])^11 Cos[x]^3 + 85 (I Sin[x])^3 Cos[x]^11 + 26 (I Sin[x])^2 Cos[x]^12 + 26 (I Sin[x])^12 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^13 + 5 (I Sin[x])^13 Cos[x]^1) + Exp[1 I y] (682 (I Sin[x])^8 Cos[x]^6 + 682 (I Sin[x])^6 Cos[x]^8 + 174 (I Sin[x])^10 Cos[x]^4 + 174 (I Sin[x])^4 Cos[x]^10 + 12 (I Sin[x])^12 Cos[x]^2 + 12 (I Sin[x])^2 Cos[x]^12 + 419 (I Sin[x])^9 Cos[x]^5 + 419 (I Sin[x])^5 Cos[x]^9 + 754 (I Sin[x])^7 Cos[x]^7 + 51 (I Sin[x])^11 Cos[x]^3 + 51 (I Sin[x])^3 Cos[x]^11 + 1 (I Sin[x])^1 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^1) + Exp[3 I y] (440 (I Sin[x])^8 Cos[x]^6 + 440 (I Sin[x])^6 Cos[x]^8 + 186 (I Sin[x])^4 Cos[x]^10 + 186 (I Sin[x])^10 Cos[x]^4 + 307 (I Sin[x])^5 Cos[x]^9 + 307 (I Sin[x])^9 Cos[x]^5 + 85 (I Sin[x])^3 Cos[x]^11 + 85 (I Sin[x])^11 Cos[x]^3 + 478 (I Sin[x])^7 Cos[x]^7 + 24 (I Sin[x])^2 Cos[x]^12 + 24 (I Sin[x])^12 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^13 + 5 (I Sin[x])^13 Cos[x]^1 + 1 Cos[x]^14 + 1 (I Sin[x])^14) + Exp[5 I y] (292 (I Sin[x])^7 Cos[x]^7 + 183 (I Sin[x])^5 Cos[x]^9 + 183 (I Sin[x])^9 Cos[x]^5 + 35 (I Sin[x])^11 Cos[x]^3 + 35 (I Sin[x])^3 Cos[x]^11 + 241 (I Sin[x])^8 Cos[x]^6 + 241 (I Sin[x])^6 Cos[x]^8 + 103 (I Sin[x])^10 Cos[x]^4 + 103 (I Sin[x])^4 Cos[x]^10 + 6 (I Sin[x])^2 Cos[x]^12 + 6 (I Sin[x])^12 Cos[x]^2 + 1 (I Sin[x])^13 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^13) + Exp[7 I y] (90 (I Sin[x])^7 Cos[x]^7 + 76 (I Sin[x])^5 Cos[x]^9 + 76 (I Sin[x])^9 Cos[x]^5 + 23 (I Sin[x])^3 Cos[x]^11 + 23 (I Sin[x])^11 Cos[x]^3 + 46 (I Sin[x])^4 Cos[x]^10 + 46 (I Sin[x])^10 Cos[x]^4 + 84 (I Sin[x])^8 Cos[x]^6 + 84 (I Sin[x])^6 Cos[x]^8 + 10 (I Sin[x])^2 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^1) + Exp[9 I y] (27 (I Sin[x])^6 Cos[x]^8 + 27 (I Sin[x])^8 Cos[x]^6 + 13 (I Sin[x])^4 Cos[x]^10 + 13 (I Sin[x])^10 Cos[x]^4 + 18 (I Sin[x])^7 Cos[x]^7 + 20 (I Sin[x])^9 Cos[x]^5 + 20 (I Sin[x])^5 Cos[x]^9 + 2 (I Sin[x])^12 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^12 + 7 (I Sin[x])^11 Cos[x]^3 + 7 (I Sin[x])^3 Cos[x]^11) + Exp[11 I y] (5 (I Sin[x])^6 Cos[x]^8 + 5 (I Sin[x])^8 Cos[x]^6 + 2 (I Sin[x])^4 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^4 + 2 (I Sin[x])^5 Cos[x]^9 + 2 (I Sin[x])^9 Cos[x]^5 + 6 (I Sin[x])^7 Cos[x]^7 + 1 (I Sin[x])^3 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^3) + Exp[13 I y] (2 (I Sin[x])^7 Cos[x]^7));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":559.9333333333,"max_line_length":3976,"alphanum_fraction":0.4960114299} {"size":150096,"ext":"ma","lang":"Mathematica","max_stars_count":507.0,"content":"\/\/Maya ASCII 2022 scene\n\/\/Name: StandardSurfaceTextured.ma\n\/\/Last modified: Mon, Jun 07, 2021 02:49:26 PM\n\/\/Codeset: 1252\nrequires maya \"2022\";\ncurrentUnit -l centimeter -a degree -t film;\nfileInfo \"application\" \"maya\";\nfileInfo \"product\" \"Maya 2022\";\nfileInfo \"version\" \"2022\";\nfileInfo \"cutIdentifier\" \"202105132251-000000\";\nfileInfo \"osv\" \"Windows 10 Pro v2009 (Build: 19042)\";\nfileInfo \"UUID\" \"BBF35912-4F9D-AFD4-E4E9-D79E73854682\";\ncreateNode transform -s -n \"persp\";\n\trename -uid \"24FF1A5E-4D07-42C5-B5DE-108A06885039\";\n\tsetAttr \".v\" no;\n\tsetAttr \".t\" -type \"double3\" 3.259358747191099 2.438679137033104 12.630772311505096 ;\n\tsetAttr \".r\" -type \"double3\" 2.6616472703979617 -1.7999999999999707 -6.2150876328019062e-18 ;\ncreateNode camera -s -n \"perspShape\" -p \"persp\";\n\trename -uid \"8B8E43C3-4FDC-04D4-4795-CD9BBF274BB0\";\n\tsetAttr -k off \".v\" no;\n\tsetAttr \".fl\" 34.999999999999993;\n\tsetAttr \".coi\" 13.127716318418864;\n\tsetAttr \".imn\" -type \"string\" \"persp\";\n\tsetAttr \".den\" -type \"string\" \"persp_depth\";\n\tsetAttr \".man\" -type \"string\" \"persp_mask\";\n\tsetAttr \".hc\" -type \"string\" \"viewSet -p %camera\";\ncreateNode transform -s -n \"top\";\n\trename -uid \"CB0BF38D-4ECC-E71F-3212-E28369226577\";\n\tsetAttr \".v\" no;\n\tsetAttr \".t\" -type \"double3\" 0 1000.1 0 ;\n\tsetAttr \".r\" -type \"double3\" -90 0 0 ;\ncreateNode camera -s -n \"topShape\" -p \"top\";\n\trename -uid \"B1D7072C-4014-8C30-2E67-66A490104EA7\";\n\tsetAttr -k off \".v\" no;\n\tsetAttr \".rnd\" no;\n\tsetAttr \".coi\" 1000.1;\n\tsetAttr \".ow\" 30;\n\tsetAttr \".imn\" -type \"string\" \"top\";\n\tsetAttr \".den\" -type \"string\" \"top_depth\";\n\tsetAttr \".man\" -type \"string\" \"top_mask\";\n\tsetAttr \".hc\" -type \"string\" \"viewSet -t %camera\";\n\tsetAttr \".o\" yes;\ncreateNode transform -s -n \"front\";\n\trename -uid \"400E3199-4A7F-98C9-2BAF-9AA6DBDDEC0E\";\n\tsetAttr \".v\" no;\n\tsetAttr \".t\" -type \"double3\" 0 0 1000.1 ;\ncreateNode camera -s -n \"frontShape\" -p \"front\";\n\trename -uid \"7738B3F9-4A1D-82BC-2334-08BFA3B9312C\";\n\tsetAttr -k off \".v\" no;\n\tsetAttr \".rnd\" no;\n\tsetAttr \".coi\" 1000.1;\n\tsetAttr \".ow\" 30;\n\tsetAttr \".imn\" -type \"string\" \"front\";\n\tsetAttr \".den\" -type \"string\" \"front_depth\";\n\tsetAttr \".man\" -type \"string\" \"front_mask\";\n\tsetAttr \".hc\" -type \"string\" \"viewSet -f %camera\";\n\tsetAttr \".o\" yes;\ncreateNode transform -s -n \"side\";\n\trename -uid \"3A481E19-436D-A40E-EFAC-3796263EEC4B\";\n\tsetAttr \".v\" no;\n\tsetAttr \".t\" -type \"double3\" 1000.1 0 0 ;\n\tsetAttr \".r\" -type \"double3\" 0 90 0 ;\ncreateNode camera -s -n \"sideShape\" -p \"side\";\n\trename -uid \"E70E78A5-4858-2B0D-2582-018D94F941D9\";\n\tsetAttr -k off \".v\" no;\n\tsetAttr \".rnd\" no;\n\tsetAttr \".coi\" 1000.1;\n\tsetAttr \".ow\" 30;\n\tsetAttr \".imn\" -type \"string\" \"side\";\n\tsetAttr \".den\" -type \"string\" \"side_depth\";\n\tsetAttr \".man\" -type \"string\" \"side_mask\";\n\tsetAttr \".hc\" -type \"string\" \"viewSet -s %camera\";\n\tsetAttr \".o\" yes;\ncreateNode transform -n \"pPlane1\";\n\trename -uid \"DC85BEB3-44A2-3EB3-2AFE-D3A5FFFDFE7D\";\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape1\" -p \"pPlane1\";\n\trename -uid \"4D3DDAFD-4ACC-2290-A833-269BF2BE46F8\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\ncreateNode transform -n \"pPlane2\";\n\trename -uid \"34A78470-4898-8464-E052-6EABFA5A3CB6\";\n\tsetAttr \".t\" -type \"double3\" 1.5 0 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape2\" -p \"pPlane2\";\n\trename -uid \"5C137301-47AB-8D02-50E1-09A7497E1DE1\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane3\";\n\trename -uid \"D9D612F2-4D2E-0243-EDE1-93A8E7397EDB\";\n\tsetAttr \".t\" -type \"double3\" 3 0 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape3\" -p \"pPlane3\";\n\trename -uid \"238FC141-4B8D-F6BE-C214-DD9BB39EAE05\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane4\";\n\trename -uid \"0D681A23-425B-F66F-A318-79AFA51A23CD\";\n\tsetAttr \".t\" -type \"double3\" 0 1.5 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape4\" -p \"pPlane4\";\n\trename -uid \"3686EBC9-4B7D-49B0-008B-DEA1E41EA613\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane5\";\n\trename -uid \"E1EA692F-40EF-86EB-3F34-83A1C59C74DC\";\n\tsetAttr \".t\" -type \"double3\" 0 3 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape5\" -p \"pPlane5\";\n\trename -uid \"0F9435EC-49D8-85BB-6596-42B40E80CE4F\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane6\";\n\trename -uid \"5BC17800-4437-33FC-B560-58950F9F04C7\";\n\tsetAttr \".t\" -type \"double3\" 0 4.5 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape6\" -p \"pPlane6\";\n\trename -uid \"CCE17BB1-4CC4-6B3F-C6E2-9CBEA02F96B2\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane7\";\n\trename -uid \"58656AAC-4090-4324-F9D8-2E8DE0E106B5\";\n\tsetAttr \".t\" -type \"double3\" 0 6 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape7\" -p \"pPlane7\";\n\trename -uid \"51264081-4922-33CA-7D58-69BE3853FD69\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane8\";\n\trename -uid \"33D7D0D3-4557-3043-24D3-6482B25D29E9\";\n\tsetAttr \".t\" -type \"double3\" 1.5 1.5 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape8\" -p \"pPlane8\";\n\trename -uid \"FA300D98-42CD-8F28-49A0-E39D9D430AD1\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane9\";\n\trename -uid \"61F10F6C-4003-870F-D0A0-1BA177F262F9\";\n\tsetAttr \".t\" -type \"double3\" 3 1.5 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape9\" -p \"pPlane9\";\n\trename -uid \"E0E41CC6-4F6F-E21D-4E0A-64947CD8E0F1\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane10\";\n\trename -uid \"42C62517-46CC-469B-F6E7-889EA386F5D4\";\n\tsetAttr \".t\" -type \"double3\" 4.5 1.5 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape10\" -p \"pPlane10\";\n\trename -uid \"3CA601EB-409E-1751-056A-8B872BA34AD3\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane11\";\n\trename -uid \"01CBE328-4043-BFBB-4034-9E95079C83CE\";\n\tsetAttr \".t\" -type \"double3\" 6 1.5 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape11\" -p \"pPlane11\";\n\trename -uid \"D60B3A72-4BAF-AEF9-064D-13B909F12F01\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane12\";\n\trename -uid \"27D502C4-4421-2887-75C7-E59A3FD0CF24\";\n\tsetAttr \".t\" -type \"double3\" 7.5 1.5 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape12\" -p \"pPlane12\";\n\trename -uid \"6593CC62-4A30-D203-7F6B-57A05CBDEAED\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane13\";\n\trename -uid \"638F9C18-45BE-2955-F226-E3BA0DEEEE92\";\n\tsetAttr \".t\" -type \"double3\" 7.5 3 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape13\" -p \"pPlane13\";\n\trename -uid \"A48FF4B5-4C17-512F-DED5-F69A2489E917\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane14\";\n\trename -uid \"FB993937-4682-85EC-8304-7EB2372710C3\";\n\tsetAttr \".t\" -type \"double3\" 4.5 0 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape14\" -p \"pPlane14\";\n\trename -uid \"8A390196-4649-1BA8-30B2-759685E5C8A6\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane15\";\n\trename -uid \"B29BEE70-4F68-A599-8954-E1A621962761\";\n\tsetAttr \".t\" -type \"double3\" 6 0 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape15\" -p \"pPlane15\";\n\trename -uid \"1386AA18-46F1-B4B6-2847-83B67C9D9DB2\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane16\";\n\trename -uid \"E356420A-4088-D4E3-99BC-DBB9A82B546F\";\n\tsetAttr \".t\" -type \"double3\" 1.5 3 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape16\" -p \"pPlane16\";\n\trename -uid \"EBF22FFC-4914-EFB8-6D54-F28C150BEEC1\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane17\";\n\trename -uid \"B9ECF996-4464-AE64-1F3D-6BA4698F16EB\";\n\tsetAttr \".t\" -type \"double3\" 3 3 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape17\" -p \"pPlane17\";\n\trename -uid \"D8DB7185-4950-4601-FFBD-5686DF095E62\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane18\";\n\trename -uid \"B2009D84-479B-DD5E-D279-24846D38DE0C\";\n\tsetAttr \".t\" -type \"double3\" 4.5 3 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape18\" -p \"pPlane18\";\n\trename -uid \"4F56C8D1-40E5-18C6-D51D-BFA414E77A3D\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane19\";\n\trename -uid \"A62F482F-4A79-5E20-B40B-B0AF26F97AB2\";\n\tsetAttr \".t\" -type \"double3\" 1.5 4.5 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape19\" -p \"pPlane19\";\n\trename -uid \"2E884DC7-4632-DBA0-FD50-D99BA2B190C7\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane20\";\n\trename -uid \"F788D7E1-4B55-DACD-833F-95B92BA7417A\";\n\tsetAttr \".t\" -type \"double3\" 3 4.5 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape20\" -p \"pPlane20\";\n\trename -uid \"B577B602-480B-4D8E-37C1-8FB0AF596D40\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane21\";\n\trename -uid \"1FCE37D7-46BC-4F0D-80D0-7A9D218F7CE1\";\n\tsetAttr \".t\" -type \"double3\" 4.5 4.5 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape21\" -p \"pPlane21\";\n\trename -uid \"771514A0-4591-1B53-E72B-A9862F3E6BD5\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane22\";\n\trename -uid \"C9AB893C-4F95-44C3-1639-3288ABC4B0C1\";\n\tsetAttr \".t\" -type \"double3\" 6 4.5 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape22\" -p \"pPlane22\";\n\trename -uid \"591656E6-4104-2827-CC9B-D3A008B759FF\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane23\";\n\trename -uid \"39E1EF14-4473-E737-FAAD-3F840B27D383\";\n\tsetAttr \".t\" -type \"double3\" 1.5 6 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape23\" -p \"pPlane23\";\n\trename -uid \"ECB87A0C-456E-C7BE-AD66-7BB5E94FBBFC\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane24\";\n\trename -uid \"CE48A02F-41BA-0E8C-A797-568CA29B2CA2\";\n\tsetAttr \".t\" -type \"double3\" 3 6 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape24\" -p \"pPlane24\";\n\trename -uid \"122DC0C6-49F8-D626-68EC-B59A6A920E32\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane25\";\n\trename -uid \"1FFA8203-448E-7937-66D2-109B76A35CB4\";\n\tsetAttr \".t\" -type \"double3\" 4.5 6 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape25\" -p \"pPlane25\";\n\trename -uid \"FF828AD5-4183-3F40-C471-09891170E42F\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane26\";\n\trename -uid \"B052EB8A-479F-FD48-A371-1FA21E15FDE2\";\n\tsetAttr \".t\" -type \"double3\" 6 6 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape26\" -p \"pPlane26\";\n\trename -uid \"FD7F5FDE-45F4-9EFD-29AA-25A99B3ABC57\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode transform -n \"pPlane27\";\n\trename -uid \"88FF0872-4EB4-F53C-3854-7D81E089D85E\";\n\tsetAttr \".t\" -type \"double3\" 6 3 0 ;\n\tsetAttr \".r\" -type \"double3\" 90 0 0 ;\ncreateNode mesh -n \"pPlaneShape27\" -p \"pPlane27\";\n\trename -uid \"A106B157-4BBE-C5BC-39C1-25B4EC2F3230\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".pv\" -type \"double2\" 0.5 0.5 ;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr -s 4 \".uvst[0].uvsp[0:3]\" -type \"float2\" -0.5274725 -0.99364352\n\t\t 1.5274725 -0.99364352 -0.5274725 1.99364352 1.5274725 1.99364352;\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr -s 4 \".vt[0:3]\" -0.5 0 0.5 0.5 0 0.5 -0.5 0 -0.5 0.5 0 -0.5;\n\tsetAttr -s 4 \".ed[0:3]\" 0 1 0 0 2 0 1 3 0 2 3 0;\n\tsetAttr -ch 4 \".fc[0]\" -type \"polyFaces\" \n\t\tf 4 0 2 -4 -2\n\t\tmu 0 4 0 1 3 2;\n\tsetAttr \".cd\" -type \"dataPolyComponent\" Index_Data Edge 0 ;\n\tsetAttr \".cvd\" -type \"dataPolyComponent\" Index_Data Vertex 0 ;\n\tsetAttr \".pd[0]\" -type \"dataPolyComponent\" Index_Data UV 0 ;\n\tsetAttr \".hfd\" -type \"dataPolyComponent\" Index_Data Face 0 ;\ncreateNode lightLinker -s -n \"lightLinker1\";\n\trename -uid \"D26C6FA1-47EA-4A8D-4350-999A02DED112\";\n\tsetAttr -s 29 \".lnk\";\n\tsetAttr -s 29 \".slnk\";\ncreateNode shapeEditorManager -n \"shapeEditorManager\";\n\trename -uid \"F4C31350-46E1-593A-3DF2-AC9657D13461\";\ncreateNode poseInterpolatorManager -n \"poseInterpolatorManager\";\n\trename -uid \"7BDB661B-4272-57EC-1D1B-2EB8EB62597C\";\ncreateNode displayLayerManager -n \"layerManager\";\n\trename -uid \"9350F104-482D-A34F-E82F-81AFBB3ABAF8\";\ncreateNode displayLayer -n \"defaultLayer\";\n\trename -uid \"D3605426-4E0C-8536-53C1-38BAAF696533\";\ncreateNode renderLayerManager -n \"renderLayerManager\";\n\trename -uid \"50AEC475-4E90-DDC3-0AE3-B490AF288A75\";\ncreateNode renderLayer -n \"defaultRenderLayer\";\n\trename -uid \"DEF989DC-4FDC-CDAD-8B54-B4B38769D4C1\";\n\tsetAttr \".g\" yes;\ncreateNode polyPlane -n \"polyPlane1\";\n\trename -uid \"486ED238-43EE-340D-88D4-7AA32602DB81\";\n\tsetAttr \".sw\" 1;\n\tsetAttr \".sh\" 1;\n\tsetAttr \".cuv\" 2;\ncreateNode standardSurface -n \"standardSurface2\";\n\trename -uid \"CEB21399-44FE-4118-F91D-A9B963BC5B07\";\ncreateNode shadingEngine -n \"standardSurface2SG\";\n\trename -uid \"DD36D833-4C81-BA1B-00E2-5C95F128C942\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo1\";\n\trename -uid \"28AAFD65-4C6A-5364-23C3-F284BAB13C9B\";\ncreateNode file -n \"file1\";\n\trename -uid \"7FAF8E25-4D5C-D6EC-C5EC-018FCBD30E9B\";\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/RGB.png\";\n\tsetAttr \".cs\" -type \"string\" \"sRGB\";\ncreateNode place2dTexture -n \"place2dTexture1\";\n\trename -uid \"BD2EFBBB-44B8-6A05-82FC-C5BF0D62C61D\";\ncreateNode polyTweakUV -n \"polyTweakUV1\";\n\trename -uid \"07A15C62-40AA-E247-A0E7-4BACD2289FEB\";\n\tsetAttr \".uopa\" yes;\n\tsetAttr -s 4 \".uvtk[0:3]\" -type \"float2\" -0.5274725 -0.99364352 0.5274725\n\t\t -0.99364352 -0.5274725 0.99364352 0.5274725 0.99364352;\ncreateNode standardSurface -n \"standardSurface3\";\n\trename -uid \"DEF7DB9D-4170-52FA-64F7-9A957E636017\";\ncreateNode shadingEngine -n \"standardSurface3SG\";\n\trename -uid \"E6BBEFD0-4266-5738-36C7-97B990A395E8\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo2\";\n\trename -uid \"E3B71177-49F4-870F-38E7-019C8632059D\";\ncreateNode file -n \"file2\";\n\trename -uid \"EF4E02DD-44F4-CFE1-04BA-FFA4AF13E172\";\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/RGB.png\";\n\tsetAttr \".cs\" -type \"string\" \"sRGB\";\ncreateNode place2dTexture -n \"place2dTexture2\";\n\trename -uid \"6DD418D2-4CD4-4F59-0568-DD86F98D0C98\";\n\tsetAttr \".mu\" yes;\n\tsetAttr \".mv\" yes;\ncreateNode standardSurface -n \"standardSurface4\";\n\trename -uid \"FA3A4724-4243-B043-2844-80ABA38F994E\";\ncreateNode shadingEngine -n \"standardSurface4SG\";\n\trename -uid \"42485728-4766-117B-DB44-B6902938AEFC\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo3\";\n\trename -uid \"3BB43488-4D60-9C52-BA03-2C9AA7127B5F\";\ncreateNode file -n \"file3\";\n\trename -uid \"2DC2F8C6-4CCF-4A94-948A-849C5FFD7030\";\n\tsetAttr \".dc\" -type \"float3\" 1 0.31760001 0 ;\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/RGB.png\";\n\tsetAttr \".cs\" -type \"string\" \"sRGB\";\ncreateNode place2dTexture -n \"place2dTexture3\";\n\trename -uid \"E7E9BED1-4E6C-7E40-792D-238200EA283E\";\n\tsetAttr \".wu\" no;\n\tsetAttr \".wv\" no;\ncreateNode script -n \"uiConfigurationScriptNode\";\n\trename -uid \"624F8451-427A-6646-6EB5-0FBBC9D3AEDC\";\n\tsetAttr \".b\" -type \"string\" (\n\t\t\"\/\/ Maya Mel UI Configuration File.\\n\/\/\\n\/\/ This script is machine generated. Edit at your own risk.\\n\/\/\\n\/\/\\n\\nglobal string $gMainPane;\\nif (`paneLayout -exists $gMainPane`) {\\n\\n\\tglobal int $gUseScenePanelConfig;\\n\\tint $useSceneConfig = $gUseScenePanelConfig;\\n\\tint $nodeEditorPanelVisible = stringArrayContains(\\\"nodeEditorPanel1\\\", `getPanel -vis`);\\n\\tint $nodeEditorWorkspaceControlOpen = (`workspaceControl -exists nodeEditorPanel1Window` && `workspaceControl -q -visible nodeEditorPanel1Window`);\\n\\tint $menusOkayInPanels = `optionVar -q allowMenusInPanels`;\\n\\tint $nVisPanes = `paneLayout -q -nvp $gMainPane`;\\n\\tint $nPanes = 0;\\n\\tstring $editorName;\\n\\tstring $panelName;\\n\\tstring $itemFilterName;\\n\\tstring $panelConfig;\\n\\n\\t\/\/\\n\\t\/\/ get current state of the UI\\n\\t\/\/\\n\\tsceneUIReplacement -update $gMainPane;\\n\\n\\t$panelName = `sceneUIReplacement -getNextPanel \\\"modelPanel\\\" (localizedPanelLabel(\\\"Top View\\\")) `;\\n\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tmodelPanel -edit -l (localizedPanelLabel(\\\"Top View\\\")) -mbv $menusOkayInPanels $panelName;\\n\"\n\t\t+ \"\\t\\t$editorName = $panelName;\\n modelEditor -e \\n -camera \\\"|top|topShape\\\" \\n -useInteractiveMode 0\\n -displayLights \\\"default\\\" \\n -displayAppearance \\\"smoothShaded\\\" \\n -activeOnly 0\\n -ignorePanZoom 0\\n -wireframeOnShaded 0\\n -headsUpDisplay 1\\n -holdOuts 1\\n -selectionHiliteDisplay 1\\n -useDefaultMaterial 0\\n -bufferMode \\\"double\\\" \\n -twoSidedLighting 0\\n -backfaceCulling 0\\n -xray 0\\n -jointXray 0\\n -activeComponentsXray 0\\n -displayTextures 0\\n -smoothWireframe 0\\n -lineWidth 1\\n -textureAnisotropic 0\\n -textureHilight 1\\n -textureSampling 2\\n -textureDisplay \\\"modulate\\\" \\n -textureMaxSize 16384\\n -fogging 0\\n -fogSource \\\"fragment\\\" \\n -fogMode \\\"linear\\\" \\n -fogStart 0\\n -fogEnd 100\\n -fogDensity 0.1\\n -fogColor 0.5 0.5 0.5 1 \\n\"\n\t\t+ \" -depthOfFieldPreview 1\\n -maxConstantTransparency 1\\n -rendererName \\\"vp2Renderer\\\" \\n -objectFilterShowInHUD 1\\n -isFiltered 0\\n -colorResolution 256 256 \\n -bumpResolution 512 512 \\n -textureCompression 0\\n -transparencyAlgorithm \\\"frontAndBackCull\\\" \\n -transpInShadows 0\\n -cullingOverride \\\"none\\\" \\n -lowQualityLighting 0\\n -maximumNumHardwareLights 1\\n -occlusionCulling 0\\n -shadingModel 0\\n -useBaseRenderer 0\\n -useReducedRenderer 0\\n -smallObjectCulling 0\\n -smallObjectThreshold -1 \\n -interactiveDisableShadows 0\\n -interactiveBackFaceCull 0\\n -sortTransparent 1\\n -controllers 1\\n -nurbsCurves 1\\n -nurbsSurfaces 1\\n -polymeshes 1\\n -subdivSurfaces 1\\n -planes 1\\n -lights 1\\n -cameras 1\\n -controlVertices 1\\n\"\n\t\t+ \" -hulls 1\\n -grid 1\\n -imagePlane 1\\n -joints 1\\n -ikHandles 1\\n -deformers 1\\n -dynamics 1\\n -particleInstancers 1\\n -fluids 1\\n -hairSystems 1\\n -follicles 1\\n -nCloths 1\\n -nParticles 1\\n -nRigids 1\\n -dynamicConstraints 1\\n -locators 1\\n -manipulators 1\\n -pluginShapes 1\\n -dimensions 1\\n -handles 1\\n -pivots 1\\n -textures 1\\n -strokes 1\\n -motionTrails 1\\n -clipGhosts 1\\n -greasePencils 1\\n -shadows 0\\n -captureSequenceNumber -1\\n -width 1\\n -height 1\\n -sceneRenderFilter 0\\n $editorName;\\n modelEditor -e -viewSelected 0 $editorName;\\n modelEditor -e \\n -pluginObjects \\\"gpuCacheDisplayFilter\\\" 1 \\n $editorName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\"\n\t\t+ \"\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextPanel \\\"modelPanel\\\" (localizedPanelLabel(\\\"Side View\\\")) `;\\n\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tmodelPanel -edit -l (localizedPanelLabel(\\\"Side View\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\t$editorName = $panelName;\\n modelEditor -e \\n -camera \\\"|side|sideShape\\\" \\n -useInteractiveMode 0\\n -displayLights \\\"default\\\" \\n -displayAppearance \\\"smoothShaded\\\" \\n -activeOnly 0\\n -ignorePanZoom 0\\n -wireframeOnShaded 0\\n -headsUpDisplay 1\\n -holdOuts 1\\n -selectionHiliteDisplay 1\\n -useDefaultMaterial 0\\n -bufferMode \\\"double\\\" \\n -twoSidedLighting 0\\n -backfaceCulling 0\\n -xray 0\\n -jointXray 0\\n -activeComponentsXray 0\\n -displayTextures 0\\n -smoothWireframe 0\\n -lineWidth 1\\n -textureAnisotropic 0\\n -textureHilight 1\\n -textureSampling 2\\n\"\n\t\t+ \" -textureDisplay \\\"modulate\\\" \\n -textureMaxSize 16384\\n -fogging 0\\n -fogSource \\\"fragment\\\" \\n -fogMode \\\"linear\\\" \\n -fogStart 0\\n -fogEnd 100\\n -fogDensity 0.1\\n -fogColor 0.5 0.5 0.5 1 \\n -depthOfFieldPreview 1\\n -maxConstantTransparency 1\\n -rendererName \\\"vp2Renderer\\\" \\n -objectFilterShowInHUD 1\\n -isFiltered 0\\n -colorResolution 256 256 \\n -bumpResolution 512 512 \\n -textureCompression 0\\n -transparencyAlgorithm \\\"frontAndBackCull\\\" \\n -transpInShadows 0\\n -cullingOverride \\\"none\\\" \\n -lowQualityLighting 0\\n -maximumNumHardwareLights 1\\n -occlusionCulling 0\\n -shadingModel 0\\n -useBaseRenderer 0\\n -useReducedRenderer 0\\n -smallObjectCulling 0\\n -smallObjectThreshold -1 \\n -interactiveDisableShadows 0\\n -interactiveBackFaceCull 0\\n\"\n\t\t+ \" -sortTransparent 1\\n -controllers 1\\n -nurbsCurves 1\\n -nurbsSurfaces 1\\n -polymeshes 1\\n -subdivSurfaces 1\\n -planes 1\\n -lights 1\\n -cameras 1\\n -controlVertices 1\\n -hulls 1\\n -grid 1\\n -imagePlane 1\\n -joints 1\\n -ikHandles 1\\n -deformers 1\\n -dynamics 1\\n -particleInstancers 1\\n -fluids 1\\n -hairSystems 1\\n -follicles 1\\n -nCloths 1\\n -nParticles 1\\n -nRigids 1\\n -dynamicConstraints 1\\n -locators 1\\n -manipulators 1\\n -pluginShapes 1\\n -dimensions 1\\n -handles 1\\n -pivots 1\\n -textures 1\\n -strokes 1\\n -motionTrails 1\\n -clipGhosts 1\\n -greasePencils 1\\n -shadows 0\\n -captureSequenceNumber -1\\n -width 1\\n -height 1\\n\"\n\t\t+ \" -sceneRenderFilter 0\\n $editorName;\\n modelEditor -e -viewSelected 0 $editorName;\\n modelEditor -e \\n -pluginObjects \\\"gpuCacheDisplayFilter\\\" 1 \\n $editorName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextPanel \\\"modelPanel\\\" (localizedPanelLabel(\\\"Front View\\\")) `;\\n\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tmodelPanel -edit -l (localizedPanelLabel(\\\"Front View\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\t$editorName = $panelName;\\n modelEditor -e \\n -camera \\\"|front|frontShape\\\" \\n -useInteractiveMode 0\\n -displayLights \\\"default\\\" \\n -displayAppearance \\\"smoothShaded\\\" \\n -activeOnly 0\\n -ignorePanZoom 0\\n -wireframeOnShaded 0\\n -headsUpDisplay 1\\n -holdOuts 1\\n -selectionHiliteDisplay 1\\n -useDefaultMaterial 0\\n -bufferMode \\\"double\\\" \\n -twoSidedLighting 0\\n\"\n\t\t+ \" -backfaceCulling 0\\n -xray 0\\n -jointXray 0\\n -activeComponentsXray 0\\n -displayTextures 0\\n -smoothWireframe 0\\n -lineWidth 1\\n -textureAnisotropic 0\\n -textureHilight 1\\n -textureSampling 2\\n -textureDisplay \\\"modulate\\\" \\n -textureMaxSize 16384\\n -fogging 0\\n -fogSource \\\"fragment\\\" \\n -fogMode \\\"linear\\\" \\n -fogStart 0\\n -fogEnd 100\\n -fogDensity 0.1\\n -fogColor 0.5 0.5 0.5 1 \\n -depthOfFieldPreview 1\\n -maxConstantTransparency 1\\n -rendererName \\\"vp2Renderer\\\" \\n -objectFilterShowInHUD 1\\n -isFiltered 0\\n -colorResolution 256 256 \\n -bumpResolution 512 512 \\n -textureCompression 0\\n -transparencyAlgorithm \\\"frontAndBackCull\\\" \\n -transpInShadows 0\\n -cullingOverride \\\"none\\\" \\n -lowQualityLighting 0\\n -maximumNumHardwareLights 1\\n\"\n\t\t+ \" -occlusionCulling 0\\n -shadingModel 0\\n -useBaseRenderer 0\\n -useReducedRenderer 0\\n -smallObjectCulling 0\\n -smallObjectThreshold -1 \\n -interactiveDisableShadows 0\\n -interactiveBackFaceCull 0\\n -sortTransparent 1\\n -controllers 1\\n -nurbsCurves 1\\n -nurbsSurfaces 1\\n -polymeshes 1\\n -subdivSurfaces 1\\n -planes 1\\n -lights 1\\n -cameras 1\\n -controlVertices 1\\n -hulls 1\\n -grid 1\\n -imagePlane 1\\n -joints 1\\n -ikHandles 1\\n -deformers 1\\n -dynamics 1\\n -particleInstancers 1\\n -fluids 1\\n -hairSystems 1\\n -follicles 1\\n -nCloths 1\\n -nParticles 1\\n -nRigids 1\\n -dynamicConstraints 1\\n -locators 1\\n -manipulators 1\\n -pluginShapes 1\\n -dimensions 1\\n\"\n\t\t+ \" -handles 1\\n -pivots 1\\n -textures 1\\n -strokes 1\\n -motionTrails 1\\n -clipGhosts 1\\n -greasePencils 1\\n -shadows 0\\n -captureSequenceNumber -1\\n -width 1\\n -height 1\\n -sceneRenderFilter 0\\n $editorName;\\n modelEditor -e -viewSelected 0 $editorName;\\n modelEditor -e \\n -pluginObjects \\\"gpuCacheDisplayFilter\\\" 1 \\n $editorName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextPanel \\\"modelPanel\\\" (localizedPanelLabel(\\\"Persp View\\\")) `;\\n\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tmodelPanel -edit -l (localizedPanelLabel(\\\"Persp View\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\t$editorName = $panelName;\\n modelEditor -e \\n -camera \\\"|persp|perspShape\\\" \\n -useInteractiveMode 0\\n -displayLights \\\"default\\\" \\n -displayAppearance \\\"smoothShaded\\\" \\n\"\n\t\t+ \" -activeOnly 0\\n -ignorePanZoom 0\\n -wireframeOnShaded 0\\n -headsUpDisplay 1\\n -holdOuts 1\\n -selectionHiliteDisplay 1\\n -useDefaultMaterial 0\\n -bufferMode \\\"double\\\" \\n -twoSidedLighting 0\\n -backfaceCulling 0\\n -xray 0\\n -jointXray 0\\n -activeComponentsXray 0\\n -displayTextures 1\\n -smoothWireframe 0\\n -lineWidth 1\\n -textureAnisotropic 0\\n -textureHilight 1\\n -textureSampling 2\\n -textureDisplay \\\"modulate\\\" \\n -textureMaxSize 16384\\n -fogging 0\\n -fogSource \\\"fragment\\\" \\n -fogMode \\\"linear\\\" \\n -fogStart 0\\n -fogEnd 100\\n -fogDensity 0.1\\n -fogColor 0.5 0.5 0.5 1 \\n -depthOfFieldPreview 1\\n -maxConstantTransparency 1\\n -rendererName \\\"vp2Renderer\\\" \\n -objectFilterShowInHUD 1\\n -isFiltered 0\\n\"\n\t\t+ \" -colorResolution 256 256 \\n -bumpResolution 512 512 \\n -textureCompression 0\\n -transparencyAlgorithm \\\"frontAndBackCull\\\" \\n -transpInShadows 0\\n -cullingOverride \\\"none\\\" \\n -lowQualityLighting 0\\n -maximumNumHardwareLights 1\\n -occlusionCulling 0\\n -shadingModel 0\\n -useBaseRenderer 0\\n -useReducedRenderer 0\\n -smallObjectCulling 0\\n -smallObjectThreshold -1 \\n -interactiveDisableShadows 0\\n -interactiveBackFaceCull 0\\n -sortTransparent 1\\n -controllers 1\\n -nurbsCurves 1\\n -nurbsSurfaces 1\\n -polymeshes 1\\n -subdivSurfaces 1\\n -planes 1\\n -lights 1\\n -cameras 1\\n -controlVertices 1\\n -hulls 1\\n -grid 1\\n -imagePlane 1\\n -joints 1\\n -ikHandles 1\\n -deformers 1\\n -dynamics 1\\n -particleInstancers 1\\n\"\n\t\t+ \" -fluids 1\\n -hairSystems 1\\n -follicles 1\\n -nCloths 1\\n -nParticles 1\\n -nRigids 1\\n -dynamicConstraints 1\\n -locators 1\\n -manipulators 1\\n -pluginShapes 1\\n -dimensions 1\\n -handles 1\\n -pivots 1\\n -textures 1\\n -strokes 1\\n -motionTrails 1\\n -clipGhosts 1\\n -greasePencils 1\\n -shadows 0\\n -captureSequenceNumber -1\\n -width 1759\\n -height 1092\\n -sceneRenderFilter 0\\n $editorName;\\n modelEditor -e -viewSelected 0 $editorName;\\n modelEditor -e \\n -pluginObjects \\\"gpuCacheDisplayFilter\\\" 1 \\n $editorName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextPanel \\\"outlinerPanel\\\" (localizedPanelLabel(\\\"ToggledOutliner\\\")) `;\\n\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\"\n\t\t+ \"\\t\\toutlinerPanel -edit -l (localizedPanelLabel(\\\"ToggledOutliner\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\t$editorName = $panelName;\\n outlinerEditor -e \\n -docTag \\\"isolOutln_fromSeln\\\" \\n -showShapes 0\\n -showAssignedMaterials 0\\n -showTimeEditor 1\\n -showReferenceNodes 1\\n -showReferenceMembers 1\\n -showAttributes 0\\n -showConnected 0\\n -showAnimCurvesOnly 0\\n -showMuteInfo 0\\n -organizeByLayer 1\\n -organizeByClip 1\\n -showAnimLayerWeight 1\\n -autoExpandLayers 1\\n -autoExpand 0\\n -showDagOnly 1\\n -showAssets 1\\n -showContainedOnly 1\\n -showPublishedAsConnected 0\\n -showParentContainers 0\\n -showContainerContents 1\\n -ignoreDagHierarchy 0\\n -expandConnections 0\\n -showUpstreamCurves 1\\n -showUnitlessCurves 1\\n -showCompounds 1\\n -showLeafs 1\\n\"\n\t\t+ \" -showNumericAttrsOnly 0\\n -highlightActive 1\\n -autoSelectNewObjects 0\\n -doNotSelectNewObjects 0\\n -dropIsParent 1\\n -transmitFilters 0\\n -setFilter \\\"defaultSetFilter\\\" \\n -showSetMembers 1\\n -allowMultiSelection 1\\n -alwaysToggleSelect 0\\n -directSelect 0\\n -isSet 0\\n -isSetMember 0\\n -displayMode \\\"DAG\\\" \\n -expandObjects 0\\n -setsIgnoreFilters 1\\n -containersIgnoreFilters 0\\n -editAttrName 0\\n -showAttrValues 0\\n -highlightSecondary 0\\n -showUVAttrsOnly 0\\n -showTextureNodesOnly 0\\n -attrAlphaOrder \\\"default\\\" \\n -animLayerFilterOptions \\\"allAffecting\\\" \\n -sortOrder \\\"none\\\" \\n -longNames 0\\n -niceNames 1\\n -showNamespace 1\\n -showPinIcons 0\\n -mapMotionTrails 0\\n -ignoreHiddenAttribute 0\\n -ignoreOutlinerColor 0\\n\"\n\t\t+ \" -renderFilterVisible 0\\n -renderFilterIndex 0\\n -selectionOrder \\\"chronological\\\" \\n -expandAttribute 0\\n $editorName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextPanel \\\"outlinerPanel\\\" (localizedPanelLabel(\\\"Outliner\\\")) `;\\n\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\toutlinerPanel -edit -l (localizedPanelLabel(\\\"Outliner\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\t$editorName = $panelName;\\n outlinerEditor -e \\n -showShapes 0\\n -showAssignedMaterials 0\\n -showTimeEditor 1\\n -showReferenceNodes 0\\n -showReferenceMembers 0\\n -showAttributes 0\\n -showConnected 0\\n -showAnimCurvesOnly 0\\n -showMuteInfo 0\\n -organizeByLayer 1\\n -organizeByClip 1\\n -showAnimLayerWeight 1\\n -autoExpandLayers 1\\n -autoExpand 0\\n -showDagOnly 1\\n -showAssets 1\\n\"\n\t\t+ \" -showContainedOnly 1\\n -showPublishedAsConnected 0\\n -showParentContainers 0\\n -showContainerContents 1\\n -ignoreDagHierarchy 0\\n -expandConnections 0\\n -showUpstreamCurves 1\\n -showUnitlessCurves 1\\n -showCompounds 1\\n -showLeafs 1\\n -showNumericAttrsOnly 0\\n -highlightActive 1\\n -autoSelectNewObjects 0\\n -doNotSelectNewObjects 0\\n -dropIsParent 1\\n -transmitFilters 0\\n -setFilter \\\"defaultSetFilter\\\" \\n -showSetMembers 1\\n -allowMultiSelection 1\\n -alwaysToggleSelect 0\\n -directSelect 0\\n -displayMode \\\"DAG\\\" \\n -expandObjects 0\\n -setsIgnoreFilters 1\\n -containersIgnoreFilters 0\\n -editAttrName 0\\n -showAttrValues 0\\n -highlightSecondary 0\\n -showUVAttrsOnly 0\\n -showTextureNodesOnly 0\\n -attrAlphaOrder \\\"default\\\" \\n\"\n\t\t+ \" -animLayerFilterOptions \\\"allAffecting\\\" \\n -sortOrder \\\"none\\\" \\n -longNames 0\\n -niceNames 1\\n -showNamespace 1\\n -showPinIcons 0\\n -mapMotionTrails 0\\n -ignoreHiddenAttribute 0\\n -ignoreOutlinerColor 0\\n -renderFilterVisible 0\\n $editorName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"graphEditor\\\" (localizedPanelLabel(\\\"Graph Editor\\\")) `;\\n\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Graph Editor\\\")) -mbv $menusOkayInPanels $panelName;\\n\\n\\t\\t\\t$editorName = ($panelName+\\\"OutlineEd\\\");\\n outlinerEditor -e \\n -showShapes 1\\n -showAssignedMaterials 0\\n -showTimeEditor 1\\n -showReferenceNodes 0\\n -showReferenceMembers 0\\n -showAttributes 1\\n -showConnected 1\\n -showAnimCurvesOnly 1\\n\"\n\t\t+ \" -showMuteInfo 0\\n -organizeByLayer 1\\n -organizeByClip 1\\n -showAnimLayerWeight 1\\n -autoExpandLayers 1\\n -autoExpand 1\\n -showDagOnly 0\\n -showAssets 1\\n -showContainedOnly 0\\n -showPublishedAsConnected 0\\n -showParentContainers 0\\n -showContainerContents 0\\n -ignoreDagHierarchy 0\\n -expandConnections 1\\n -showUpstreamCurves 1\\n -showUnitlessCurves 1\\n -showCompounds 0\\n -showLeafs 1\\n -showNumericAttrsOnly 1\\n -highlightActive 0\\n -autoSelectNewObjects 1\\n -doNotSelectNewObjects 0\\n -dropIsParent 1\\n -transmitFilters 1\\n -setFilter \\\"0\\\" \\n -showSetMembers 0\\n -allowMultiSelection 1\\n -alwaysToggleSelect 0\\n -directSelect 0\\n\"\n\t\t+ \" -displayMode \\\"DAG\\\" \\n -expandObjects 0\\n -setsIgnoreFilters 1\\n -containersIgnoreFilters 0\\n -editAttrName 0\\n -showAttrValues 0\\n -highlightSecondary 0\\n -showUVAttrsOnly 0\\n -showTextureNodesOnly 0\\n -attrAlphaOrder \\\"default\\\" \\n -animLayerFilterOptions \\\"allAffecting\\\" \\n -sortOrder \\\"none\\\" \\n -longNames 0\\n -niceNames 1\\n -showNamespace 1\\n -showPinIcons 1\\n -mapMotionTrails 1\\n -ignoreHiddenAttribute 0\\n -ignoreOutlinerColor 0\\n -renderFilterVisible 0\\n $editorName;\\n\\n\\t\\t\\t$editorName = ($panelName+\\\"GraphEd\\\");\\n animCurveEditor -e \\n -displayValues 0\\n -snapTime \\\"integer\\\" \\n -snapValue \\\"none\\\" \\n -showPlayRangeShades \\\"on\\\" \\n -lockPlayRangeShades \\\"off\\\" \\n\"\n\t\t+ \" -smoothness \\\"fine\\\" \\n -resultSamples 1\\n -resultScreenSamples 0\\n -resultUpdate \\\"delayed\\\" \\n -showUpstreamCurves 1\\n -keyMinScale 1\\n -stackedCurvesMin -1\\n -stackedCurvesMax 1\\n -stackedCurvesSpace 0.2\\n -preSelectionHighlight 0\\n -constrainDrag 0\\n -valueLinesToggle 1\\n -highlightAffectedCurves 0\\n $editorName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"dopeSheetPanel\\\" (localizedPanelLabel(\\\"Dope Sheet\\\")) `;\\n\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Dope Sheet\\\")) -mbv $menusOkayInPanels $panelName;\\n\\n\\t\\t\\t$editorName = ($panelName+\\\"OutlineEd\\\");\\n outlinerEditor -e \\n -showShapes 1\\n -showAssignedMaterials 0\\n -showTimeEditor 1\\n\"\n\t\t+ \" -showReferenceNodes 0\\n -showReferenceMembers 0\\n -showAttributes 1\\n -showConnected 1\\n -showAnimCurvesOnly 1\\n -showMuteInfo 0\\n -organizeByLayer 1\\n -organizeByClip 1\\n -showAnimLayerWeight 1\\n -autoExpandLayers 1\\n -autoExpand 0\\n -showDagOnly 0\\n -showAssets 1\\n -showContainedOnly 0\\n -showPublishedAsConnected 0\\n -showParentContainers 0\\n -showContainerContents 0\\n -ignoreDagHierarchy 0\\n -expandConnections 1\\n -showUpstreamCurves 1\\n -showUnitlessCurves 0\\n -showCompounds 1\\n -showLeafs 1\\n -showNumericAttrsOnly 1\\n -highlightActive 0\\n -autoSelectNewObjects 0\\n -doNotSelectNewObjects 1\\n -dropIsParent 1\\n -transmitFilters 0\\n\"\n\t\t+ \" -setFilter \\\"0\\\" \\n -showSetMembers 0\\n -allowMultiSelection 1\\n -alwaysToggleSelect 0\\n -directSelect 0\\n -displayMode \\\"DAG\\\" \\n -expandObjects 0\\n -setsIgnoreFilters 1\\n -containersIgnoreFilters 0\\n -editAttrName 0\\n -showAttrValues 0\\n -highlightSecondary 0\\n -showUVAttrsOnly 0\\n -showTextureNodesOnly 0\\n -attrAlphaOrder \\\"default\\\" \\n -animLayerFilterOptions \\\"allAffecting\\\" \\n -sortOrder \\\"none\\\" \\n -longNames 0\\n -niceNames 1\\n -showNamespace 1\\n -showPinIcons 0\\n -mapMotionTrails 1\\n -ignoreHiddenAttribute 0\\n -ignoreOutlinerColor 0\\n -renderFilterVisible 0\\n $editorName;\\n\\n\\t\\t\\t$editorName = ($panelName+\\\"DopeSheetEd\\\");\\n dopeSheetEditor -e \\n -displayValues 0\\n\"\n\t\t+ \" -snapTime \\\"integer\\\" \\n -snapValue \\\"none\\\" \\n -outliner \\\"dopeSheetPanel1OutlineEd\\\" \\n -showSummary 1\\n -showScene 0\\n -hierarchyBelow 0\\n -showTicks 1\\n -selectionWindow 0 0 0 0 \\n $editorName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"timeEditorPanel\\\" (localizedPanelLabel(\\\"Time Editor\\\")) `;\\n\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Time Editor\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"clipEditorPanel\\\" (localizedPanelLabel(\\\"Trax Editor\\\")) `;\\n\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Trax Editor\\\")) -mbv $menusOkayInPanels $panelName;\\n\\n\\t\\t\\t$editorName = clipEditorNameFromPanel($panelName);\\n\"\n\t\t+ \" clipEditor -e \\n -displayValues 0\\n -snapTime \\\"none\\\" \\n -snapValue \\\"none\\\" \\n -initialized 0\\n -manageSequencer 0 \\n $editorName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"sequenceEditorPanel\\\" (localizedPanelLabel(\\\"Camera Sequencer\\\")) `;\\n\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Camera Sequencer\\\")) -mbv $menusOkayInPanels $panelName;\\n\\n\\t\\t\\t$editorName = sequenceEditorNameFromPanel($panelName);\\n clipEditor -e \\n -displayValues 0\\n -snapTime \\\"none\\\" \\n -snapValue \\\"none\\\" \\n -initialized 0\\n -manageSequencer 1 \\n $editorName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"hyperGraphPanel\\\" (localizedPanelLabel(\\\"Hypergraph Hierarchy\\\")) `;\\n\"\n\t\t+ \"\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Hypergraph Hierarchy\\\")) -mbv $menusOkayInPanels $panelName;\\n\\n\\t\\t\\t$editorName = ($panelName+\\\"HyperGraphEd\\\");\\n hyperGraph -e \\n -graphLayoutStyle \\\"hierarchicalLayout\\\" \\n -orientation \\\"horiz\\\" \\n -mergeConnections 0\\n -zoom 1\\n -animateTransition 0\\n -showRelationships 1\\n -showShapes 0\\n -showDeformers 0\\n -showExpressions 0\\n -showConstraints 0\\n -showConnectionFromSelected 0\\n -showConnectionToSelected 0\\n -showConstraintLabels 0\\n -showUnderworld 0\\n -showInvisible 0\\n -transitionFrames 1\\n -opaqueContainers 0\\n -freeform 0\\n -imagePosition 0 0 \\n -imageScale 1\\n -imageEnabled 0\\n -graphType \\\"DAG\\\" \\n\"\n\t\t+ \" -heatMapDisplay 0\\n -updateSelection 1\\n -updateNodeAdded 1\\n -useDrawOverrideColor 0\\n -limitGraphTraversal -1\\n -range 0 0 \\n -iconSize \\\"smallIcons\\\" \\n -showCachedConnections 0\\n $editorName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"hyperShadePanel\\\" (localizedPanelLabel(\\\"Hypershade\\\")) `;\\n\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Hypershade\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"visorPanel\\\" (localizedPanelLabel(\\\"Visor\\\")) `;\\n\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Visor\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\"\n\t\t+ \"\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"nodeEditorPanel\\\" (localizedPanelLabel(\\\"Node Editor\\\")) `;\\n\\tif ($nodeEditorPanelVisible || $nodeEditorWorkspaceControlOpen) {\\n\\t\\tif (\\\"\\\" == $panelName) {\\n\\t\\t\\tif ($useSceneConfig) {\\n\\t\\t\\t\\t$panelName = `scriptedPanel -unParent -type \\\"nodeEditorPanel\\\" -l (localizedPanelLabel(\\\"Node Editor\\\")) -mbv $menusOkayInPanels `;\\n\\n\\t\\t\\t$editorName = ($panelName+\\\"NodeEditorEd\\\");\\n nodeEditor -e \\n -allAttributes 0\\n -allNodes 0\\n -autoSizeNodes 1\\n -consistentNameSize 1\\n -createNodeCommand \\\"nodeEdCreateNodeCommand\\\" \\n -connectNodeOnCreation 0\\n -connectOnDrop 0\\n -copyConnectionsOnPaste 0\\n -connectionStyle \\\"bezier\\\" \\n -defaultPinnedState 0\\n -additiveGraphingMode 0\\n -settingsChangedCallback \\\"nodeEdSyncControls\\\" \\n -traversalDepthLimit -1\\n -keyPressCommand \\\"nodeEdKeyPressCommand\\\" \\n\"\n\t\t+ \" -nodeTitleMode \\\"name\\\" \\n -gridSnap 0\\n -gridVisibility 1\\n -crosshairOnEdgeDragging 0\\n -popupMenuScript \\\"nodeEdBuildPanelMenus\\\" \\n -showNamespace 1\\n -showShapes 1\\n -showSGShapes 0\\n -showTransforms 1\\n -useAssets 1\\n -syncedSelection 1\\n -extendToShapes 1\\n -editorMode \\\"default\\\" \\n -hasWatchpoint 0\\n $editorName;\\n\\t\\t\\t}\\n\\t\\t} else {\\n\\t\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Node Editor\\\")) -mbv $menusOkayInPanels $panelName;\\n\\n\\t\\t\\t$editorName = ($panelName+\\\"NodeEditorEd\\\");\\n nodeEditor -e \\n -allAttributes 0\\n -allNodes 0\\n -autoSizeNodes 1\\n -consistentNameSize 1\\n -createNodeCommand \\\"nodeEdCreateNodeCommand\\\" \\n -connectNodeOnCreation 0\\n -connectOnDrop 0\\n\"\n\t\t+ \" -copyConnectionsOnPaste 0\\n -connectionStyle \\\"bezier\\\" \\n -defaultPinnedState 0\\n -additiveGraphingMode 0\\n -settingsChangedCallback \\\"nodeEdSyncControls\\\" \\n -traversalDepthLimit -1\\n -keyPressCommand \\\"nodeEdKeyPressCommand\\\" \\n -nodeTitleMode \\\"name\\\" \\n -gridSnap 0\\n -gridVisibility 1\\n -crosshairOnEdgeDragging 0\\n -popupMenuScript \\\"nodeEdBuildPanelMenus\\\" \\n -showNamespace 1\\n -showShapes 1\\n -showSGShapes 0\\n -showTransforms 1\\n -useAssets 1\\n -syncedSelection 1\\n -extendToShapes 1\\n -editorMode \\\"default\\\" \\n -hasWatchpoint 0\\n $editorName;\\n\\t\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"createNodePanel\\\" (localizedPanelLabel(\\\"Create Node\\\")) `;\\n\"\n\t\t+ \"\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Create Node\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"polyTexturePlacementPanel\\\" (localizedPanelLabel(\\\"UV Editor\\\")) `;\\n\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"UV Editor\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"renderWindowPanel\\\" (localizedPanelLabel(\\\"Render View\\\")) `;\\n\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Render View\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextPanel \\\"shapePanel\\\" (localizedPanelLabel(\\\"Shape Editor\\\")) `;\\n\"\n\t\t+ \"\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tshapePanel -edit -l (localizedPanelLabel(\\\"Shape Editor\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextPanel \\\"posePanel\\\" (localizedPanelLabel(\\\"Pose Editor\\\")) `;\\n\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tposePanel -edit -l (localizedPanelLabel(\\\"Pose Editor\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"dynRelEdPanel\\\" (localizedPanelLabel(\\\"Dynamic Relationships\\\")) `;\\n\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Dynamic Relationships\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"relationshipPanel\\\" (localizedPanelLabel(\\\"Relationship Editor\\\")) `;\\n\"\n\t\t+ \"\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Relationship Editor\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"referenceEditorPanel\\\" (localizedPanelLabel(\\\"Reference Editor\\\")) `;\\n\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Reference Editor\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"componentEditorPanel\\\" (localizedPanelLabel(\\\"Component Editor\\\")) `;\\n\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Component Editor\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"dynPaintScriptedPanelType\\\" (localizedPanelLabel(\\\"Paint Effects\\\")) `;\\n\"\n\t\t+ \"\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Paint Effects\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"scriptEditorPanel\\\" (localizedPanelLabel(\\\"Script Editor\\\")) `;\\n\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Script Editor\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"profilerPanel\\\" (localizedPanelLabel(\\\"Profiler Tool\\\")) `;\\n\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Profiler Tool\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"contentBrowserPanel\\\" (localizedPanelLabel(\\\"Content Browser\\\")) `;\\n\"\n\t\t+ \"\\tif (\\\"\\\" != $panelName) {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Content Browser\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\tif ($useSceneConfig) {\\n string $configName = `getPanel -cwl (localizedPanelLabel(\\\"Current Layout\\\"))`;\\n if (\\\"\\\" != $configName) {\\n\\t\\t\\tpanelConfiguration -edit -label (localizedPanelLabel(\\\"Current Layout\\\")) \\n\\t\\t\\t\\t-userCreated false\\n\\t\\t\\t\\t-defaultImage \\\"vacantCell.xP:\/\\\"\\n\\t\\t\\t\\t-image \\\"\\\"\\n\\t\\t\\t\\t-sc false\\n\\t\\t\\t\\t-configString \\\"global string $gMainPane; paneLayout -e -cn \\\\\\\"single\\\\\\\" -ps 1 100 100 $gMainPane;\\\"\\n\\t\\t\\t\\t-removeAllPanels\\n\\t\\t\\t\\t-ap false\\n\\t\\t\\t\\t\\t(localizedPanelLabel(\\\"Persp View\\\")) \\n\\t\\t\\t\\t\\t\\\"modelPanel\\\"\\n\"\n\t\t+ \"\\t\\t\\t\\t\\t\\\"$panelName = `modelPanel -unParent -l (localizedPanelLabel(\\\\\\\"Persp View\\\\\\\")) -mbv $menusOkayInPanels `;\\\\n$editorName = $panelName;\\\\nmodelEditor -e \\\\n -cam `findStartUpCamera persp` \\\\n -useInteractiveMode 0\\\\n -displayLights \\\\\\\"default\\\\\\\" \\\\n -displayAppearance \\\\\\\"smoothShaded\\\\\\\" \\\\n -activeOnly 0\\\\n -ignorePanZoom 0\\\\n -wireframeOnShaded 0\\\\n -headsUpDisplay 1\\\\n -holdOuts 1\\\\n -selectionHiliteDisplay 1\\\\n -useDefaultMaterial 0\\\\n -bufferMode \\\\\\\"double\\\\\\\" \\\\n -twoSidedLighting 0\\\\n -backfaceCulling 0\\\\n -xray 0\\\\n -jointXray 0\\\\n -activeComponentsXray 0\\\\n -displayTextures 1\\\\n -smoothWireframe 0\\\\n -lineWidth 1\\\\n -textureAnisotropic 0\\\\n -textureHilight 1\\\\n -textureSampling 2\\\\n -textureDisplay \\\\\\\"modulate\\\\\\\" \\\\n -textureMaxSize 16384\\\\n -fogging 0\\\\n -fogSource \\\\\\\"fragment\\\\\\\" \\\\n -fogMode \\\\\\\"linear\\\\\\\" \\\\n -fogStart 0\\\\n -fogEnd 100\\\\n -fogDensity 0.1\\\\n -fogColor 0.5 0.5 0.5 1 \\\\n -depthOfFieldPreview 1\\\\n -maxConstantTransparency 1\\\\n -rendererName \\\\\\\"vp2Renderer\\\\\\\" \\\\n -objectFilterShowInHUD 1\\\\n -isFiltered 0\\\\n -colorResolution 256 256 \\\\n -bumpResolution 512 512 \\\\n -textureCompression 0\\\\n -transparencyAlgorithm \\\\\\\"frontAndBackCull\\\\\\\" \\\\n -transpInShadows 0\\\\n -cullingOverride \\\\\\\"none\\\\\\\" \\\\n -lowQualityLighting 0\\\\n -maximumNumHardwareLights 1\\\\n -occlusionCulling 0\\\\n -shadingModel 0\\\\n -useBaseRenderer 0\\\\n -useReducedRenderer 0\\\\n -smallObjectCulling 0\\\\n -smallObjectThreshold -1 \\\\n -interactiveDisableShadows 0\\\\n -interactiveBackFaceCull 0\\\\n -sortTransparent 1\\\\n -controllers 1\\\\n -nurbsCurves 1\\\\n -nurbsSurfaces 1\\\\n -polymeshes 1\\\\n -subdivSurfaces 1\\\\n -planes 1\\\\n -lights 1\\\\n -cameras 1\\\\n -controlVertices 1\\\\n -hulls 1\\\\n -grid 1\\\\n -imagePlane 1\\\\n -joints 1\\\\n -ikHandles 1\\\\n -deformers 1\\\\n -dynamics 1\\\\n -particleInstancers 1\\\\n -fluids 1\\\\n -hairSystems 1\\\\n -follicles 1\\\\n -nCloths 1\\\\n -nParticles 1\\\\n -nRigids 1\\\\n -dynamicConstraints 1\\\\n -locators 1\\\\n -manipulators 1\\\\n -pluginShapes 1\\\\n -dimensions 1\\\\n -handles 1\\\\n -pivots 1\\\\n -textures 1\\\\n -strokes 1\\\\n -motionTrails 1\\\\n -clipGhosts 1\\\\n -greasePencils 1\\\\n -shadows 0\\\\n -captureSequenceNumber -1\\\\n -width 1759\\\\n -height 1092\\\\n -sceneRenderFilter 0\\\\n $editorName;\\\\nmodelEditor -e -viewSelected 0 $editorName;\\\\nmodelEditor -e \\\\n -pluginObjects \\\\\\\"gpuCacheDisplayFilter\\\\\\\" 1 \\\\n $editorName\\\"\\n\"\n\t\t+ \"\\t\\t\\t\\t\\t\\\"modelPanel -edit -l (localizedPanelLabel(\\\\\\\"Persp View\\\\\\\")) -mbv $menusOkayInPanels $panelName;\\\\n$editorName = $panelName;\\\\nmodelEditor -e \\\\n -cam `findStartUpCamera persp` \\\\n -useInteractiveMode 0\\\\n -displayLights \\\\\\\"default\\\\\\\" \\\\n -displayAppearance \\\\\\\"smoothShaded\\\\\\\" \\\\n -activeOnly 0\\\\n -ignorePanZoom 0\\\\n -wireframeOnShaded 0\\\\n -headsUpDisplay 1\\\\n -holdOuts 1\\\\n -selectionHiliteDisplay 1\\\\n -useDefaultMaterial 0\\\\n -bufferMode \\\\\\\"double\\\\\\\" \\\\n -twoSidedLighting 0\\\\n -backfaceCulling 0\\\\n -xray 0\\\\n -jointXray 0\\\\n -activeComponentsXray 0\\\\n -displayTextures 1\\\\n -smoothWireframe 0\\\\n -lineWidth 1\\\\n -textureAnisotropic 0\\\\n -textureHilight 1\\\\n -textureSampling 2\\\\n -textureDisplay \\\\\\\"modulate\\\\\\\" \\\\n -textureMaxSize 16384\\\\n -fogging 0\\\\n -fogSource \\\\\\\"fragment\\\\\\\" \\\\n -fogMode \\\\\\\"linear\\\\\\\" \\\\n -fogStart 0\\\\n -fogEnd 100\\\\n -fogDensity 0.1\\\\n -fogColor 0.5 0.5 0.5 1 \\\\n -depthOfFieldPreview 1\\\\n -maxConstantTransparency 1\\\\n -rendererName \\\\\\\"vp2Renderer\\\\\\\" \\\\n -objectFilterShowInHUD 1\\\\n -isFiltered 0\\\\n -colorResolution 256 256 \\\\n -bumpResolution 512 512 \\\\n -textureCompression 0\\\\n -transparencyAlgorithm \\\\\\\"frontAndBackCull\\\\\\\" \\\\n -transpInShadows 0\\\\n -cullingOverride \\\\\\\"none\\\\\\\" \\\\n -lowQualityLighting 0\\\\n -maximumNumHardwareLights 1\\\\n -occlusionCulling 0\\\\n -shadingModel 0\\\\n -useBaseRenderer 0\\\\n -useReducedRenderer 0\\\\n -smallObjectCulling 0\\\\n -smallObjectThreshold -1 \\\\n -interactiveDisableShadows 0\\\\n -interactiveBackFaceCull 0\\\\n -sortTransparent 1\\\\n -controllers 1\\\\n -nurbsCurves 1\\\\n -nurbsSurfaces 1\\\\n -polymeshes 1\\\\n -subdivSurfaces 1\\\\n -planes 1\\\\n -lights 1\\\\n -cameras 1\\\\n -controlVertices 1\\\\n -hulls 1\\\\n -grid 1\\\\n -imagePlane 1\\\\n -joints 1\\\\n -ikHandles 1\\\\n -deformers 1\\\\n -dynamics 1\\\\n -particleInstancers 1\\\\n -fluids 1\\\\n -hairSystems 1\\\\n -follicles 1\\\\n -nCloths 1\\\\n -nParticles 1\\\\n -nRigids 1\\\\n -dynamicConstraints 1\\\\n -locators 1\\\\n -manipulators 1\\\\n -pluginShapes 1\\\\n -dimensions 1\\\\n -handles 1\\\\n -pivots 1\\\\n -textures 1\\\\n -strokes 1\\\\n -motionTrails 1\\\\n -clipGhosts 1\\\\n -greasePencils 1\\\\n -shadows 0\\\\n -captureSequenceNumber -1\\\\n -width 1759\\\\n -height 1092\\\\n -sceneRenderFilter 0\\\\n $editorName;\\\\nmodelEditor -e -viewSelected 0 $editorName;\\\\nmodelEditor -e \\\\n -pluginObjects \\\\\\\"gpuCacheDisplayFilter\\\\\\\" 1 \\\\n $editorName\\\"\\n\"\n\t\t+ \"\\t\\t\\t\\t$configName;\\n\\n setNamedPanelLayout (localizedPanelLabel(\\\"Current Layout\\\"));\\n }\\n\\n panelHistory -e -clear mainPanelHistory;\\n sceneUIReplacement -clear;\\n\\t}\\n\\n\\ngrid -spacing 5 -size 12 -divisions 5 -displayAxes yes -displayGridLines yes -displayDivisionLines yes -displayPerspectiveLabels no -displayOrthographicLabels no -displayAxesBold yes -perspectiveLabelPosition axis -orthographicLabelPosition edge;\\nviewManip -drawCompass 0 -compassAngle 0 -frontParameters \\\"\\\" -homeParameters \\\"\\\" -selectionLockParameters \\\"\\\";\\n}\\n\");\n\tsetAttr \".st\" 3;\ncreateNode script -n \"sceneConfigurationScriptNode\";\n\trename -uid \"FC969DC6-40A2-8803-E5BE-1C82B4BFB130\";\n\tsetAttr \".b\" -type \"string\" \"playbackOptions -min 1 -max 120 -ast 1 -aet 200 \";\n\tsetAttr \".st\" 6;\ncreateNode standardSurface -n \"standardSurface5\";\n\trename -uid \"1DFB2053-42EF-EBB9-6DDD-A689AAD6DD89\";\ncreateNode shadingEngine -n \"standardSurface5SG\";\n\trename -uid \"A0B8D7EE-4510-7629-1D04-158B66562364\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo4\";\n\trename -uid \"D05CC5E3-474D-A18A-E40A-B88E4229E317\";\ncreateNode file -n \"file4\";\n\trename -uid \"84DAF956-4A41-877C-8AED-669C23CBFDB2\";\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/RGBA.png\";\n\tsetAttr \".cs\" -type \"string\" \"sRGB\";\ncreateNode place2dTexture -n \"place2dTexture4\";\n\trename -uid \"D79F837E-4420-300F-B051-B5B8843E1B75\";\ncreateNode standardSurface -n \"standardSurface6\";\n\trename -uid \"89ABC625-46D2-B143-F1BD-25A1D106DC24\";\ncreateNode shadingEngine -n \"standardSurface6SG\";\n\trename -uid \"CEA112D2-4A87-8191-48ED-F2806F11674D\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo5\";\n\trename -uid \"C0FF05E9-453B-0B8A-1BA4-02B055C1FCAA\";\ncreateNode file -n \"file5\";\n\trename -uid \"DDF54699-4CB9-C295-30A4-E8A3329C3F37\";\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/RGB.png\";\n\tsetAttr \".cs\" -type \"string\" \"sRGB\";\ncreateNode place2dTexture -n \"place2dTexture5\";\n\trename -uid \"D1050468-4376-EEE7-6155-A78964F02BF2\";\ncreateNode standardSurface -n \"standardSurface7\";\n\trename -uid \"E959BE5F-40F6-05F5-586A-86BEDF101EE9\";\ncreateNode shadingEngine -n \"standardSurface7SG\";\n\trename -uid \"C8591C7E-4A51-2B6A-CAFE-13B207ECA11D\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo6\";\n\trename -uid \"18B76998-4DE6-E551-6CC2-C4844CDEE0FF\";\ncreateNode file -n \"file6\";\n\trename -uid \"83F1C82C-4A65-D94C-F4E4-F4BAB85DD878\";\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/MonoA.png\";\n\tsetAttr \".cs\" -type \"string\" \"sRGB\";\ncreateNode place2dTexture -n \"place2dTexture6\";\n\trename -uid \"F132D7BF-463B-437D-82C0-CAB8CFF2AE82\";\ncreateNode standardSurface -n \"standardSurface8\";\n\trename -uid \"166B2193-4728-8327-E6FC-F5911DBF28A6\";\ncreateNode shadingEngine -n \"standardSurface8SG\";\n\trename -uid \"28215A1A-4D30-BBA9-8D2D-77A4A939F06D\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo7\";\n\trename -uid \"6A075EB8-45E7-725D-152D-BA897F4AAF5E\";\ncreateNode file -n \"file7\";\n\trename -uid \"BC060BB3-45B2-9D0D-0E22-72ADEBE9C10B\";\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/Mono.png\";\n\tsetAttr \".cs\" -type \"string\" \"sRGB\";\ncreateNode place2dTexture -n \"place2dTexture7\";\n\trename -uid \"6BE3301F-43B0-E1F6-F295-9CAFD87CF8DC\";\ncreateNode standardSurface -n \"standardSurface9\";\n\trename -uid \"E8DA083C-4821-6F33-E64E-089A2C327D63\";\ncreateNode shadingEngine -n \"standardSurface9SG\";\n\trename -uid \"74D88063-4F58-663C-A9BC-59976B4D14F3\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo8\";\n\trename -uid \"C8FBE7B6-48D2-9F63-31CB-4BABD4536808\";\ncreateNode file -n \"file8\";\n\trename -uid \"AF6C2238-46FA-BC3F-31CD-3591C76C979D\";\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/RGBA.png\";\n\tsetAttr \".cs\" -type \"string\" \"Raw\";\ncreateNode place2dTexture -n \"place2dTexture8\";\n\trename -uid \"ED68F4BC-49D8-76A6-F6E0-78B813E4A7AB\";\ncreateNode standardSurface -n \"standardSurface10\";\n\trename -uid \"1E7FA635-4FC4-22E8-447B-F0BCC4E91DDB\";\ncreateNode shadingEngine -n \"standardSurface10SG\";\n\trename -uid \"41FD65FD-4086-434A-73F9-19BE8B310272\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo9\";\n\trename -uid \"20DF6353-4581-B0D7-3426-E9A25CACE775\";\ncreateNode file -n \"file9\";\n\trename -uid \"7AA01CB3-4B14-FD04-37B3-17853EE56409\";\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/RGBA.png\";\n\tsetAttr \".cs\" -type \"string\" \"Raw\";\ncreateNode place2dTexture -n \"place2dTexture9\";\n\trename -uid \"A8D5468C-41AA-F951-2974-C99D1BE7D9B0\";\ncreateNode standardSurface -n \"standardSurface11\";\n\trename -uid \"E97DA489-4D83-E416-EE07-5C98BAB768E8\";\ncreateNode shadingEngine -n \"standardSurface11SG\";\n\trename -uid \"3C59FDA4-4487-9AEB-3E3D-629ECA8204A5\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo10\";\n\trename -uid \"BDB86E2C-4C70-6EAB-C6FA-D48B64366C35\";\ncreateNode file -n \"file10\";\n\trename -uid \"C05FF9C4-4EDD-2F68-82A9-BFB9461BF916\";\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/RGBA.png\";\n\tsetAttr \".cs\" -type \"string\" \"Raw\";\ncreateNode place2dTexture -n \"place2dTexture10\";\n\trename -uid \"F5603859-4505-0D54-EA09-C7989AE7DB49\";\ncreateNode standardSurface -n \"standardSurface12\";\n\trename -uid \"FC1B07E5-43EF-EFC7-ECA5-7298DE5A29EF\";\ncreateNode shadingEngine -n \"standardSurface12SG\";\n\trename -uid \"B087EFD7-45C3-DC47-4967-D2B6B3AC1B7D\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo11\";\n\trename -uid \"A7C97C73-4782-A4AB-6A04-19843FF775AA\";\ncreateNode file -n \"file11\";\n\trename -uid \"5AE878EC-4AA9-047E-40DB-5F85303A5F2C\";\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/RGBA.png\";\n\tsetAttr \".cs\" -type \"string\" \"Raw\";\ncreateNode place2dTexture -n \"place2dTexture11\";\n\trename -uid \"E4789D12-4785-7515-0B13-45BFB608474F\";\ncreateNode standardSurface -n \"standardSurface13\";\n\trename -uid \"25AC6D01-46F3-FD62-80B0-81904E946B11\";\ncreateNode shadingEngine -n \"standardSurface13SG\";\n\trename -uid \"59076A95-4BA4-5B07-2DC8-849DA1168700\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo12\";\n\trename -uid \"191612D1-4551-2566-52FA-F9AE31F1621F\";\ncreateNode file -n \"file12\";\n\trename -uid \"D6BEA98C-4155-4E8C-EA12-809412D83A9F\";\n\tsetAttr \".ail\" yes;\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/RGBA.png\";\n\tsetAttr \".cs\" -type \"string\" \"Raw\";\ncreateNode place2dTexture -n \"place2dTexture12\";\n\trename -uid \"8267406D-4A32-F308-63BF-3FB69EB64502\";\ncreateNode standardSurface -n \"standardSurface14\";\n\trename -uid \"601DD894-48BD-27D0-529E-CC8BAFB14CCF\";\n\tsetAttr \".bc\" -type \"float3\" 1 1 0 ;\n\tsetAttr \".ec\" -type \"float3\" 1 0 1 ;\ncreateNode shadingEngine -n \"standardSurface14SG\";\n\trename -uid \"EE00DF0D-49AD-A337-CC92-4BBA7ADF46E2\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo13\";\n\trename -uid \"797EBEFE-45D2-3ED1-3E94-67B52BCC71D8\";\ncreateNode file -n \"file13\";\n\trename -uid \"4F4F30FB-432B-BCFB-931F-319D6B71D155\";\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/RGB.png\";\n\tsetAttr \".cs\" -type \"string\" \"Raw\";\ncreateNode place2dTexture -n \"place2dTexture13\";\n\trename -uid \"684756BF-4B99-26A5-DC06-B481C54850B6\";\ncreateNode standardSurface -n \"standardSurface15\";\n\trename -uid \"42EDA0A1-4E24-D77A-3C86-D4890697030F\";\ncreateNode shadingEngine -n \"standardSurface15SG\";\n\trename -uid \"965668C2-42C1-059F-A82F-118A96B956BB\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo14\";\n\trename -uid \"12972C11-4BC5-F45F-D09A-06B5E9930137\";\ncreateNode file -n \"file14\";\n\trename -uid \"145A5D3A-439B-FB64-77AA-59A955821B89\";\n\tsetAttr \".ail\" yes;\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/normalSpiral.png\";\n\tsetAttr \".cs\" -type \"string\" \"Raw\";\ncreateNode place2dTexture -n \"place2dTexture14\";\n\trename -uid \"1DC4968C-4F75-5312-E949-088F94B28707\";\ncreateNode standardSurface -n \"standardSurface16\";\n\trename -uid \"961EEA23-4E7B-31E6-5D00-0490F2E68CF6\";\ncreateNode shadingEngine -n \"standardSurface16SG\";\n\trename -uid \"9B811961-4DBE-8A28-F949-DE9B7018ACA5\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo15\";\n\trename -uid \"C0707FEC-4BA4-7050-2D98-25977AF4BAAE\";\ncreateNode file -n \"file15\";\n\trename -uid \"5C3B0023-4DCB-CF18-A711-D89FB4839B44\";\n\tsetAttr \".ail\" yes;\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/normalSpiralA.png\";\n\tsetAttr \".cs\" -type \"string\" \"Raw\";\ncreateNode place2dTexture -n \"place2dTexture15\";\n\trename -uid \"3E7E71C7-45C7-AD16-0F00-34953D8387B7\";\ncreateNode standardSurface -n \"standardSurface17\";\n\trename -uid \"5E9C736E-484E-17DC-338B-F2AC67B7EB90\";\ncreateNode shadingEngine -n \"standardSurface17SG\";\n\trename -uid \"BAB8CBD8-4C12-C10E-5261-4186F9C0E2B8\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo16\";\n\trename -uid \"E3D6897F-446B-2F83-5F9C-6983C95C80E7\";\ncreateNode standardSurface -n \"standardSurface18\";\n\trename -uid \"0D207226-4659-96FC-E898-118CB1C33AB6\";\ncreateNode shadingEngine -n \"standardSurface18SG\";\n\trename -uid \"2FCD8CD1-425A-B33F-B9FD-80AC114B7A3A\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo17\";\n\trename -uid \"E1A6C441-40EC-48CD-3E6C-70924C887361\";\ncreateNode standardSurface -n \"standardSurface19\";\n\trename -uid \"39FA0977-41DD-6EF4-DEBF-96BAAC6D1F5E\";\ncreateNode shadingEngine -n \"standardSurface19SG\";\n\trename -uid \"1D17FFA7-4EA9-5337-A586-B7A05B5EE6CB\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo18\";\n\trename -uid \"D24B0DFD-495F-48E7-91E6-44ADEB2AC377\";\ncreateNode standardSurface -n \"standardSurface20\";\n\trename -uid \"AF90CC71-4581-6CF5-A5D0-1A8F83DE063F\";\ncreateNode shadingEngine -n \"standardSurface20SG\";\n\trename -uid \"0565AC94-49D8-EC6A-4FE5-B893E031C33B\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo19\";\n\trename -uid \"738924DF-4690-483E-83F9-BDB0C461F470\";\ncreateNode standardSurface -n \"standardSurface21\";\n\trename -uid \"F1A1ABB0-4F3E-5C4D-03A2-2EAF77921F31\";\ncreateNode shadingEngine -n \"standardSurface21SG\";\n\trename -uid \"2B105629-48DB-6AEA-A0B8-8294AA30FFAA\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo20\";\n\trename -uid \"97DC3160-4A6D-32D1-36F7-EAA31AF960CD\";\ncreateNode standardSurface -n \"standardSurface22\";\n\trename -uid \"1ECAE0BD-49D9-C366-B169-DDA4E7EC68DA\";\ncreateNode shadingEngine -n \"standardSurface22SG\";\n\trename -uid \"DBA392D6-44BB-FA0D-6702-9DBC6C305E3F\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo21\";\n\trename -uid \"F8802DD5-4659-8386-B814-D4B2108F0DFA\";\ncreateNode standardSurface -n \"standardSurface23\";\n\trename -uid \"1FD36256-451D-9396-F32A-118C39E65070\";\ncreateNode shadingEngine -n \"standardSurface23SG\";\n\trename -uid \"42D2653B-4BFD-43E7-111D-358B517598A0\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo22\";\n\trename -uid \"34EB0325-4D81-B20F-AD74-879C7DAB9BD1\";\ncreateNode standardSurface -n \"standardSurface24\";\n\trename -uid \"170465BD-4641-BDE7-DC6C-8F8CBA5EA96E\";\ncreateNode shadingEngine -n \"standardSurface24SG\";\n\trename -uid \"EC3347E6-4A15-3843-DF2F-B1900483AA6F\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo23\";\n\trename -uid \"A218ACA1-4796-6CD6-DDF6-63BF20ECD33B\";\ncreateNode standardSurface -n \"standardSurface25\";\n\trename -uid \"536403DA-4879-5DC2-20B4-F0B8AAEB6089\";\ncreateNode shadingEngine -n \"standardSurface25SG\";\n\trename -uid \"9B181935-4B82-C344-048E-61B6DA8AC98A\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo24\";\n\trename -uid \"4D8D1D32-40A0-CA6D-8C50-D88F789B9BA1\";\ncreateNode standardSurface -n \"standardSurface26\";\n\trename -uid \"8DDF8D04-4420-48F4-6EC4-A9A2C7E55F70\";\ncreateNode shadingEngine -n \"standardSurface26SG\";\n\trename -uid \"5D4A91F2-405D-614B-D09A-95B34F369D42\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo25\";\n\trename -uid \"5AB2B2D2-4980-81BE-3C17-C297B10F93B6\";\ncreateNode standardSurface -n \"standardSurface27\";\n\trename -uid \"C3BAE52C-4E71-8D19-360C-68A2A15CEB6E\";\ncreateNode shadingEngine -n \"standardSurface27SG\";\n\trename -uid \"B398C3F5-487A-60D1-AE76-1EB183BE7DD3\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo26\";\n\trename -uid \"1ED2C5B1-409B-9FFD-AD01-E2BF1E0FAB47\";\ncreateNode standardSurface -n \"standardSurface28\";\n\trename -uid \"1EE323B6-4D68-32EF-715F-6A84308DA38A\";\ncreateNode shadingEngine -n \"standardSurface28SG\";\n\trename -uid \"3B036492-4592-0877-3C46-0D8619887537\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo27\";\n\trename -uid \"7424D855-40A7-4219-E2BD-FD8B78D9B925\";\ncreateNode file -n \"file16\";\n\trename -uid \"CB8EC9E0-4B0A-C7A6-C2C7-57B7187A3168\";\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/Mono.png\";\n\tsetAttr \".cs\" -type \"string\" \"Raw\";\ncreateNode place2dTexture -n \"place2dTexture16\";\n\trename -uid \"AE04D72B-4D30-31C9-AD92-4D87E790A25D\";\ncreateNode file -n \"file17\";\n\trename -uid \"11F80F37-4885-FD73-A4E7-53A3BC31B6E9\";\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/Mono.png\";\n\tsetAttr \".cs\" -type \"string\" \"Raw\";\ncreateNode place2dTexture -n \"place2dTexture17\";\n\trename -uid \"CDF04A95-4D1F-99FE-1AD1-7B9577B5EE3C\";\ncreateNode file -n \"file18\";\n\trename -uid \"2F6840EE-42A0-45EC-7EA3-CD9A849C31AC\";\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/Mono.png\";\n\tsetAttr \".cs\" -type \"string\" \"Raw\";\ncreateNode place2dTexture -n \"place2dTexture18\";\n\trename -uid \"8F5FFC1B-403E-F897-958D-918CFC852446\";\ncreateNode file -n \"file19\";\n\trename -uid \"3896E06B-417B-83E9-3677-7CA4975685D3\";\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/Mono.png\";\n\tsetAttr \".cs\" -type \"string\" \"Raw\";\ncreateNode place2dTexture -n \"place2dTexture19\";\n\trename -uid \"3CE689B3-4CEE-0D2A-37A6-4FB97DC9DE43\";\ncreateNode file -n \"file20\";\n\trename -uid \"319184C8-459D-D4C7-E5C7-048644E73981\";\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/MonoA.png\";\n\tsetAttr \".cs\" -type \"string\" \"Raw\";\ncreateNode place2dTexture -n \"place2dTexture20\";\n\trename -uid \"C1E696CA-4168-A538-F9ED-4592BB81B202\";\ncreateNode file -n \"file21\";\n\trename -uid \"5F8DA435-446F-D3D6-9630-B59AC0C05440\";\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/MonoA.png\";\n\tsetAttr \".cs\" -type \"string\" \"Raw\";\ncreateNode place2dTexture -n \"place2dTexture21\";\n\trename -uid \"51D4B39F-4A2F-8F47-B9F2-AF984A5F963F\";\ncreateNode file -n \"file22\";\n\trename -uid \"9DE00A3B-41C2-7967-EFD0-DE961587D529\";\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/MonoA.png\";\n\tsetAttr \".cs\" -type \"string\" \"Raw\";\ncreateNode place2dTexture -n \"place2dTexture22\";\n\trename -uid \"CBFC1B0D-4120-8FC5-A803-EAA69EED7AD0\";\ncreateNode file -n \"file23\";\n\trename -uid \"05F08AF1-4B6E-66AB-2EB8-EE850E8FCB57\";\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/MonoA.png\";\n\tsetAttr \".cs\" -type \"string\" \"Raw\";\ncreateNode place2dTexture -n \"place2dTexture23\";\n\trename -uid \"A0E7C4AD-40F5-D1DE-1925-73A3B1BDECC8\";\ncreateNode file -n \"file24\";\n\trename -uid \"5A82C5BF-4559-C041-53F8-CB9B5192E780\";\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/RGB.png\";\n\tsetAttr \".cs\" -type \"string\" \"Raw\";\ncreateNode place2dTexture -n \"place2dTexture24\";\n\trename -uid \"5AD0BA20-43F4-4180-9638-F6AEA3178E88\";\ncreateNode file -n \"file25\";\n\trename -uid \"361087F1-4CB2-B999-0204-E8A59D92D1DD\";\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/RGB.png\";\n\tsetAttr \".cs\" -type \"string\" \"Raw\";\ncreateNode place2dTexture -n \"place2dTexture25\";\n\trename -uid \"8C70BA1B-4FFF-510C-8F2E-C791B333C470\";\ncreateNode file -n \"file26\";\n\trename -uid \"1DAFDF71-402E-E218-3F90-8BB674B00A5E\";\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/RGB.png\";\n\tsetAttr \".cs\" -type \"string\" \"Raw\";\ncreateNode place2dTexture -n \"place2dTexture26\";\n\trename -uid \"31516F6A-426A-DF0A-BC83-5AA70E18373C\";\ncreateNode file -n \"file27\";\n\trename -uid \"FD240793-4B9D-497B-0436-14B6E0A104F2\";\n\tsetAttr \".ftn\" -type \"string\" \"..\/textures\/RGB.png\";\n\tsetAttr \".cs\" -type \"string\" \"Raw\";\ncreateNode place2dTexture -n \"place2dTexture27\";\n\trename -uid \"F51A155F-4622-EE5C-6CB7-4983133F7049\";\nselect -ne :time1;\n\tsetAttr \".o\" 1;\n\tsetAttr \".unw\" 1;\nselect -ne :hardwareRenderingGlobals;\n\tsetAttr \".otfna\" -type \"stringArray\" 22 \"NURBS Curves\" \"NURBS Surfaces\" \"Polygons\" \"Subdiv Surface\" \"Particles\" \"Particle Instance\" \"Fluids\" \"Strokes\" \"Image Planes\" \"UI\" \"Lights\" \"Cameras\" \"Locators\" \"Joints\" \"IK Handles\" \"Deformers\" \"Motion Trails\" \"Components\" \"Hair Systems\" \"Follicles\" \"Misc. UI\" \"Ornaments\" ;\n\tsetAttr \".otfva\" -type \"Int32Array\" 22 0 1 1 1 1 1\n\t\t 1 1 1 0 0 0 0 0 0 0 0 0\n\t\t 0 0 0 0 ;\n\tsetAttr \".fprt\" yes;\nselect -ne :renderPartition;\n\tsetAttr -s 29 \".st\";\nselect -ne :renderGlobalsList1;\nselect -ne :defaultShaderList1;\n\tsetAttr -s 32 \".s\";\nselect -ne :postProcessList1;\n\tsetAttr -s 2 \".p\";\nselect -ne :defaultRenderUtilityList1;\n\tsetAttr -s 27 \".u\";\nselect -ne :defaultRenderingList1;\nselect -ne :defaultTextureList1;\n\tsetAttr -s 27 \".tx\";\nselect -ne :initialShadingGroup;\n\tsetAttr \".ro\" yes;\nselect -ne :initialParticleSE;\n\tsetAttr \".ro\" yes;\nselect -ne :defaultRenderGlobals;\n\taddAttr -ci true -h true -sn \"dss\" -ln \"defaultSurfaceShader\" -dt \"string\";\n\tsetAttr \".dss\" -type \"string\" \"lambert1\";\nselect -ne :defaultResolution;\n\tsetAttr \".pa\" 1;\nselect -ne :defaultColorMgtGlobals;\n\tsetAttr \".cfe\" yes;\n\tsetAttr \".cfp\" -type \"string\" \"\/OCIO-configs\/Maya2022-default\/config.ocio\";\n\tsetAttr \".vtn\" -type \"string\" \"ACES 1.0 SDR-video (sRGB)\";\n\tsetAttr \".vn\" -type \"string\" \"ACES 1.0 SDR-video\";\n\tsetAttr \".dn\" -type \"string\" \"sRGB\";\n\tsetAttr \".wsn\" -type \"string\" \"ACEScg\";\n\tsetAttr \".otn\" -type \"string\" \"ACES 1.0 SDR-video (sRGB)\";\n\tsetAttr \".potn\" -type \"string\" \"ACES 1.0 SDR-video (sRGB)\";\nselect -ne :hardwareRenderGlobals;\n\tsetAttr \".ctrs\" 256;\n\tsetAttr \".btrs\" 512;\nconnectAttr \"polyTweakUV1.out\" \"pPlaneShape1.i\";\nconnectAttr \"polyTweakUV1.uvtk[0]\" \"pPlaneShape1.uvst[0].uvtw\";\nrelationship \"link\" \":lightLinker1\" \":initialShadingGroup.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \":initialParticleSE.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface2SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface3SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface4SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface5SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface6SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface7SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface8SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface9SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface10SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface11SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface12SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface13SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface14SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface15SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface16SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface17SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface18SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface19SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface20SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface21SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface22SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface23SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface24SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface25SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface26SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface27SG.message\" \":defaultLightSet.message\";\nrelationship \"link\" \":lightLinker1\" \"standardSurface28SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \":initialShadingGroup.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \":initialParticleSE.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface2SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface3SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface4SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface5SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface6SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface7SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface8SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface9SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface10SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface11SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface12SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface13SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface14SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface15SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface16SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface17SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface18SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface19SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface20SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface21SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface22SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface23SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface24SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface25SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface26SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface27SG.message\" \":defaultLightSet.message\";\nrelationship \"shadowLink\" \":lightLinker1\" \"standardSurface28SG.message\" \":defaultLightSet.message\";\nconnectAttr \"layerManager.dli[0]\" \"defaultLayer.id\";\nconnectAttr \"renderLayerManager.rlmi[0]\" \"defaultRenderLayer.rlid\";\nconnectAttr \"file1.oc\" \"standardSurface2.bc\";\nconnectAttr \"standardSurface2.oc\" \"standardSurface2SG.ss\";\nconnectAttr \"pPlaneShape1.iog\" \"standardSurface2SG.dsm\" -na;\nconnectAttr \"standardSurface2SG.msg\" \"materialInfo1.sg\";\nconnectAttr \"standardSurface2.msg\" \"materialInfo1.m\";\nconnectAttr \"file1.msg\" \"materialInfo1.t\" -na;\nconnectAttr \":defaultColorMgtGlobals.cme\" \"file1.cme\";\nconnectAttr \":defaultColorMgtGlobals.cfe\" \"file1.cmcf\";\nconnectAttr \":defaultColorMgtGlobals.cfp\" \"file1.cmcp\";\nconnectAttr \":defaultColorMgtGlobals.wsn\" \"file1.ws\";\nconnectAttr \"place2dTexture1.c\" \"file1.c\";\nconnectAttr \"place2dTexture1.tf\" \"file1.tf\";\nconnectAttr \"place2dTexture1.rf\" \"file1.rf\";\nconnectAttr \"place2dTexture1.mu\" \"file1.mu\";\nconnectAttr \"place2dTexture1.mv\" \"file1.mv\";\nconnectAttr \"place2dTexture1.s\" \"file1.s\";\nconnectAttr \"place2dTexture1.wu\" \"file1.wu\";\nconnectAttr \"place2dTexture1.wv\" \"file1.wv\";\nconnectAttr \"place2dTexture1.re\" \"file1.re\";\nconnectAttr \"place2dTexture1.of\" \"file1.of\";\nconnectAttr \"place2dTexture1.r\" \"file1.ro\";\nconnectAttr \"place2dTexture1.n\" \"file1.n\";\nconnectAttr \"place2dTexture1.vt1\" \"file1.vt1\";\nconnectAttr \"place2dTexture1.vt2\" \"file1.vt2\";\nconnectAttr \"place2dTexture1.vt3\" \"file1.vt3\";\nconnectAttr \"place2dTexture1.vc1\" \"file1.vc1\";\nconnectAttr \"place2dTexture1.o\" \"file1.uv\";\nconnectAttr \"place2dTexture1.ofs\" \"file1.fs\";\nconnectAttr \"polyPlane1.out\" \"polyTweakUV1.ip\";\nconnectAttr \"file2.oc\" \"standardSurface3.bc\";\nconnectAttr \"standardSurface3.oc\" \"standardSurface3SG.ss\";\nconnectAttr \"pPlaneShape2.iog\" \"standardSurface3SG.dsm\" -na;\nconnectAttr \"standardSurface3SG.msg\" \"materialInfo2.sg\";\nconnectAttr \"standardSurface3.msg\" \"materialInfo2.m\";\nconnectAttr \"standardSurface3.msg\" \"materialInfo2.t\" -na;\nconnectAttr \":defaultColorMgtGlobals.cme\" \"file2.cme\";\nconnectAttr \":defaultColorMgtGlobals.cfe\" \"file2.cmcf\";\nconnectAttr \":defaultColorMgtGlobals.cfp\" \"file2.cmcp\";\nconnectAttr \":defaultColorMgtGlobals.wsn\" \"file2.ws\";\nconnectAttr \"place2dTexture2.c\" \"file2.c\";\nconnectAttr \"place2dTexture2.tf\" \"file2.tf\";\nconnectAttr \"place2dTexture2.rf\" \"file2.rf\";\nconnectAttr \"place2dTexture2.mu\" \"file2.mu\";\nconnectAttr \"place2dTexture2.mv\" \"file2.mv\";\nconnectAttr \"place2dTexture2.s\" \"file2.s\";\nconnectAttr \"place2dTexture2.wu\" \"file2.wu\";\nconnectAttr \"place2dTexture2.wv\" \"file2.wv\";\nconnectAttr \"place2dTexture2.re\" \"file2.re\";\nconnectAttr \"place2dTexture2.of\" \"file2.of\";\nconnectAttr \"place2dTexture2.r\" \"file2.ro\";\nconnectAttr \"place2dTexture2.n\" \"file2.n\";\nconnectAttr \"place2dTexture2.vt1\" \"file2.vt1\";\nconnectAttr \"place2dTexture2.vt2\" \"file2.vt2\";\nconnectAttr \"place2dTexture2.vt3\" \"file2.vt3\";\nconnectAttr \"place2dTexture2.vc1\" \"file2.vc1\";\nconnectAttr \"place2dTexture2.o\" \"file2.uv\";\nconnectAttr 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Cos[x]^6 + 24 (I Sin[x])^6 Cos[x]^10 + 20 (I Sin[x])^5 Cos[x]^11 + 20 (I Sin[x])^11 Cos[x]^5 + 11 (I Sin[x])^4 Cos[x]^12 + 11 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3) + Exp[-9 I y] (122 (I Sin[x])^10 Cos[x]^6 + 122 (I Sin[x])^6 Cos[x]^10 + 168 (I Sin[x])^8 Cos[x]^8 + 155 (I Sin[x])^7 Cos[x]^9 + 155 (I Sin[x])^9 Cos[x]^7 + 65 (I Sin[x])^5 Cos[x]^11 + 65 (I Sin[x])^11 Cos[x]^5 + 25 (I Sin[x])^4 Cos[x]^12 + 25 (I Sin[x])^12 Cos[x]^4 + 4 (I Sin[x])^3 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^3) + Exp[-7 I y] (351 (I Sin[x])^6 Cos[x]^10 + 351 (I Sin[x])^10 Cos[x]^6 + 484 (I Sin[x])^8 Cos[x]^8 + 431 (I Sin[x])^9 Cos[x]^7 + 431 (I Sin[x])^7 Cos[x]^9 + 204 (I Sin[x])^11 Cos[x]^5 + 204 (I Sin[x])^5 Cos[x]^11 + 93 (I Sin[x])^4 Cos[x]^12 + 93 (I Sin[x])^12 Cos[x]^4 + 37 (I Sin[x])^3 Cos[x]^13 + 37 (I Sin[x])^13 Cos[x]^3 + 7 (I Sin[x])^2 Cos[x]^14 + 7 (I Sin[x])^14 Cos[x]^2) + Exp[-5 I y] (371 (I Sin[x])^11 Cos[x]^5 + 371 (I Sin[x])^5 Cos[x]^11 + 1111 (I Sin[x])^7 Cos[x]^9 + 1111 (I Sin[x])^9 Cos[x]^7 + 1268 (I Sin[x])^8 Cos[x]^8 + 726 (I Sin[x])^10 Cos[x]^6 + 726 (I Sin[x])^6 Cos[x]^10 + 127 (I Sin[x])^12 Cos[x]^4 + 127 (I Sin[x])^4 Cos[x]^12 + 30 (I Sin[x])^3 Cos[x]^13 + 30 (I Sin[x])^13 Cos[x]^3 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2) + Exp[-3 I y] (1696 (I Sin[x])^7 Cos[x]^9 + 1696 (I Sin[x])^9 Cos[x]^7 + 720 (I Sin[x])^5 Cos[x]^11 + 720 (I Sin[x])^11 Cos[x]^5 + 1858 (I Sin[x])^8 Cos[x]^8 + 1200 (I Sin[x])^10 Cos[x]^6 + 1200 (I Sin[x])^6 Cos[x]^10 + 330 (I Sin[x])^4 Cos[x]^12 + 330 (I Sin[x])^12 Cos[x]^4 + 99 (I Sin[x])^3 Cos[x]^13 + 99 (I Sin[x])^13 Cos[x]^3 + 26 (I Sin[x])^2 Cos[x]^14 + 26 (I Sin[x])^14 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^15 + 5 (I Sin[x])^15 Cos[x]^1) + Exp[-1 I y] (1561 (I Sin[x])^10 Cos[x]^6 + 1561 (I Sin[x])^6 Cos[x]^10 + 2806 (I Sin[x])^8 Cos[x]^8 + 2411 (I Sin[x])^7 Cos[x]^9 + 2411 (I Sin[x])^9 Cos[x]^7 + 720 (I Sin[x])^11 Cos[x]^5 + 720 (I Sin[x])^5 Cos[x]^11 + 260 (I Sin[x])^4 Cos[x]^12 + 260 (I Sin[x])^12 Cos[x]^4 + 68 (I Sin[x])^3 Cos[x]^13 + 68 (I Sin[x])^13 Cos[x]^3 + 11 (I Sin[x])^2 Cos[x]^14 + 11 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[1 I y] (1593 (I Sin[x])^6 Cos[x]^10 + 1593 (I Sin[x])^10 Cos[x]^6 + 388 (I Sin[x])^4 Cos[x]^12 + 388 (I Sin[x])^12 Cos[x]^4 + 2436 (I Sin[x])^8 Cos[x]^8 + 2163 (I Sin[x])^7 Cos[x]^9 + 2163 (I Sin[x])^9 Cos[x]^7 + 884 (I Sin[x])^5 Cos[x]^11 + 884 (I Sin[x])^11 Cos[x]^5 + 148 (I Sin[x])^3 Cos[x]^13 + 148 (I Sin[x])^13 Cos[x]^3 + 35 (I Sin[x])^2 Cos[x]^14 + 35 (I Sin[x])^14 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^15 + 5 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[3 I y] (1825 (I Sin[x])^9 Cos[x]^7 + 1825 (I Sin[x])^7 Cos[x]^9 + 638 (I Sin[x])^11 Cos[x]^5 + 638 (I Sin[x])^5 Cos[x]^11 + 1214 (I Sin[x])^6 Cos[x]^10 + 1214 (I Sin[x])^10 Cos[x]^6 + 2062 (I Sin[x])^8 Cos[x]^8 + 230 (I Sin[x])^4 Cos[x]^12 + 230 (I Sin[x])^12 Cos[x]^4 + 56 (I Sin[x])^3 Cos[x]^13 + 56 (I Sin[x])^13 Cos[x]^3 + 10 (I Sin[x])^2 Cos[x]^14 + 10 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^15 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^15) + Exp[5 I y] (453 (I Sin[x])^5 Cos[x]^11 + 453 (I Sin[x])^11 Cos[x]^5 + 982 (I Sin[x])^7 Cos[x]^9 + 982 (I Sin[x])^9 Cos[x]^7 + 73 (I Sin[x])^3 Cos[x]^13 + 73 (I Sin[x])^13 Cos[x]^3 + 712 (I Sin[x])^6 Cos[x]^10 + 712 (I Sin[x])^10 Cos[x]^6 + 227 (I Sin[x])^4 Cos[x]^12 + 227 (I Sin[x])^12 Cos[x]^4 + 1064 (I Sin[x])^8 Cos[x]^8 + 20 (I Sin[x])^2 Cos[x]^14 + 20 (I Sin[x])^14 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[7 I y] (520 (I Sin[x])^8 Cos[x]^8 + 351 (I Sin[x])^6 Cos[x]^10 + 351 (I Sin[x])^10 Cos[x]^6 + 461 (I Sin[x])^7 Cos[x]^9 + 461 (I Sin[x])^9 Cos[x]^7 + 188 (I Sin[x])^11 Cos[x]^5 + 188 (I Sin[x])^5 Cos[x]^11 + 79 (I Sin[x])^12 Cos[x]^4 + 79 (I Sin[x])^4 Cos[x]^12 + 23 (I Sin[x])^3 Cos[x]^13 + 23 (I Sin[x])^13 Cos[x]^3 + 3 (I Sin[x])^14 Cos[x]^2 + 3 (I Sin[x])^2 Cos[x]^14) + Exp[9 I y] (122 (I Sin[x])^6 Cos[x]^10 + 122 (I Sin[x])^10 Cos[x]^6 + 39 (I Sin[x])^4 Cos[x]^12 + 39 (I Sin[x])^12 Cos[x]^4 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2 + 132 (I Sin[x])^8 Cos[x]^8 + 81 (I Sin[x])^5 Cos[x]^11 + 81 (I Sin[x])^11 Cos[x]^5 + 125 (I Sin[x])^9 Cos[x]^7 + 125 (I Sin[x])^7 Cos[x]^9 + 18 (I Sin[x])^3 Cos[x]^13 + 18 (I Sin[x])^13 Cos[x]^3) + Exp[11 I y] (37 (I Sin[x])^7 Cos[x]^9 + 37 (I Sin[x])^9 Cos[x]^7 + 18 (I Sin[x])^5 Cos[x]^11 + 18 (I Sin[x])^11 Cos[x]^5 + 32 (I Sin[x])^8 Cos[x]^8 + 26 (I Sin[x])^10 Cos[x]^6 + 26 (I Sin[x])^6 Cos[x]^10 + 7 (I Sin[x])^12 Cos[x]^4 + 7 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^13 Cos[x]^3 + 1 (I Sin[x])^3 Cos[x]^13) + Exp[13 I y] (3 (I Sin[x])^7 Cos[x]^9 + 3 (I Sin[x])^9 Cos[x]^7 + 4 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^5 + 1 (I Sin[x])^3 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^3 + 2 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^8 Cos[x]^8 + 4 (I Sin[x])^4 Cos[x]^12 + 4 (I Sin[x])^12 Cos[x]^4) + Exp[15 I y] (2 (I Sin[x])^8 Cos[x]^8));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":742.3333333333,"max_line_length":5344,"alphanum_fraction":0.5039964077} {"size":11301,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 16;\nname = \"16v2 1 4 1 1 5 1 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-15 I y] (2 (I Sin[x])^8 Cos[x]^8) + Exp[-13 I y] (4 (I Sin[x])^7 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^7 + 2 (I Sin[x])^8 Cos[x]^8 + 3 (I Sin[x])^6 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^5 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^5 + 3 (I Sin[x])^4 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3) + Exp[-11 I y] (34 (I Sin[x])^9 Cos[x]^7 + 34 (I Sin[x])^7 Cos[x]^9 + 28 (I Sin[x])^8 Cos[x]^8 + 24 (I Sin[x])^6 Cos[x]^10 + 24 (I Sin[x])^10 Cos[x]^6 + 20 (I Sin[x])^5 Cos[x]^11 + 20 (I Sin[x])^11 Cos[x]^5 + 11 (I Sin[x])^4 Cos[x]^12 + 11 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3) + Exp[-9 I y] (112 (I Sin[x])^6 Cos[x]^10 + 112 (I Sin[x])^10 Cos[x]^6 + 140 (I Sin[x])^8 Cos[x]^8 + 123 (I Sin[x])^7 Cos[x]^9 + 123 (I Sin[x])^9 Cos[x]^7 + 87 (I Sin[x])^5 Cos[x]^11 + 87 (I Sin[x])^11 Cos[x]^5 + 44 (I Sin[x])^4 Cos[x]^12 + 44 (I Sin[x])^12 Cos[x]^4 + 14 (I Sin[x])^3 Cos[x]^13 + 14 (I Sin[x])^13 Cos[x]^3 + 5 (I Sin[x])^2 Cos[x]^14 + 5 (I Sin[x])^14 Cos[x]^2) + Exp[-7 I y] (500 (I Sin[x])^8 Cos[x]^8 + 363 (I Sin[x])^10 Cos[x]^6 + 363 (I Sin[x])^6 Cos[x]^10 + 447 (I Sin[x])^7 Cos[x]^9 + 447 (I Sin[x])^9 Cos[x]^7 + 202 (I Sin[x])^11 Cos[x]^5 + 202 (I Sin[x])^5 Cos[x]^11 + 77 (I Sin[x])^12 Cos[x]^4 + 77 (I Sin[x])^4 Cos[x]^12 + 23 (I Sin[x])^13 Cos[x]^3 + 23 (I Sin[x])^3 Cos[x]^13 + 3 (I Sin[x])^2 Cos[x]^14 + 3 (I Sin[x])^14 Cos[x]^2) + Exp[-5 I y] (429 (I Sin[x])^5 Cos[x]^11 + 429 (I Sin[x])^11 Cos[x]^5 + 1001 (I Sin[x])^7 Cos[x]^9 + 1001 (I Sin[x])^9 Cos[x]^7 + 737 (I Sin[x])^6 Cos[x]^10 + 737 (I Sin[x])^10 Cos[x]^6 + 205 (I Sin[x])^4 Cos[x]^12 + 205 (I Sin[x])^12 Cos[x]^4 + 78 (I Sin[x])^3 Cos[x]^13 + 78 (I Sin[x])^13 Cos[x]^3 + 1066 (I Sin[x])^8 Cos[x]^8 + 16 (I Sin[x])^2 Cos[x]^14 + 16 (I Sin[x])^14 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[-3 I y] (1848 (I Sin[x])^7 Cos[x]^9 + 1848 (I Sin[x])^9 Cos[x]^7 + 616 (I Sin[x])^11 Cos[x]^5 + 616 (I Sin[x])^5 Cos[x]^11 + 1207 (I Sin[x])^6 Cos[x]^10 + 1207 (I Sin[x])^10 Cos[x]^6 + 232 (I Sin[x])^12 Cos[x]^4 + 232 (I Sin[x])^4 Cos[x]^12 + 2070 (I Sin[x])^8 Cos[x]^8 + 55 (I Sin[x])^13 Cos[x]^3 + 55 (I Sin[x])^3 Cos[x]^13 + 11 (I Sin[x])^14 Cos[x]^2 + 11 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[-1 I y] (414 (I Sin[x])^4 Cos[x]^12 + 414 (I Sin[x])^12 Cos[x]^4 + 1551 (I Sin[x])^6 Cos[x]^10 + 1551 (I Sin[x])^10 Cos[x]^6 + 2458 (I Sin[x])^8 Cos[x]^8 + 2149 (I Sin[x])^7 Cos[x]^9 + 2149 (I Sin[x])^9 Cos[x]^7 + 907 (I Sin[x])^5 Cos[x]^11 + 907 (I Sin[x])^11 Cos[x]^5 + 139 (I Sin[x])^3 Cos[x]^13 + 139 (I Sin[x])^13 Cos[x]^3 + 40 (I Sin[x])^2 Cos[x]^14 + 40 (I Sin[x])^14 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^15 + 5 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[1 I y] (2858 (I Sin[x])^8 Cos[x]^8 + 1547 (I Sin[x])^10 Cos[x]^6 + 1547 (I Sin[x])^6 Cos[x]^10 + 250 (I Sin[x])^12 Cos[x]^4 + 250 (I Sin[x])^4 Cos[x]^12 + 721 (I Sin[x])^5 Cos[x]^11 + 721 (I Sin[x])^11 Cos[x]^5 + 69 (I Sin[x])^13 Cos[x]^3 + 69 (I Sin[x])^3 Cos[x]^13 + 2409 (I Sin[x])^7 Cos[x]^9 + 2409 (I Sin[x])^9 Cos[x]^7 + 9 (I Sin[x])^2 Cos[x]^14 + 9 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^15 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^15) + Exp[3 I y] (113 (I Sin[x])^3 Cos[x]^13 + 113 (I Sin[x])^13 Cos[x]^3 + 725 (I Sin[x])^5 Cos[x]^11 + 725 (I Sin[x])^11 Cos[x]^5 + 1677 (I Sin[x])^7 Cos[x]^9 + 1677 (I Sin[x])^9 Cos[x]^7 + 1786 (I Sin[x])^8 Cos[x]^8 + 1245 (I Sin[x])^6 Cos[x]^10 + 1245 (I Sin[x])^10 Cos[x]^6 + 323 (I Sin[x])^4 Cos[x]^12 + 323 (I Sin[x])^12 Cos[x]^4 + 24 (I Sin[x])^2 Cos[x]^14 + 24 (I Sin[x])^14 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^15 + 5 (I Sin[x])^15 Cos[x]^1) + Exp[5 I y] (1116 (I Sin[x])^9 Cos[x]^7 + 1116 (I Sin[x])^7 Cos[x]^9 + 370 (I Sin[x])^11 Cos[x]^5 + 370 (I Sin[x])^5 Cos[x]^11 + 735 (I Sin[x])^6 Cos[x]^10 + 735 (I Sin[x])^10 Cos[x]^6 + 131 (I Sin[x])^12 Cos[x]^4 + 131 (I Sin[x])^4 Cos[x]^12 + 1240 (I Sin[x])^8 Cos[x]^8 + 26 (I Sin[x])^3 Cos[x]^13 + 26 (I Sin[x])^13 Cos[x]^3 + 5 (I Sin[x])^14 Cos[x]^2 + 5 (I Sin[x])^2 Cos[x]^14) + Exp[7 I y] (98 (I Sin[x])^4 Cos[x]^12 + 98 (I Sin[x])^12 Cos[x]^4 + 332 (I Sin[x])^6 Cos[x]^10 + 332 (I Sin[x])^10 Cos[x]^6 + 512 (I Sin[x])^8 Cos[x]^8 + 439 (I Sin[x])^9 Cos[x]^7 + 439 (I Sin[x])^7 Cos[x]^9 + 203 (I Sin[x])^5 Cos[x]^11 + 203 (I Sin[x])^11 Cos[x]^5 + 7 (I Sin[x])^2 Cos[x]^14 + 7 (I Sin[x])^14 Cos[x]^2 + 30 (I Sin[x])^3 Cos[x]^13 + 30 (I Sin[x])^13 Cos[x]^3) + Exp[9 I y] (126 (I Sin[x])^10 Cos[x]^6 + 126 (I Sin[x])^6 Cos[x]^10 + 160 (I Sin[x])^8 Cos[x]^8 + 147 (I Sin[x])^7 Cos[x]^9 + 147 (I Sin[x])^9 Cos[x]^7 + 70 (I Sin[x])^11 Cos[x]^5 + 70 (I Sin[x])^5 Cos[x]^11 + 25 (I Sin[x])^4 Cos[x]^12 + 25 (I Sin[x])^12 Cos[x]^4 + 7 (I Sin[x])^13 Cos[x]^3 + 7 (I Sin[x])^3 Cos[x]^13) + Exp[11 I y] (13 (I Sin[x])^5 Cos[x]^11 + 13 (I Sin[x])^11 Cos[x]^5 + 41 (I Sin[x])^7 Cos[x]^9 + 41 (I Sin[x])^9 Cos[x]^7 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3 + 42 (I Sin[x])^8 Cos[x]^8 + 23 (I Sin[x])^6 Cos[x]^10 + 23 (I Sin[x])^10 Cos[x]^6 + 5 (I Sin[x])^4 Cos[x]^12 + 5 (I Sin[x])^12 Cos[x]^4) + Exp[13 I y] (5 (I Sin[x])^9 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^9 + 3 (I Sin[x])^11 Cos[x]^5 + 3 (I Sin[x])^5 Cos[x]^11 + 6 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^4 Cos[x]^12) + Exp[15 I y] (1 (I Sin[x])^6 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^6))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-15 I y] (2 (I Sin[x])^8 Cos[x]^8) + Exp[-13 I y] (4 (I Sin[x])^7 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^7 + 2 (I Sin[x])^8 Cos[x]^8 + 3 (I Sin[x])^6 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^5 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^5 + 3 (I Sin[x])^4 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3) + Exp[-11 I y] (34 (I Sin[x])^9 Cos[x]^7 + 34 (I Sin[x])^7 Cos[x]^9 + 28 (I Sin[x])^8 Cos[x]^8 + 24 (I Sin[x])^6 Cos[x]^10 + 24 (I Sin[x])^10 Cos[x]^6 + 20 (I Sin[x])^5 Cos[x]^11 + 20 (I Sin[x])^11 Cos[x]^5 + 11 (I Sin[x])^4 Cos[x]^12 + 11 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3) + Exp[-9 I y] (112 (I Sin[x])^6 Cos[x]^10 + 112 (I Sin[x])^10 Cos[x]^6 + 140 (I Sin[x])^8 Cos[x]^8 + 123 (I Sin[x])^7 Cos[x]^9 + 123 (I Sin[x])^9 Cos[x]^7 + 87 (I Sin[x])^5 Cos[x]^11 + 87 (I Sin[x])^11 Cos[x]^5 + 44 (I Sin[x])^4 Cos[x]^12 + 44 (I Sin[x])^12 Cos[x]^4 + 14 (I Sin[x])^3 Cos[x]^13 + 14 (I Sin[x])^13 Cos[x]^3 + 5 (I Sin[x])^2 Cos[x]^14 + 5 (I Sin[x])^14 Cos[x]^2) + Exp[-7 I y] (500 (I Sin[x])^8 Cos[x]^8 + 363 (I Sin[x])^10 Cos[x]^6 + 363 (I Sin[x])^6 Cos[x]^10 + 447 (I Sin[x])^7 Cos[x]^9 + 447 (I Sin[x])^9 Cos[x]^7 + 202 (I Sin[x])^11 Cos[x]^5 + 202 (I Sin[x])^5 Cos[x]^11 + 77 (I Sin[x])^12 Cos[x]^4 + 77 (I Sin[x])^4 Cos[x]^12 + 23 (I Sin[x])^13 Cos[x]^3 + 23 (I Sin[x])^3 Cos[x]^13 + 3 (I Sin[x])^2 Cos[x]^14 + 3 (I Sin[x])^14 Cos[x]^2) + Exp[-5 I y] (429 (I Sin[x])^5 Cos[x]^11 + 429 (I Sin[x])^11 Cos[x]^5 + 1001 (I Sin[x])^7 Cos[x]^9 + 1001 (I Sin[x])^9 Cos[x]^7 + 737 (I Sin[x])^6 Cos[x]^10 + 737 (I Sin[x])^10 Cos[x]^6 + 205 (I Sin[x])^4 Cos[x]^12 + 205 (I Sin[x])^12 Cos[x]^4 + 78 (I Sin[x])^3 Cos[x]^13 + 78 (I Sin[x])^13 Cos[x]^3 + 1066 (I Sin[x])^8 Cos[x]^8 + 16 (I Sin[x])^2 Cos[x]^14 + 16 (I Sin[x])^14 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[-3 I y] (1848 (I Sin[x])^7 Cos[x]^9 + 1848 (I Sin[x])^9 Cos[x]^7 + 616 (I Sin[x])^11 Cos[x]^5 + 616 (I Sin[x])^5 Cos[x]^11 + 1207 (I Sin[x])^6 Cos[x]^10 + 1207 (I Sin[x])^10 Cos[x]^6 + 232 (I Sin[x])^12 Cos[x]^4 + 232 (I Sin[x])^4 Cos[x]^12 + 2070 (I Sin[x])^8 Cos[x]^8 + 55 (I Sin[x])^13 Cos[x]^3 + 55 (I Sin[x])^3 Cos[x]^13 + 11 (I Sin[x])^14 Cos[x]^2 + 11 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[-1 I y] (414 (I Sin[x])^4 Cos[x]^12 + 414 (I Sin[x])^12 Cos[x]^4 + 1551 (I Sin[x])^6 Cos[x]^10 + 1551 (I Sin[x])^10 Cos[x]^6 + 2458 (I Sin[x])^8 Cos[x]^8 + 2149 (I Sin[x])^7 Cos[x]^9 + 2149 (I Sin[x])^9 Cos[x]^7 + 907 (I Sin[x])^5 Cos[x]^11 + 907 (I Sin[x])^11 Cos[x]^5 + 139 (I Sin[x])^3 Cos[x]^13 + 139 (I Sin[x])^13 Cos[x]^3 + 40 (I Sin[x])^2 Cos[x]^14 + 40 (I Sin[x])^14 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^15 + 5 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[1 I y] (2858 (I Sin[x])^8 Cos[x]^8 + 1547 (I Sin[x])^10 Cos[x]^6 + 1547 (I Sin[x])^6 Cos[x]^10 + 250 (I Sin[x])^12 Cos[x]^4 + 250 (I Sin[x])^4 Cos[x]^12 + 721 (I Sin[x])^5 Cos[x]^11 + 721 (I Sin[x])^11 Cos[x]^5 + 69 (I Sin[x])^13 Cos[x]^3 + 69 (I Sin[x])^3 Cos[x]^13 + 2409 (I Sin[x])^7 Cos[x]^9 + 2409 (I Sin[x])^9 Cos[x]^7 + 9 (I Sin[x])^2 Cos[x]^14 + 9 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^15 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^15) + Exp[3 I y] (113 (I Sin[x])^3 Cos[x]^13 + 113 (I Sin[x])^13 Cos[x]^3 + 725 (I Sin[x])^5 Cos[x]^11 + 725 (I Sin[x])^11 Cos[x]^5 + 1677 (I Sin[x])^7 Cos[x]^9 + 1677 (I Sin[x])^9 Cos[x]^7 + 1786 (I Sin[x])^8 Cos[x]^8 + 1245 (I Sin[x])^6 Cos[x]^10 + 1245 (I Sin[x])^10 Cos[x]^6 + 323 (I Sin[x])^4 Cos[x]^12 + 323 (I Sin[x])^12 Cos[x]^4 + 24 (I Sin[x])^2 Cos[x]^14 + 24 (I Sin[x])^14 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^15 + 5 (I Sin[x])^15 Cos[x]^1) + Exp[5 I y] (1116 (I Sin[x])^9 Cos[x]^7 + 1116 (I Sin[x])^7 Cos[x]^9 + 370 (I Sin[x])^11 Cos[x]^5 + 370 (I Sin[x])^5 Cos[x]^11 + 735 (I Sin[x])^6 Cos[x]^10 + 735 (I Sin[x])^10 Cos[x]^6 + 131 (I Sin[x])^12 Cos[x]^4 + 131 (I Sin[x])^4 Cos[x]^12 + 1240 (I Sin[x])^8 Cos[x]^8 + 26 (I Sin[x])^3 Cos[x]^13 + 26 (I Sin[x])^13 Cos[x]^3 + 5 (I Sin[x])^14 Cos[x]^2 + 5 (I Sin[x])^2 Cos[x]^14) + Exp[7 I y] (98 (I Sin[x])^4 Cos[x]^12 + 98 (I Sin[x])^12 Cos[x]^4 + 332 (I Sin[x])^6 Cos[x]^10 + 332 (I Sin[x])^10 Cos[x]^6 + 512 (I Sin[x])^8 Cos[x]^8 + 439 (I Sin[x])^9 Cos[x]^7 + 439 (I Sin[x])^7 Cos[x]^9 + 203 (I Sin[x])^5 Cos[x]^11 + 203 (I Sin[x])^11 Cos[x]^5 + 7 (I Sin[x])^2 Cos[x]^14 + 7 (I Sin[x])^14 Cos[x]^2 + 30 (I Sin[x])^3 Cos[x]^13 + 30 (I Sin[x])^13 Cos[x]^3) + Exp[9 I y] (126 (I Sin[x])^10 Cos[x]^6 + 126 (I Sin[x])^6 Cos[x]^10 + 160 (I Sin[x])^8 Cos[x]^8 + 147 (I Sin[x])^7 Cos[x]^9 + 147 (I Sin[x])^9 Cos[x]^7 + 70 (I Sin[x])^11 Cos[x]^5 + 70 (I Sin[x])^5 Cos[x]^11 + 25 (I Sin[x])^4 Cos[x]^12 + 25 (I Sin[x])^12 Cos[x]^4 + 7 (I Sin[x])^13 Cos[x]^3 + 7 (I Sin[x])^3 Cos[x]^13) + Exp[11 I y] (13 (I Sin[x])^5 Cos[x]^11 + 13 (I Sin[x])^11 Cos[x]^5 + 41 (I Sin[x])^7 Cos[x]^9 + 41 (I Sin[x])^9 Cos[x]^7 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3 + 42 (I Sin[x])^8 Cos[x]^8 + 23 (I Sin[x])^6 Cos[x]^10 + 23 (I Sin[x])^10 Cos[x]^6 + 5 (I Sin[x])^4 Cos[x]^12 + 5 (I Sin[x])^12 Cos[x]^4) + Exp[13 I y] (5 (I Sin[x])^9 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^9 + 3 (I Sin[x])^11 Cos[x]^5 + 3 (I Sin[x])^5 Cos[x]^11 + 6 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^4 Cos[x]^12) + Exp[15 I y] (1 (I Sin[x])^6 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^6));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":753.4,"max_line_length":5428,"alphanum_fraction":0.5039377046} {"size":11251,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 16;\nname = \"16v3 2 5 1 1 1 1 1 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^5 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^5) + Exp[-13 I y] (6 (I Sin[x])^6 Cos[x]^10 + 6 (I Sin[x])^10 Cos[x]^6 + 3 (I Sin[x])^5 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^9 Cos[x]^7 + 4 (I Sin[x])^7 Cos[x]^9 + 4 (I Sin[x])^8 Cos[x]^8) + Exp[-11 I y] (10 (I Sin[x])^4 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^4 + 26 (I Sin[x])^6 Cos[x]^10 + 26 (I Sin[x])^10 Cos[x]^6 + 14 (I Sin[x])^5 Cos[x]^11 + 14 (I Sin[x])^11 Cos[x]^5 + 34 (I Sin[x])^7 Cos[x]^9 + 34 (I Sin[x])^9 Cos[x]^7 + 1 (I Sin[x])^3 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^3 + 40 (I Sin[x])^8 Cos[x]^8) + Exp[-9 I y] (170 (I Sin[x])^7 Cos[x]^9 + 170 (I Sin[x])^9 Cos[x]^7 + 58 (I Sin[x])^5 Cos[x]^11 + 58 (I Sin[x])^11 Cos[x]^5 + 21 (I Sin[x])^4 Cos[x]^12 + 21 (I Sin[x])^12 Cos[x]^4 + 116 (I Sin[x])^10 Cos[x]^6 + 116 (I Sin[x])^6 Cos[x]^10 + 174 (I Sin[x])^8 Cos[x]^8 + 3 (I Sin[x])^3 Cos[x]^13 + 3 (I Sin[x])^13 Cos[x]^3) + Exp[-7 I y] (38 (I Sin[x])^3 Cos[x]^13 + 38 (I Sin[x])^13 Cos[x]^3 + 211 (I Sin[x])^5 Cos[x]^11 + 211 (I Sin[x])^11 Cos[x]^5 + 444 (I Sin[x])^7 Cos[x]^9 + 444 (I Sin[x])^9 Cos[x]^7 + 338 (I Sin[x])^6 Cos[x]^10 + 338 (I Sin[x])^10 Cos[x]^6 + 90 (I Sin[x])^4 Cos[x]^12 + 90 (I Sin[x])^12 Cos[x]^4 + 476 (I Sin[x])^8 Cos[x]^8 + 6 (I Sin[x])^2 Cos[x]^14 + 6 (I Sin[x])^14 Cos[x]^2) + Exp[-5 I y] (1304 (I Sin[x])^8 Cos[x]^8 + 722 (I Sin[x])^10 Cos[x]^6 + 722 (I Sin[x])^6 Cos[x]^10 + 134 (I Sin[x])^4 Cos[x]^12 + 134 (I Sin[x])^12 Cos[x]^4 + 32 (I Sin[x])^3 Cos[x]^13 + 32 (I Sin[x])^13 Cos[x]^3 + 1088 (I Sin[x])^9 Cos[x]^7 + 1088 (I Sin[x])^7 Cos[x]^9 + 371 (I Sin[x])^5 Cos[x]^11 + 371 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2) + Exp[-3 I y] (29 (I Sin[x])^2 Cos[x]^14 + 29 (I Sin[x])^14 Cos[x]^2 + 1233 (I Sin[x])^6 Cos[x]^10 + 1233 (I Sin[x])^10 Cos[x]^6 + 339 (I Sin[x])^4 Cos[x]^12 + 339 (I Sin[x])^12 Cos[x]^4 + 1838 (I Sin[x])^8 Cos[x]^8 + 1663 (I Sin[x])^7 Cos[x]^9 + 1663 (I Sin[x])^9 Cos[x]^7 + 718 (I Sin[x])^5 Cos[x]^11 + 718 (I Sin[x])^11 Cos[x]^5 + 99 (I Sin[x])^3 Cos[x]^13 + 99 (I Sin[x])^13 Cos[x]^3 + 5 (I Sin[x])^1 Cos[x]^15 + 5 (I Sin[x])^15 Cos[x]^1) + Exp[-1 I y] (2421 (I Sin[x])^9 Cos[x]^7 + 2421 (I Sin[x])^7 Cos[x]^9 + 745 (I Sin[x])^5 Cos[x]^11 + 745 (I Sin[x])^11 Cos[x]^5 + 260 (I Sin[x])^4 Cos[x]^12 + 260 (I Sin[x])^12 Cos[x]^4 + 2696 (I Sin[x])^8 Cos[x]^8 + 1581 (I Sin[x])^6 Cos[x]^10 + 1581 (I Sin[x])^10 Cos[x]^6 + 68 (I Sin[x])^13 Cos[x]^3 + 68 (I Sin[x])^3 Cos[x]^13 + 11 (I Sin[x])^2 Cos[x]^14 + 11 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[1 I y] (152 (I Sin[x])^3 Cos[x]^13 + 152 (I Sin[x])^13 Cos[x]^3 + 2185 (I Sin[x])^7 Cos[x]^9 + 2185 (I Sin[x])^9 Cos[x]^7 + 893 (I Sin[x])^5 Cos[x]^11 + 893 (I Sin[x])^11 Cos[x]^5 + 2454 (I Sin[x])^8 Cos[x]^8 + 1552 (I Sin[x])^6 Cos[x]^10 + 1552 (I Sin[x])^10 Cos[x]^6 + 388 (I Sin[x])^4 Cos[x]^12 + 388 (I Sin[x])^12 Cos[x]^4 + 5 (I Sin[x])^1 Cos[x]^15 + 5 (I Sin[x])^15 Cos[x]^1 + 32 (I Sin[x])^2 Cos[x]^14 + 32 (I Sin[x])^14 Cos[x]^2 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[3 I y] (1208 (I Sin[x])^10 Cos[x]^6 + 1208 (I Sin[x])^6 Cos[x]^10 + 2148 (I Sin[x])^8 Cos[x]^8 + 617 (I Sin[x])^5 Cos[x]^11 + 617 (I Sin[x])^11 Cos[x]^5 + 1813 (I Sin[x])^7 Cos[x]^9 + 1813 (I Sin[x])^9 Cos[x]^7 + 228 (I Sin[x])^12 Cos[x]^4 + 228 (I Sin[x])^4 Cos[x]^12 + 54 (I Sin[x])^3 Cos[x]^13 + 54 (I Sin[x])^13 Cos[x]^3 + 10 (I Sin[x])^2 Cos[x]^14 + 10 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^15 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^15) + Exp[5 I y] (218 (I Sin[x])^4 Cos[x]^12 + 218 (I Sin[x])^12 Cos[x]^4 + 1072 (I Sin[x])^8 Cos[x]^8 + 737 (I Sin[x])^6 Cos[x]^10 + 737 (I Sin[x])^10 Cos[x]^6 + 984 (I Sin[x])^9 Cos[x]^7 + 984 (I Sin[x])^7 Cos[x]^9 + 437 (I Sin[x])^5 Cos[x]^11 + 437 (I Sin[x])^11 Cos[x]^5 + 21 (I Sin[x])^2 Cos[x]^14 + 21 (I Sin[x])^14 Cos[x]^2 + 66 (I Sin[x])^3 Cos[x]^13 + 66 (I Sin[x])^13 Cos[x]^3 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[7 I y] (185 (I Sin[x])^11 Cos[x]^5 + 185 (I Sin[x])^5 Cos[x]^11 + 484 (I Sin[x])^9 Cos[x]^7 + 484 (I Sin[x])^7 Cos[x]^9 + 75 (I Sin[x])^4 Cos[x]^12 + 75 (I Sin[x])^12 Cos[x]^4 + 337 (I Sin[x])^6 Cos[x]^10 + 337 (I Sin[x])^10 Cos[x]^6 + 514 (I Sin[x])^8 Cos[x]^8 + 24 (I Sin[x])^3 Cos[x]^13 + 24 (I Sin[x])^13 Cos[x]^3 + 3 (I Sin[x])^14 Cos[x]^2 + 3 (I Sin[x])^2 Cos[x]^14) + Exp[9 I y] (21 (I Sin[x])^3 Cos[x]^13 + 21 (I Sin[x])^13 Cos[x]^3 + 122 (I Sin[x])^9 Cos[x]^7 + 122 (I Sin[x])^7 Cos[x]^9 + 88 (I Sin[x])^5 Cos[x]^11 + 88 (I Sin[x])^11 Cos[x]^5 + 124 (I Sin[x])^8 Cos[x]^8 + 116 (I Sin[x])^6 Cos[x]^10 + 116 (I Sin[x])^10 Cos[x]^6 + 42 (I Sin[x])^4 Cos[x]^12 + 42 (I Sin[x])^12 Cos[x]^4 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2) + Exp[11 I y] (34 (I Sin[x])^10 Cos[x]^6 + 34 (I Sin[x])^6 Cos[x]^10 + 10 (I Sin[x])^12 Cos[x]^4 + 10 (I Sin[x])^4 Cos[x]^12 + 24 (I Sin[x])^8 Cos[x]^8 + 22 (I Sin[x])^5 Cos[x]^11 + 22 (I Sin[x])^11 Cos[x]^5 + 26 (I Sin[x])^7 Cos[x]^9 + 26 (I Sin[x])^9 Cos[x]^7 + 1 (I Sin[x])^13 Cos[x]^3 + 1 (I Sin[x])^3 Cos[x]^13) + Exp[13 I y] (5 (I Sin[x])^4 Cos[x]^12 + 5 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^9 Cos[x]^7 + 2 (I Sin[x])^7 Cos[x]^9 + 4 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^5 + 1 (I Sin[x])^3 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^3) + Exp[15 I y] (1 (I Sin[x])^11 Cos[x]^5 + 1 (I Sin[x])^5 Cos[x]^11))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^5 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^5) + Exp[-13 I y] (6 (I Sin[x])^6 Cos[x]^10 + 6 (I Sin[x])^10 Cos[x]^6 + 3 (I Sin[x])^5 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^9 Cos[x]^7 + 4 (I Sin[x])^7 Cos[x]^9 + 4 (I Sin[x])^8 Cos[x]^8) + Exp[-11 I y] (10 (I Sin[x])^4 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^4 + 26 (I Sin[x])^6 Cos[x]^10 + 26 (I Sin[x])^10 Cos[x]^6 + 14 (I Sin[x])^5 Cos[x]^11 + 14 (I Sin[x])^11 Cos[x]^5 + 34 (I Sin[x])^7 Cos[x]^9 + 34 (I Sin[x])^9 Cos[x]^7 + 1 (I Sin[x])^3 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^3 + 40 (I Sin[x])^8 Cos[x]^8) + Exp[-9 I y] (170 (I Sin[x])^7 Cos[x]^9 + 170 (I Sin[x])^9 Cos[x]^7 + 58 (I Sin[x])^5 Cos[x]^11 + 58 (I Sin[x])^11 Cos[x]^5 + 21 (I Sin[x])^4 Cos[x]^12 + 21 (I Sin[x])^12 Cos[x]^4 + 116 (I Sin[x])^10 Cos[x]^6 + 116 (I Sin[x])^6 Cos[x]^10 + 174 (I Sin[x])^8 Cos[x]^8 + 3 (I Sin[x])^3 Cos[x]^13 + 3 (I Sin[x])^13 Cos[x]^3) + Exp[-7 I y] (38 (I Sin[x])^3 Cos[x]^13 + 38 (I Sin[x])^13 Cos[x]^3 + 211 (I Sin[x])^5 Cos[x]^11 + 211 (I Sin[x])^11 Cos[x]^5 + 444 (I Sin[x])^7 Cos[x]^9 + 444 (I Sin[x])^9 Cos[x]^7 + 338 (I Sin[x])^6 Cos[x]^10 + 338 (I Sin[x])^10 Cos[x]^6 + 90 (I Sin[x])^4 Cos[x]^12 + 90 (I Sin[x])^12 Cos[x]^4 + 476 (I Sin[x])^8 Cos[x]^8 + 6 (I Sin[x])^2 Cos[x]^14 + 6 (I Sin[x])^14 Cos[x]^2) + Exp[-5 I y] (1304 (I Sin[x])^8 Cos[x]^8 + 722 (I Sin[x])^10 Cos[x]^6 + 722 (I Sin[x])^6 Cos[x]^10 + 134 (I Sin[x])^4 Cos[x]^12 + 134 (I Sin[x])^12 Cos[x]^4 + 32 (I Sin[x])^3 Cos[x]^13 + 32 (I Sin[x])^13 Cos[x]^3 + 1088 (I Sin[x])^9 Cos[x]^7 + 1088 (I Sin[x])^7 Cos[x]^9 + 371 (I Sin[x])^5 Cos[x]^11 + 371 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2) + Exp[-3 I y] (29 (I Sin[x])^2 Cos[x]^14 + 29 (I Sin[x])^14 Cos[x]^2 + 1233 (I Sin[x])^6 Cos[x]^10 + 1233 (I Sin[x])^10 Cos[x]^6 + 339 (I Sin[x])^4 Cos[x]^12 + 339 (I Sin[x])^12 Cos[x]^4 + 1838 (I Sin[x])^8 Cos[x]^8 + 1663 (I Sin[x])^7 Cos[x]^9 + 1663 (I Sin[x])^9 Cos[x]^7 + 718 (I Sin[x])^5 Cos[x]^11 + 718 (I Sin[x])^11 Cos[x]^5 + 99 (I Sin[x])^3 Cos[x]^13 + 99 (I Sin[x])^13 Cos[x]^3 + 5 (I Sin[x])^1 Cos[x]^15 + 5 (I Sin[x])^15 Cos[x]^1) + Exp[-1 I y] (2421 (I Sin[x])^9 Cos[x]^7 + 2421 (I Sin[x])^7 Cos[x]^9 + 745 (I Sin[x])^5 Cos[x]^11 + 745 (I Sin[x])^11 Cos[x]^5 + 260 (I Sin[x])^4 Cos[x]^12 + 260 (I Sin[x])^12 Cos[x]^4 + 2696 (I Sin[x])^8 Cos[x]^8 + 1581 (I Sin[x])^6 Cos[x]^10 + 1581 (I Sin[x])^10 Cos[x]^6 + 68 (I Sin[x])^13 Cos[x]^3 + 68 (I Sin[x])^3 Cos[x]^13 + 11 (I Sin[x])^2 Cos[x]^14 + 11 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[1 I y] (152 (I Sin[x])^3 Cos[x]^13 + 152 (I Sin[x])^13 Cos[x]^3 + 2185 (I Sin[x])^7 Cos[x]^9 + 2185 (I Sin[x])^9 Cos[x]^7 + 893 (I Sin[x])^5 Cos[x]^11 + 893 (I Sin[x])^11 Cos[x]^5 + 2454 (I Sin[x])^8 Cos[x]^8 + 1552 (I Sin[x])^6 Cos[x]^10 + 1552 (I Sin[x])^10 Cos[x]^6 + 388 (I Sin[x])^4 Cos[x]^12 + 388 (I Sin[x])^12 Cos[x]^4 + 5 (I Sin[x])^1 Cos[x]^15 + 5 (I Sin[x])^15 Cos[x]^1 + 32 (I Sin[x])^2 Cos[x]^14 + 32 (I Sin[x])^14 Cos[x]^2 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[3 I y] (1208 (I Sin[x])^10 Cos[x]^6 + 1208 (I Sin[x])^6 Cos[x]^10 + 2148 (I Sin[x])^8 Cos[x]^8 + 617 (I Sin[x])^5 Cos[x]^11 + 617 (I Sin[x])^11 Cos[x]^5 + 1813 (I Sin[x])^7 Cos[x]^9 + 1813 (I Sin[x])^9 Cos[x]^7 + 228 (I Sin[x])^12 Cos[x]^4 + 228 (I Sin[x])^4 Cos[x]^12 + 54 (I Sin[x])^3 Cos[x]^13 + 54 (I Sin[x])^13 Cos[x]^3 + 10 (I Sin[x])^2 Cos[x]^14 + 10 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^15 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^15) + Exp[5 I y] (218 (I Sin[x])^4 Cos[x]^12 + 218 (I Sin[x])^12 Cos[x]^4 + 1072 (I Sin[x])^8 Cos[x]^8 + 737 (I Sin[x])^6 Cos[x]^10 + 737 (I Sin[x])^10 Cos[x]^6 + 984 (I Sin[x])^9 Cos[x]^7 + 984 (I Sin[x])^7 Cos[x]^9 + 437 (I Sin[x])^5 Cos[x]^11 + 437 (I Sin[x])^11 Cos[x]^5 + 21 (I Sin[x])^2 Cos[x]^14 + 21 (I Sin[x])^14 Cos[x]^2 + 66 (I Sin[x])^3 Cos[x]^13 + 66 (I Sin[x])^13 Cos[x]^3 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[7 I y] (185 (I Sin[x])^11 Cos[x]^5 + 185 (I Sin[x])^5 Cos[x]^11 + 484 (I Sin[x])^9 Cos[x]^7 + 484 (I Sin[x])^7 Cos[x]^9 + 75 (I Sin[x])^4 Cos[x]^12 + 75 (I Sin[x])^12 Cos[x]^4 + 337 (I Sin[x])^6 Cos[x]^10 + 337 (I Sin[x])^10 Cos[x]^6 + 514 (I Sin[x])^8 Cos[x]^8 + 24 (I Sin[x])^3 Cos[x]^13 + 24 (I Sin[x])^13 Cos[x]^3 + 3 (I Sin[x])^14 Cos[x]^2 + 3 (I Sin[x])^2 Cos[x]^14) + Exp[9 I y] (21 (I Sin[x])^3 Cos[x]^13 + 21 (I Sin[x])^13 Cos[x]^3 + 122 (I Sin[x])^9 Cos[x]^7 + 122 (I Sin[x])^7 Cos[x]^9 + 88 (I Sin[x])^5 Cos[x]^11 + 88 (I Sin[x])^11 Cos[x]^5 + 124 (I Sin[x])^8 Cos[x]^8 + 116 (I Sin[x])^6 Cos[x]^10 + 116 (I Sin[x])^10 Cos[x]^6 + 42 (I Sin[x])^4 Cos[x]^12 + 42 (I Sin[x])^12 Cos[x]^4 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2) + Exp[11 I y] (34 (I Sin[x])^10 Cos[x]^6 + 34 (I Sin[x])^6 Cos[x]^10 + 10 (I Sin[x])^12 Cos[x]^4 + 10 (I Sin[x])^4 Cos[x]^12 + 24 (I Sin[x])^8 Cos[x]^8 + 22 (I Sin[x])^5 Cos[x]^11 + 22 (I Sin[x])^11 Cos[x]^5 + 26 (I Sin[x])^7 Cos[x]^9 + 26 (I Sin[x])^9 Cos[x]^7 + 1 (I Sin[x])^13 Cos[x]^3 + 1 (I Sin[x])^3 Cos[x]^13) + Exp[13 I y] (5 (I Sin[x])^4 Cos[x]^12 + 5 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^9 Cos[x]^7 + 2 (I Sin[x])^7 Cos[x]^9 + 4 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^5 + 1 (I Sin[x])^3 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^3) + Exp[15 I y] (1 (I Sin[x])^11 Cos[x]^5 + 1 (I Sin[x])^5 Cos[x]^11));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":750.0666666667,"max_line_length":5402,"alphanum_fraction":0.504132966} {"size":9777,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 15;\nname = \"15v2 1 3 1 2 2 3 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-14 I y] (1 (I Sin[x])^5 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^5) + Exp[-12 I y] (1 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^4 + 6 (I Sin[x])^9 Cos[x]^6 + 6 (I Sin[x])^6 Cos[x]^9 + 2 (I Sin[x])^5 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^5 + 5 (I Sin[x])^8 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^8) + Exp[-10 I y] (31 (I Sin[x])^6 Cos[x]^9 + 31 (I Sin[x])^9 Cos[x]^6 + 7 (I Sin[x])^4 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616 (I Sin[x])^8 Cos[x]^8 + 503 (I Sin[x])^7 Cos[x]^9 + 503 (I Sin[x])^9 Cos[x]^7 + 161 (I Sin[x])^5 Cos[x]^11 + 161 (I Sin[x])^11 Cos[x]^5 + 53 (I Sin[x])^4 Cos[x]^12 + 53 (I Sin[x])^12 Cos[x]^4 + 8 (I Sin[x])^3 Cos[x]^13 + 8 (I Sin[x])^13 Cos[x]^3) + Exp[-5 I y] (1171 (I Sin[x])^9 Cos[x]^7 + 1171 (I Sin[x])^7 Cos[x]^9 + 321 (I Sin[x])^5 Cos[x]^11 + 321 (I Sin[x])^11 Cos[x]^5 + 730 (I Sin[x])^6 Cos[x]^10 + 730 (I Sin[x])^10 Cos[x]^6 + 1320 (I Sin[x])^8 Cos[x]^8 + 101 (I Sin[x])^12 Cos[x]^4 + 101 (I Sin[x])^4 Cos[x]^12 + 20 (I Sin[x])^13 Cos[x]^3 + 20 (I Sin[x])^3 Cos[x]^13) + Exp[-3 I y] (654 (I Sin[x])^5 Cos[x]^11 + 654 (I Sin[x])^11 Cos[x]^5 + 1793 (I Sin[x])^7 Cos[x]^9 + 1793 (I Sin[x])^9 Cos[x]^7 + 1976 (I Sin[x])^8 Cos[x]^8 + 1229 (I Sin[x])^6 Cos[x]^10 + 1229 (I Sin[x])^10 Cos[x]^6 + 256 (I Sin[x])^4 Cos[x]^12 + 256 (I Sin[x])^12 Cos[x]^4 + 73 (I Sin[x])^3 Cos[x]^13 + 73 (I Sin[x])^13 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2) + Exp[-1 I y] (1536 (I 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(I Sin[x])^13 Cos[x]^3 + 4 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^4 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^4 + 1 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^6) + Exp[15 I y] (1 (I Sin[x])^10 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^10))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-15 I y] (2 (I Sin[x])^8 Cos[x]^8) + Exp[-13 I y] (8 (I Sin[x])^9 Cos[x]^7 + 8 (I Sin[x])^7 Cos[x]^9 + 10 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^6) + Exp[-11 I y] (50 (I Sin[x])^7 Cos[x]^9 + 50 (I Sin[x])^9 Cos[x]^7 + 25 (I Sin[x])^6 Cos[x]^10 + 25 (I Sin[x])^10 Cos[x]^6 + 48 (I Sin[x])^8 Cos[x]^8 + 6 (I Sin[x])^5 Cos[x]^11 + 6 (I Sin[x])^11 Cos[x]^5) + Exp[-9 I y] (200 (I Sin[x])^8 Cos[x]^8 + 119 (I Sin[x])^6 Cos[x]^10 + 119 (I Sin[x])^10 Cos[x]^6 + 169 (I Sin[x])^7 Cos[x]^9 + 169 (I Sin[x])^9 Cos[x]^7 + 55 (I Sin[x])^5 Cos[x]^11 + 55 (I Sin[x])^11 Cos[x]^5 + 12 (I Sin[x])^12 Cos[x]^4 + 12 (I Sin[x])^4 Cos[x]^12) + Exp[-7 I y] (332 (I Sin[x])^6 Cos[x]^10 + 332 (I Sin[x])^10 Cos[x]^6 + 616 (I Sin[x])^8 Cos[x]^8 + 503 (I Sin[x])^7 Cos[x]^9 + 503 (I Sin[x])^9 Cos[x]^7 + 161 (I Sin[x])^5 Cos[x]^11 + 161 (I Sin[x])^11 Cos[x]^5 + 53 (I Sin[x])^4 Cos[x]^12 + 53 (I Sin[x])^12 Cos[x]^4 + 8 (I Sin[x])^3 Cos[x]^13 + 8 (I Sin[x])^13 Cos[x]^3) + Exp[-5 I y] (1171 (I Sin[x])^9 Cos[x]^7 + 1171 (I Sin[x])^7 Cos[x]^9 + 321 (I Sin[x])^5 Cos[x]^11 + 321 (I Sin[x])^11 Cos[x]^5 + 730 (I Sin[x])^6 Cos[x]^10 + 730 (I Sin[x])^10 Cos[x]^6 + 1320 (I Sin[x])^8 Cos[x]^8 + 101 (I Sin[x])^12 Cos[x]^4 + 101 (I Sin[x])^4 Cos[x]^12 + 20 (I Sin[x])^13 Cos[x]^3 + 20 (I Sin[x])^3 Cos[x]^13) + Exp[-3 I y] (654 (I Sin[x])^5 Cos[x]^11 + 654 (I Sin[x])^11 Cos[x]^5 + 1793 (I Sin[x])^7 Cos[x]^9 + 1793 (I Sin[x])^9 Cos[x]^7 + 1976 (I Sin[x])^8 Cos[x]^8 + 1229 (I Sin[x])^6 Cos[x]^10 + 1229 (I Sin[x])^10 Cos[x]^6 + 256 (I Sin[x])^4 Cos[x]^12 + 256 (I Sin[x])^12 Cos[x]^4 + 73 (I Sin[x])^3 Cos[x]^13 + 73 (I Sin[x])^13 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2) + Exp[-1 I y] (1536 (I Sin[x])^10 Cos[x]^6 + 1536 (I Sin[x])^6 Cos[x]^10 + 2852 (I Sin[x])^8 Cos[x]^8 + 262 (I Sin[x])^4 Cos[x]^12 + 262 (I Sin[x])^12 Cos[x]^4 + 2388 (I Sin[x])^7 Cos[x]^9 + 2388 (I Sin[x])^9 Cos[x]^7 + 751 (I Sin[x])^5 Cos[x]^11 + 751 (I Sin[x])^11 Cos[x]^5 + 61 (I Sin[x])^3 Cos[x]^13 + 61 (I Sin[x])^13 Cos[x]^3 + 11 (I Sin[x])^2 Cos[x]^14 + 11 (I Sin[x])^14 Cos[x]^2) + Exp[1 I y] (1596 (I Sin[x])^6 Cos[x]^10 + 1596 (I Sin[x])^10 Cos[x]^6 + 2306 (I Sin[x])^8 Cos[x]^8 + 2086 (I Sin[x])^9 Cos[x]^7 + 2086 (I Sin[x])^7 Cos[x]^9 + 955 (I Sin[x])^5 Cos[x]^11 + 955 (I Sin[x])^11 Cos[x]^5 + 450 (I Sin[x])^4 Cos[x]^12 + 450 (I Sin[x])^12 Cos[x]^4 + 153 (I Sin[x])^3 Cos[x]^13 + 153 (I Sin[x])^13 Cos[x]^3 + 36 (I Sin[x])^2 Cos[x]^14 + 36 (I Sin[x])^14 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^15 + 6 (I Sin[x])^15 Cos[x]^1) + Exp[3 I y] (653 (I Sin[x])^11 Cos[x]^5 + 653 (I Sin[x])^5 Cos[x]^11 + 1790 (I Sin[x])^7 Cos[x]^9 + 1790 (I Sin[x])^9 Cos[x]^7 + 75 (I Sin[x])^3 Cos[x]^13 + 75 (I Sin[x])^13 Cos[x]^3 + 1250 (I Sin[x])^6 Cos[x]^10 + 1250 (I Sin[x])^10 Cos[x]^6 + 258 (I Sin[x])^4 Cos[x]^12 + 258 (I Sin[x])^12 Cos[x]^4 + 1930 (I Sin[x])^8 Cos[x]^8 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[5 I y] (507 (I Sin[x])^5 Cos[x]^11 + 507 (I Sin[x])^11 Cos[x]^5 + 884 (I Sin[x])^9 Cos[x]^7 + 884 (I Sin[x])^7 Cos[x]^9 + 712 (I Sin[x])^10 Cos[x]^6 + 712 (I Sin[x])^6 Cos[x]^10 + 274 (I Sin[x])^4 Cos[x]^12 + 274 (I Sin[x])^12 Cos[x]^4 + 938 (I Sin[x])^8 Cos[x]^8 + 115 (I Sin[x])^3 Cos[x]^13 + 115 (I Sin[x])^13 Cos[x]^3 + 35 (I Sin[x])^2 Cos[x]^14 + 35 (I Sin[x])^14 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^15 + 6 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[7 I y] (86 (I Sin[x])^12 Cos[x]^4 + 86 (I Sin[x])^4 Cos[x]^12 + 516 (I Sin[x])^8 Cos[x]^8 + 344 (I Sin[x])^10 Cos[x]^6 + 344 (I Sin[x])^6 Cos[x]^10 + 5 (I Sin[x])^2 Cos[x]^14 + 5 (I Sin[x])^14 Cos[x]^2 + 206 (I Sin[x])^5 Cos[x]^11 + 206 (I Sin[x])^11 Cos[x]^5 + 23 (I Sin[x])^3 Cos[x]^13 + 23 (I Sin[x])^13 Cos[x]^3 + 443 (I Sin[x])^7 Cos[x]^9 + 443 (I Sin[x])^9 Cos[x]^7) + Exp[9 I y] (57 (I Sin[x])^4 Cos[x]^12 + 57 (I Sin[x])^12 Cos[x]^4 + 108 (I Sin[x])^10 Cos[x]^6 + 108 (I Sin[x])^6 Cos[x]^10 + 116 (I Sin[x])^8 Cos[x]^8 + 115 (I Sin[x])^9 Cos[x]^7 + 115 (I Sin[x])^7 Cos[x]^9 + 80 (I Sin[x])^5 Cos[x]^11 + 80 (I Sin[x])^11 Cos[x]^5 + 27 (I Sin[x])^3 Cos[x]^13 + 27 (I Sin[x])^13 Cos[x]^3 + 8 (I Sin[x])^2 Cos[x]^14 + 8 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[11 I y] (16 (I Sin[x])^11 Cos[x]^5 + 16 (I Sin[x])^5 Cos[x]^11 + 37 (I Sin[x])^9 Cos[x]^7 + 37 (I Sin[x])^7 Cos[x]^9 + 3 (I Sin[x])^13 Cos[x]^3 + 3 (I Sin[x])^3 Cos[x]^13 + 22 (I Sin[x])^6 Cos[x]^10 + 22 (I Sin[x])^10 Cos[x]^6 + 9 (I Sin[x])^4 Cos[x]^12 + 9 (I Sin[x])^12 Cos[x]^4 + 36 (I Sin[x])^8 Cos[x]^8) + Exp[13 I y] (3 (I Sin[x])^5 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^5 + 3 (I Sin[x])^9 Cos[x]^7 + 3 (I Sin[x])^7 Cos[x]^9 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3 + 4 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^4 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^4 + 1 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^6) + Exp[15 I y] (1 (I Sin[x])^10 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^10));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":702.6,"max_line_length":5044,"alphanum_fraction":0.5049814973} {"size":10777,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 16;\nname = \"16v4 1 1 1 2 1 1 1 4\";\nnstates = 2;\n\namplitude[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4) + Exp[-13 I y] (2 (I Sin[x])^5 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^5 + 2 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^6 + 6 (I Sin[x])^7 Cos[x]^9 + 6 (I Sin[x])^9 Cos[x]^7 + 10 (I Sin[x])^8 Cos[x]^8) + Exp[-11 I y] (32 (I Sin[x])^5 Cos[x]^11 + 32 (I Sin[x])^11 Cos[x]^5 + 26 (I Sin[x])^6 Cos[x]^10 + 26 (I Sin[x])^10 Cos[x]^6 + 18 (I Sin[x])^7 Cos[x]^9 + 18 (I Sin[x])^9 Cos[x]^7 + 6 (I Sin[x])^3 Cos[x]^13 + 6 (I Sin[x])^13 Cos[x]^3 + 16 (I Sin[x])^4 Cos[x]^12 + 16 (I Sin[x])^12 Cos[x]^4 + 14 (I Sin[x])^8 Cos[x]^8) + Exp[-9 I y] (120 (I Sin[x])^6 Cos[x]^10 + 120 (I Sin[x])^10 Cos[x]^6 + 180 (I Sin[x])^7 Cos[x]^9 + 180 (I Sin[x])^9 Cos[x]^7 + 12 (I Sin[x])^4 Cos[x]^12 + 12 (I Sin[x])^12 Cos[x]^4 + 44 (I Sin[x])^5 Cos[x]^11 + 44 (I Sin[x])^11 Cos[x]^5 + 198 (I Sin[x])^8 Cos[x]^8) + Exp[-7 I y] (361 (I Sin[x])^6 Cos[x]^10 + 361 (I Sin[x])^10 Cos[x]^6 + 126 (I Sin[x])^4 Cos[x]^12 + 126 (I Sin[x])^12 Cos[x]^4 + 236 (I Sin[x])^5 Cos[x]^11 + 236 (I Sin[x])^11 Cos[x]^5 + 392 (I Sin[x])^7 Cos[x]^9 + 392 (I Sin[x])^9 Cos[x]^7 + 390 (I Sin[x])^8 Cos[x]^8 + 11 (I Sin[x])^2 Cos[x]^14 + 11 (I Sin[x])^14 Cos[x]^2 + 44 (I Sin[x])^3 Cos[x]^13 + 44 (I Sin[x])^13 Cos[x]^3) + Exp[-5 I y] (360 (I Sin[x])^5 Cos[x]^11 + 360 (I Sin[x])^11 Cos[x]^5 + 1130 (I Sin[x])^7 Cos[x]^9 + 1130 (I Sin[x])^9 Cos[x]^7 + 1302 (I Sin[x])^8 Cos[x]^8 + 730 (I Sin[x])^6 Cos[x]^10 + 730 (I Sin[x])^10 Cos[x]^6 + 22 (I Sin[x])^3 Cos[x]^13 + 22 (I Sin[x])^13 Cos[x]^3 + 110 (I Sin[x])^4 Cos[x]^12 + 110 (I Sin[x])^12 Cos[x]^4) + Exp[-3 I y] (1680 (I Sin[x])^7 Cos[x]^9 + 1680 (I Sin[x])^9 Cos[x]^7 + 726 (I Sin[x])^5 Cos[x]^11 + 726 (I Sin[x])^11 Cos[x]^5 + 108 (I Sin[x])^3 Cos[x]^13 + 108 (I Sin[x])^13 Cos[x]^3 + 325 (I Sin[x])^4 Cos[x]^12 + 325 (I Sin[x])^12 Cos[x]^4 + 1197 (I Sin[x])^6 Cos[x]^10 + 1197 (I Sin[x])^10 Cos[x]^6 + 1876 (I Sin[x])^8 Cos[x]^8 + 6 (I Sin[x])^1 Cos[x]^15 + 6 (I Sin[x])^15 Cos[x]^1 + 25 (I Sin[x])^2 Cos[x]^14 + 25 (I Sin[x])^14 Cos[x]^2) + Exp[-1 I y] (258 (I Sin[x])^4 Cos[x]^12 + 258 (I Sin[x])^12 Cos[x]^4 + 1548 (I Sin[x])^6 Cos[x]^10 + 1548 (I Sin[x])^10 Cos[x]^6 + 2834 (I Sin[x])^8 Cos[x]^8 + 2420 (I Sin[x])^9 Cos[x]^7 + 2420 (I Sin[x])^7 Cos[x]^9 + 718 (I Sin[x])^5 Cos[x]^11 + 718 (I Sin[x])^11 Cos[x]^5 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2 + 62 (I Sin[x])^3 Cos[x]^13 + 62 (I Sin[x])^13 Cos[x]^3) + Exp[1 I y] (2498 (I Sin[x])^8 Cos[x]^8 + 1581 (I Sin[x])^6 Cos[x]^10 + 1581 (I Sin[x])^10 Cos[x]^6 + 369 (I Sin[x])^4 Cos[x]^12 + 369 (I Sin[x])^12 Cos[x]^4 + 838 (I Sin[x])^5 Cos[x]^11 + 838 (I Sin[x])^11 Cos[x]^5 + 2224 (I Sin[x])^7 Cos[x]^9 + 2224 (I Sin[x])^9 Cos[x]^7 + 35 (I Sin[x])^2 Cos[x]^14 + 35 (I Sin[x])^14 Cos[x]^2 + 134 (I Sin[x])^3 Cos[x]^13 + 134 (I Sin[x])^13 Cos[x]^3 + 1 Cos[x]^16 + 1 (I Sin[x])^16 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[3 I y] (638 (I Sin[x])^5 Cos[x]^11 + 638 (I Sin[x])^11 Cos[x]^5 + 68 (I Sin[x])^3 Cos[x]^13 + 68 (I Sin[x])^13 Cos[x]^3 + 1812 (I Sin[x])^7 Cos[x]^9 + 1812 (I Sin[x])^9 Cos[x]^7 + 2026 (I Sin[x])^8 Cos[x]^8 + 1220 (I Sin[x])^6 Cos[x]^10 + 1220 (I Sin[x])^10 Cos[x]^6 + 242 (I Sin[x])^4 Cos[x]^12 + 242 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1 + 10 (I Sin[x])^2 Cos[x]^14 + 10 (I Sin[x])^14 Cos[x]^2) + Exp[5 I y] (982 (I Sin[x])^7 Cos[x]^9 + 982 (I Sin[x])^9 Cos[x]^7 + 458 (I Sin[x])^5 Cos[x]^11 + 458 (I Sin[x])^11 Cos[x]^5 + 717 (I Sin[x])^6 Cos[x]^10 + 717 (I Sin[x])^10 Cos[x]^6 + 1086 (I Sin[x])^8 Cos[x]^8 + 68 (I Sin[x])^3 Cos[x]^13 + 68 (I Sin[x])^13 Cos[x]^3 + 214 (I Sin[x])^4 Cos[x]^12 + 214 (I Sin[x])^12 Cos[x]^4 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1 + 17 (I Sin[x])^2 Cos[x]^14 + 17 (I Sin[x])^14 Cos[x]^2) + Exp[7 I y] (362 (I Sin[x])^6 Cos[x]^10 + 362 (I Sin[x])^10 Cos[x]^6 + 94 (I Sin[x])^4 Cos[x]^12 + 94 (I Sin[x])^12 Cos[x]^4 + 6 (I Sin[x])^2 Cos[x]^14 + 6 (I Sin[x])^14 Cos[x]^2 + 424 (I Sin[x])^7 Cos[x]^9 + 424 (I Sin[x])^9 Cos[x]^7 + 222 (I Sin[x])^5 Cos[x]^11 + 222 (I Sin[x])^11 Cos[x]^5 + 26 (I Sin[x])^3 Cos[x]^13 + 26 (I Sin[x])^13 Cos[x]^3 + 462 (I Sin[x])^8 Cos[x]^8) + Exp[9 I y] (120 (I Sin[x])^6 Cos[x]^10 + 120 (I Sin[x])^10 Cos[x]^6 + 134 (I Sin[x])^8 Cos[x]^8 + 132 (I Sin[x])^7 Cos[x]^9 + 132 (I Sin[x])^9 Cos[x]^7 + 74 (I Sin[x])^11 Cos[x]^5 + 74 (I Sin[x])^5 Cos[x]^11 + 40 (I Sin[x])^4 Cos[x]^12 + 40 (I Sin[x])^12 Cos[x]^4 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2 + 18 (I Sin[x])^3 Cos[x]^13 + 18 (I Sin[x])^13 Cos[x]^3) + Exp[11 I y] (34 (I Sin[x])^7 Cos[x]^9 + 34 (I Sin[x])^9 Cos[x]^7 + 18 (I Sin[x])^5 Cos[x]^11 + 18 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^3 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^3 + 30 (I Sin[x])^8 Cos[x]^8 + 22 (I Sin[x])^6 Cos[x]^10 + 22 (I Sin[x])^10 Cos[x]^6 + 12 (I Sin[x])^4 Cos[x]^12 + 12 (I Sin[x])^12 Cos[x]^4) + Exp[13 I y] (6 (I Sin[x])^7 Cos[x]^9 + 6 (I Sin[x])^9 Cos[x]^7 + 2 (I Sin[x])^11 Cos[x]^5 + 2 (I Sin[x])^5 Cos[x]^11 + 8 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^6 Cos[x]^10 + 1 (I Sin[x])^12 Cos[x]^4 + 1 (I Sin[x])^4 Cos[x]^12) + Exp[15 I y] (2 (I Sin[x])^8 Cos[x]^8))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4) + Exp[-13 I y] (2 (I Sin[x])^5 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^5 + 2 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^6 + 6 (I Sin[x])^7 Cos[x]^9 + 6 (I Sin[x])^9 Cos[x]^7 + 10 (I Sin[x])^8 Cos[x]^8) + Exp[-11 I y] (32 (I Sin[x])^5 Cos[x]^11 + 32 (I Sin[x])^11 Cos[x]^5 + 26 (I Sin[x])^6 Cos[x]^10 + 26 (I Sin[x])^10 Cos[x]^6 + 18 (I Sin[x])^7 Cos[x]^9 + 18 (I Sin[x])^9 Cos[x]^7 + 6 (I Sin[x])^3 Cos[x]^13 + 6 (I Sin[x])^13 Cos[x]^3 + 16 (I Sin[x])^4 Cos[x]^12 + 16 (I Sin[x])^12 Cos[x]^4 + 14 (I Sin[x])^8 Cos[x]^8) + Exp[-9 I y] (120 (I Sin[x])^6 Cos[x]^10 + 120 (I Sin[x])^10 Cos[x]^6 + 180 (I Sin[x])^7 Cos[x]^9 + 180 (I Sin[x])^9 Cos[x]^7 + 12 (I Sin[x])^4 Cos[x]^12 + 12 (I Sin[x])^12 Cos[x]^4 + 44 (I Sin[x])^5 Cos[x]^11 + 44 (I Sin[x])^11 Cos[x]^5 + 198 (I Sin[x])^8 Cos[x]^8) + Exp[-7 I y] (361 (I Sin[x])^6 Cos[x]^10 + 361 (I Sin[x])^10 Cos[x]^6 + 126 (I Sin[x])^4 Cos[x]^12 + 126 (I Sin[x])^12 Cos[x]^4 + 236 (I Sin[x])^5 Cos[x]^11 + 236 (I Sin[x])^11 Cos[x]^5 + 392 (I Sin[x])^7 Cos[x]^9 + 392 (I Sin[x])^9 Cos[x]^7 + 390 (I Sin[x])^8 Cos[x]^8 + 11 (I Sin[x])^2 Cos[x]^14 + 11 (I Sin[x])^14 Cos[x]^2 + 44 (I Sin[x])^3 Cos[x]^13 + 44 (I Sin[x])^13 Cos[x]^3) + Exp[-5 I y] (360 (I Sin[x])^5 Cos[x]^11 + 360 (I Sin[x])^11 Cos[x]^5 + 1130 (I Sin[x])^7 Cos[x]^9 + 1130 (I Sin[x])^9 Cos[x]^7 + 1302 (I Sin[x])^8 Cos[x]^8 + 730 (I Sin[x])^6 Cos[x]^10 + 730 (I Sin[x])^10 Cos[x]^6 + 22 (I Sin[x])^3 Cos[x]^13 + 22 (I Sin[x])^13 Cos[x]^3 + 110 (I Sin[x])^4 Cos[x]^12 + 110 (I Sin[x])^12 Cos[x]^4) + Exp[-3 I y] (1680 (I Sin[x])^7 Cos[x]^9 + 1680 (I Sin[x])^9 Cos[x]^7 + 726 (I Sin[x])^5 Cos[x]^11 + 726 (I Sin[x])^11 Cos[x]^5 + 108 (I Sin[x])^3 Cos[x]^13 + 108 (I Sin[x])^13 Cos[x]^3 + 325 (I Sin[x])^4 Cos[x]^12 + 325 (I Sin[x])^12 Cos[x]^4 + 1197 (I Sin[x])^6 Cos[x]^10 + 1197 (I Sin[x])^10 Cos[x]^6 + 1876 (I Sin[x])^8 Cos[x]^8 + 6 (I Sin[x])^1 Cos[x]^15 + 6 (I Sin[x])^15 Cos[x]^1 + 25 (I Sin[x])^2 Cos[x]^14 + 25 (I Sin[x])^14 Cos[x]^2) + Exp[-1 I y] (258 (I Sin[x])^4 Cos[x]^12 + 258 (I Sin[x])^12 Cos[x]^4 + 1548 (I Sin[x])^6 Cos[x]^10 + 1548 (I Sin[x])^10 Cos[x]^6 + 2834 (I Sin[x])^8 Cos[x]^8 + 2420 (I Sin[x])^9 Cos[x]^7 + 2420 (I Sin[x])^7 Cos[x]^9 + 718 (I Sin[x])^5 Cos[x]^11 + 718 (I Sin[x])^11 Cos[x]^5 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2 + 62 (I Sin[x])^3 Cos[x]^13 + 62 (I Sin[x])^13 Cos[x]^3) + Exp[1 I y] (2498 (I Sin[x])^8 Cos[x]^8 + 1581 (I Sin[x])^6 Cos[x]^10 + 1581 (I Sin[x])^10 Cos[x]^6 + 369 (I Sin[x])^4 Cos[x]^12 + 369 (I Sin[x])^12 Cos[x]^4 + 838 (I Sin[x])^5 Cos[x]^11 + 838 (I Sin[x])^11 Cos[x]^5 + 2224 (I Sin[x])^7 Cos[x]^9 + 2224 (I Sin[x])^9 Cos[x]^7 + 35 (I Sin[x])^2 Cos[x]^14 + 35 (I Sin[x])^14 Cos[x]^2 + 134 (I Sin[x])^3 Cos[x]^13 + 134 (I Sin[x])^13 Cos[x]^3 + 1 Cos[x]^16 + 1 (I Sin[x])^16 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[3 I y] (638 (I Sin[x])^5 Cos[x]^11 + 638 (I Sin[x])^11 Cos[x]^5 + 68 (I Sin[x])^3 Cos[x]^13 + 68 (I Sin[x])^13 Cos[x]^3 + 1812 (I Sin[x])^7 Cos[x]^9 + 1812 (I Sin[x])^9 Cos[x]^7 + 2026 (I Sin[x])^8 Cos[x]^8 + 1220 (I Sin[x])^6 Cos[x]^10 + 1220 (I Sin[x])^10 Cos[x]^6 + 242 (I Sin[x])^4 Cos[x]^12 + 242 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1 + 10 (I Sin[x])^2 Cos[x]^14 + 10 (I Sin[x])^14 Cos[x]^2) + Exp[5 I y] (982 (I Sin[x])^7 Cos[x]^9 + 982 (I Sin[x])^9 Cos[x]^7 + 458 (I Sin[x])^5 Cos[x]^11 + 458 (I Sin[x])^11 Cos[x]^5 + 717 (I Sin[x])^6 Cos[x]^10 + 717 (I Sin[x])^10 Cos[x]^6 + 1086 (I Sin[x])^8 Cos[x]^8 + 68 (I Sin[x])^3 Cos[x]^13 + 68 (I Sin[x])^13 Cos[x]^3 + 214 (I Sin[x])^4 Cos[x]^12 + 214 (I Sin[x])^12 Cos[x]^4 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1 + 17 (I Sin[x])^2 Cos[x]^14 + 17 (I Sin[x])^14 Cos[x]^2) + Exp[7 I y] (362 (I Sin[x])^6 Cos[x]^10 + 362 (I Sin[x])^10 Cos[x]^6 + 94 (I Sin[x])^4 Cos[x]^12 + 94 (I Sin[x])^12 Cos[x]^4 + 6 (I Sin[x])^2 Cos[x]^14 + 6 (I Sin[x])^14 Cos[x]^2 + 424 (I Sin[x])^7 Cos[x]^9 + 424 (I Sin[x])^9 Cos[x]^7 + 222 (I Sin[x])^5 Cos[x]^11 + 222 (I Sin[x])^11 Cos[x]^5 + 26 (I Sin[x])^3 Cos[x]^13 + 26 (I Sin[x])^13 Cos[x]^3 + 462 (I Sin[x])^8 Cos[x]^8) + Exp[9 I y] (120 (I Sin[x])^6 Cos[x]^10 + 120 (I Sin[x])^10 Cos[x]^6 + 134 (I Sin[x])^8 Cos[x]^8 + 132 (I Sin[x])^7 Cos[x]^9 + 132 (I Sin[x])^9 Cos[x]^7 + 74 (I Sin[x])^11 Cos[x]^5 + 74 (I Sin[x])^5 Cos[x]^11 + 40 (I Sin[x])^4 Cos[x]^12 + 40 (I Sin[x])^12 Cos[x]^4 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2 + 18 (I Sin[x])^3 Cos[x]^13 + 18 (I Sin[x])^13 Cos[x]^3) + Exp[11 I y] (34 (I Sin[x])^7 Cos[x]^9 + 34 (I Sin[x])^9 Cos[x]^7 + 18 (I Sin[x])^5 Cos[x]^11 + 18 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^3 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^3 + 30 (I Sin[x])^8 Cos[x]^8 + 22 (I Sin[x])^6 Cos[x]^10 + 22 (I Sin[x])^10 Cos[x]^6 + 12 (I Sin[x])^4 Cos[x]^12 + 12 (I Sin[x])^12 Cos[x]^4) + Exp[13 I y] (6 (I Sin[x])^7 Cos[x]^9 + 6 (I Sin[x])^9 Cos[x]^7 + 2 (I Sin[x])^11 Cos[x]^5 + 2 (I Sin[x])^5 Cos[x]^11 + 8 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^6 Cos[x]^10 + 1 (I Sin[x])^12 Cos[x]^4 + 1 (I Sin[x])^4 Cos[x]^12) + Exp[15 I y] (2 (I Sin[x])^8 Cos[x]^8));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":718.4666666667,"max_line_length":5165,"alphanum_fraction":0.5057065974} {"size":11143,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 16;\nname = \"16v5 2 1 1 5 1 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4) + Exp[-13 I y] (3 (I Sin[x])^5 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^5 + 1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^6 Cos[x]^10 + 5 (I Sin[x])^9 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^9 + 8 (I Sin[x])^8 Cos[x]^8) + Exp[-11 I y] (9 (I Sin[x])^3 Cos[x]^13 + 9 (I Sin[x])^13 Cos[x]^3 + 22 (I Sin[x])^5 Cos[x]^11 + 22 (I Sin[x])^11 Cos[x]^5 + 11 (I Sin[x])^4 Cos[x]^12 + 11 (I Sin[x])^12 Cos[x]^4 + 23 (I Sin[x])^6 Cos[x]^10 + 23 (I Sin[x])^10 Cos[x]^6 + 25 (I Sin[x])^7 Cos[x]^9 + 25 (I Sin[x])^9 Cos[x]^7 + 26 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^2 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^2) + Exp[-9 I y] (121 (I Sin[x])^6 Cos[x]^10 + 121 (I Sin[x])^10 Cos[x]^6 + 71 (I Sin[x])^5 Cos[x]^11 + 71 (I Sin[x])^11 Cos[x]^5 + 139 (I Sin[x])^9 Cos[x]^7 + 139 (I Sin[x])^7 Cos[x]^9 + 138 (I Sin[x])^8 Cos[x]^8 + 39 (I Sin[x])^12 Cos[x]^4 + 39 (I Sin[x])^4 Cos[x]^12 + 14 (I Sin[x])^13 Cos[x]^3 + 14 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^2 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^2) + Exp[-7 I y] (135 (I Sin[x])^4 Cos[x]^12 + 135 (I Sin[x])^12 Cos[x]^4 + 338 (I Sin[x])^6 Cos[x]^10 + 338 (I Sin[x])^10 Cos[x]^6 + 229 (I Sin[x])^5 Cos[x]^11 + 229 (I Sin[x])^11 Cos[x]^5 + 396 (I Sin[x])^7 Cos[x]^9 + 396 (I Sin[x])^9 Cos[x]^7 + 412 (I Sin[x])^8 Cos[x]^8 + 44 (I Sin[x])^3 Cos[x]^13 + 44 (I Sin[x])^13 Cos[x]^3 + 14 (I Sin[x])^2 Cos[x]^14 + 14 (I Sin[x])^14 Cos[x]^2 + 3 (I Sin[x])^1 Cos[x]^15 + 3 (I Sin[x])^15 Cos[x]^1) + Exp[-5 I y] (1023 (I Sin[x])^7 Cos[x]^9 + 1023 (I Sin[x])^9 Cos[x]^7 + 442 (I Sin[x])^11 Cos[x]^5 + 442 (I Sin[x])^5 Cos[x]^11 + 737 (I Sin[x])^6 Cos[x]^10 + 737 (I Sin[x])^10 Cos[x]^6 + 1142 (I Sin[x])^8 Cos[x]^8 + 174 (I Sin[x])^12 Cos[x]^4 + 174 (I Sin[x])^4 Cos[x]^12 + 46 (I Sin[x])^13 Cos[x]^3 + 46 (I Sin[x])^3 Cos[x]^13 + 9 (I Sin[x])^14 Cos[x]^2 + 9 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[-3 I y] (734 (I Sin[x])^5 Cos[x]^11 + 734 (I Sin[x])^11 Cos[x]^5 + 1647 (I Sin[x])^7 Cos[x]^9 + 1647 (I Sin[x])^9 Cos[x]^7 + 1208 (I Sin[x])^6 Cos[x]^10 + 1208 (I Sin[x])^10 Cos[x]^6 + 329 (I Sin[x])^4 Cos[x]^12 + 329 (I Sin[x])^12 Cos[x]^4 + 134 (I Sin[x])^3 Cos[x]^13 + 134 (I Sin[x])^13 Cos[x]^3 + 1828 (I Sin[x])^8 Cos[x]^8 + 33 (I Sin[x])^2 Cos[x]^14 + 33 (I Sin[x])^14 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^15 + 5 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[-1 I y] (2708 (I Sin[x])^8 Cos[x]^8 + 1591 (I Sin[x])^10 Cos[x]^6 + 1591 (I Sin[x])^6 Cos[x]^10 + 750 (I Sin[x])^5 Cos[x]^11 + 750 (I Sin[x])^11 Cos[x]^5 + 2375 (I Sin[x])^9 Cos[x]^7 + 2375 (I Sin[x])^7 Cos[x]^9 + 278 (I Sin[x])^12 Cos[x]^4 + 278 (I Sin[x])^4 Cos[x]^12 + 74 (I Sin[x])^13 Cos[x]^3 + 74 (I Sin[x])^3 Cos[x]^13 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^15 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^15) + Exp[1 I y] (407 (I Sin[x])^4 Cos[x]^12 + 407 (I Sin[x])^12 Cos[x]^4 + 1576 (I Sin[x])^6 Cos[x]^10 + 1576 (I Sin[x])^10 Cos[x]^6 + 2440 (I Sin[x])^8 Cos[x]^8 + 2194 (I Sin[x])^7 Cos[x]^9 + 2194 (I Sin[x])^9 Cos[x]^7 + 875 (I Sin[x])^5 Cos[x]^11 + 875 (I Sin[x])^11 Cos[x]^5 + 125 (I Sin[x])^3 Cos[x]^13 + 125 (I Sin[x])^13 Cos[x]^3 + 32 (I Sin[x])^2 Cos[x]^14 + 32 (I Sin[x])^14 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^15 + 6 (I Sin[x])^15 Cos[x]^1) + Exp[3 I y] (1907 (I Sin[x])^9 Cos[x]^7 + 1907 (I Sin[x])^7 Cos[x]^9 + 572 (I Sin[x])^11 Cos[x]^5 + 572 (I Sin[x])^5 Cos[x]^11 + 187 (I Sin[x])^4 Cos[x]^12 + 187 (I Sin[x])^12 Cos[x]^4 + 2232 (I Sin[x])^8 Cos[x]^8 + 1177 (I Sin[x])^6 Cos[x]^10 + 1177 (I Sin[x])^10 Cos[x]^6 + 41 (I Sin[x])^3 Cos[x]^13 + 41 (I Sin[x])^13 Cos[x]^3 + 5 (I Sin[x])^14 Cos[x]^2 + 5 (I Sin[x])^2 Cos[x]^14) + Exp[5 I y] (60 (I Sin[x])^3 Cos[x]^13 + 60 (I Sin[x])^13 Cos[x]^3 + 1011 (I Sin[x])^7 Cos[x]^9 + 1011 (I Sin[x])^9 Cos[x]^7 + 441 (I Sin[x])^5 Cos[x]^11 + 441 (I Sin[x])^11 Cos[x]^5 + 736 (I Sin[x])^6 Cos[x]^10 + 736 (I Sin[x])^10 Cos[x]^6 + 179 (I Sin[x])^4 Cos[x]^12 + 179 (I Sin[x])^12 Cos[x]^4 + 11 (I Sin[x])^2 Cos[x]^14 + 11 (I Sin[x])^14 Cos[x]^2 + 1130 (I Sin[x])^8 Cos[x]^8) + Exp[7 I y] (586 (I Sin[x])^8 Cos[x]^8 + 353 (I Sin[x])^10 Cos[x]^6 + 353 (I Sin[x])^6 Cos[x]^10 + 152 (I Sin[x])^5 Cos[x]^11 + 152 (I Sin[x])^11 Cos[x]^5 + 513 (I Sin[x])^7 Cos[x]^9 + 513 (I Sin[x])^9 Cos[x]^7 + 47 (I Sin[x])^4 Cos[x]^12 + 47 (I Sin[x])^12 Cos[x]^4 + 7 (I Sin[x])^13 Cos[x]^3 + 7 (I Sin[x])^3 Cos[x]^13) + Exp[9 I y] (29 (I Sin[x])^4 Cos[x]^12 + 29 (I Sin[x])^12 Cos[x]^4 + 164 (I Sin[x])^8 Cos[x]^8 + 120 (I Sin[x])^6 Cos[x]^10 + 120 (I Sin[x])^10 Cos[x]^6 + 157 (I Sin[x])^7 Cos[x]^9 + 157 (I Sin[x])^9 Cos[x]^7 + 61 (I Sin[x])^5 Cos[x]^11 + 61 (I Sin[x])^11 Cos[x]^5 + 6 (I Sin[x])^3 Cos[x]^13 + 6 (I Sin[x])^13 Cos[x]^3) + Exp[11 I y] (44 (I Sin[x])^9 Cos[x]^7 + 44 (I Sin[x])^7 Cos[x]^9 + 12 (I Sin[x])^11 Cos[x]^5 + 12 (I Sin[x])^5 Cos[x]^11 + 22 (I Sin[x])^6 Cos[x]^10 + 22 (I Sin[x])^10 Cos[x]^6 + 50 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^4 Cos[x]^12) + Exp[13 I y] (4 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^9 Cos[x]^7 + 4 (I Sin[x])^7 Cos[x]^9 + 6 (I Sin[x])^8 Cos[x]^8 + 3 (I Sin[x])^6 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^6 + 1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4) + Exp[15 I y] (1 (I Sin[x])^10 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^10))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4) + Exp[-13 I y] (3 (I Sin[x])^5 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^5 + 1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^6 Cos[x]^10 + 5 (I Sin[x])^9 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^9 + 8 (I Sin[x])^8 Cos[x]^8) + Exp[-11 I y] (9 (I Sin[x])^3 Cos[x]^13 + 9 (I Sin[x])^13 Cos[x]^3 + 22 (I Sin[x])^5 Cos[x]^11 + 22 (I Sin[x])^11 Cos[x]^5 + 11 (I Sin[x])^4 Cos[x]^12 + 11 (I Sin[x])^12 Cos[x]^4 + 23 (I Sin[x])^6 Cos[x]^10 + 23 (I Sin[x])^10 Cos[x]^6 + 25 (I Sin[x])^7 Cos[x]^9 + 25 (I Sin[x])^9 Cos[x]^7 + 26 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^2 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^2) + Exp[-9 I y] (121 (I Sin[x])^6 Cos[x]^10 + 121 (I Sin[x])^10 Cos[x]^6 + 71 (I Sin[x])^5 Cos[x]^11 + 71 (I Sin[x])^11 Cos[x]^5 + 139 (I Sin[x])^9 Cos[x]^7 + 139 (I Sin[x])^7 Cos[x]^9 + 138 (I Sin[x])^8 Cos[x]^8 + 39 (I Sin[x])^12 Cos[x]^4 + 39 (I Sin[x])^4 Cos[x]^12 + 14 (I Sin[x])^13 Cos[x]^3 + 14 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^2 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^2) + Exp[-7 I y] (135 (I Sin[x])^4 Cos[x]^12 + 135 (I Sin[x])^12 Cos[x]^4 + 338 (I Sin[x])^6 Cos[x]^10 + 338 (I Sin[x])^10 Cos[x]^6 + 229 (I Sin[x])^5 Cos[x]^11 + 229 (I Sin[x])^11 Cos[x]^5 + 396 (I Sin[x])^7 Cos[x]^9 + 396 (I Sin[x])^9 Cos[x]^7 + 412 (I Sin[x])^8 Cos[x]^8 + 44 (I Sin[x])^3 Cos[x]^13 + 44 (I Sin[x])^13 Cos[x]^3 + 14 (I Sin[x])^2 Cos[x]^14 + 14 (I Sin[x])^14 Cos[x]^2 + 3 (I Sin[x])^1 Cos[x]^15 + 3 (I Sin[x])^15 Cos[x]^1) + Exp[-5 I y] (1023 (I Sin[x])^7 Cos[x]^9 + 1023 (I Sin[x])^9 Cos[x]^7 + 442 (I Sin[x])^11 Cos[x]^5 + 442 (I Sin[x])^5 Cos[x]^11 + 737 (I Sin[x])^6 Cos[x]^10 + 737 (I Sin[x])^10 Cos[x]^6 + 1142 (I Sin[x])^8 Cos[x]^8 + 174 (I Sin[x])^12 Cos[x]^4 + 174 (I Sin[x])^4 Cos[x]^12 + 46 (I Sin[x])^13 Cos[x]^3 + 46 (I Sin[x])^3 Cos[x]^13 + 9 (I Sin[x])^14 Cos[x]^2 + 9 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[-3 I y] (734 (I Sin[x])^5 Cos[x]^11 + 734 (I Sin[x])^11 Cos[x]^5 + 1647 (I Sin[x])^7 Cos[x]^9 + 1647 (I Sin[x])^9 Cos[x]^7 + 1208 (I Sin[x])^6 Cos[x]^10 + 1208 (I Sin[x])^10 Cos[x]^6 + 329 (I Sin[x])^4 Cos[x]^12 + 329 (I Sin[x])^12 Cos[x]^4 + 134 (I Sin[x])^3 Cos[x]^13 + 134 (I Sin[x])^13 Cos[x]^3 + 1828 (I Sin[x])^8 Cos[x]^8 + 33 (I Sin[x])^2 Cos[x]^14 + 33 (I Sin[x])^14 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^15 + 5 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[-1 I y] (2708 (I Sin[x])^8 Cos[x]^8 + 1591 (I Sin[x])^10 Cos[x]^6 + 1591 (I Sin[x])^6 Cos[x]^10 + 750 (I Sin[x])^5 Cos[x]^11 + 750 (I Sin[x])^11 Cos[x]^5 + 2375 (I Sin[x])^9 Cos[x]^7 + 2375 (I Sin[x])^7 Cos[x]^9 + 278 (I Sin[x])^12 Cos[x]^4 + 278 (I Sin[x])^4 Cos[x]^12 + 74 (I Sin[x])^13 Cos[x]^3 + 74 (I Sin[x])^3 Cos[x]^13 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^15 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^15) + Exp[1 I y] (407 (I Sin[x])^4 Cos[x]^12 + 407 (I Sin[x])^12 Cos[x]^4 + 1576 (I Sin[x])^6 Cos[x]^10 + 1576 (I Sin[x])^10 Cos[x]^6 + 2440 (I Sin[x])^8 Cos[x]^8 + 2194 (I Sin[x])^7 Cos[x]^9 + 2194 (I Sin[x])^9 Cos[x]^7 + 875 (I Sin[x])^5 Cos[x]^11 + 875 (I Sin[x])^11 Cos[x]^5 + 125 (I Sin[x])^3 Cos[x]^13 + 125 (I Sin[x])^13 Cos[x]^3 + 32 (I Sin[x])^2 Cos[x]^14 + 32 (I Sin[x])^14 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^15 + 6 (I Sin[x])^15 Cos[x]^1) + Exp[3 I y] (1907 (I Sin[x])^9 Cos[x]^7 + 1907 (I Sin[x])^7 Cos[x]^9 + 572 (I Sin[x])^11 Cos[x]^5 + 572 (I Sin[x])^5 Cos[x]^11 + 187 (I Sin[x])^4 Cos[x]^12 + 187 (I Sin[x])^12 Cos[x]^4 + 2232 (I Sin[x])^8 Cos[x]^8 + 1177 (I Sin[x])^6 Cos[x]^10 + 1177 (I Sin[x])^10 Cos[x]^6 + 41 (I Sin[x])^3 Cos[x]^13 + 41 (I Sin[x])^13 Cos[x]^3 + 5 (I Sin[x])^14 Cos[x]^2 + 5 (I Sin[x])^2 Cos[x]^14) + Exp[5 I y] (60 (I Sin[x])^3 Cos[x]^13 + 60 (I Sin[x])^13 Cos[x]^3 + 1011 (I Sin[x])^7 Cos[x]^9 + 1011 (I Sin[x])^9 Cos[x]^7 + 441 (I Sin[x])^5 Cos[x]^11 + 441 (I Sin[x])^11 Cos[x]^5 + 736 (I Sin[x])^6 Cos[x]^10 + 736 (I Sin[x])^10 Cos[x]^6 + 179 (I Sin[x])^4 Cos[x]^12 + 179 (I Sin[x])^12 Cos[x]^4 + 11 (I Sin[x])^2 Cos[x]^14 + 11 (I Sin[x])^14 Cos[x]^2 + 1130 (I Sin[x])^8 Cos[x]^8) + Exp[7 I y] (586 (I Sin[x])^8 Cos[x]^8 + 353 (I Sin[x])^10 Cos[x]^6 + 353 (I Sin[x])^6 Cos[x]^10 + 152 (I Sin[x])^5 Cos[x]^11 + 152 (I Sin[x])^11 Cos[x]^5 + 513 (I Sin[x])^7 Cos[x]^9 + 513 (I Sin[x])^9 Cos[x]^7 + 47 (I Sin[x])^4 Cos[x]^12 + 47 (I Sin[x])^12 Cos[x]^4 + 7 (I Sin[x])^13 Cos[x]^3 + 7 (I Sin[x])^3 Cos[x]^13) + Exp[9 I y] (29 (I Sin[x])^4 Cos[x]^12 + 29 (I Sin[x])^12 Cos[x]^4 + 164 (I Sin[x])^8 Cos[x]^8 + 120 (I Sin[x])^6 Cos[x]^10 + 120 (I Sin[x])^10 Cos[x]^6 + 157 (I Sin[x])^7 Cos[x]^9 + 157 (I Sin[x])^9 Cos[x]^7 + 61 (I Sin[x])^5 Cos[x]^11 + 61 (I Sin[x])^11 Cos[x]^5 + 6 (I Sin[x])^3 Cos[x]^13 + 6 (I Sin[x])^13 Cos[x]^3) + Exp[11 I y] (44 (I Sin[x])^9 Cos[x]^7 + 44 (I Sin[x])^7 Cos[x]^9 + 12 (I Sin[x])^11 Cos[x]^5 + 12 (I Sin[x])^5 Cos[x]^11 + 22 (I Sin[x])^6 Cos[x]^10 + 22 (I Sin[x])^10 Cos[x]^6 + 50 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^4 Cos[x]^12) + Exp[13 I y] (4 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^9 Cos[x]^7 + 4 (I Sin[x])^7 Cos[x]^9 + 6 (I Sin[x])^8 Cos[x]^8 + 3 (I Sin[x])^6 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^6 + 1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4) + Exp[15 I y] (1 (I Sin[x])^10 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^10));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":742.8666666667,"max_line_length":5350,"alphanum_fraction":0.5045319932} {"size":7531,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 14;\nname = \"14v4 2 3 2 3\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-13 I y] (1 (I Sin[x])^4 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^4) + Exp[-11 I y] (3 (I Sin[x])^5 Cos[x]^9 + 3 (I Sin[x])^9 Cos[x]^5 + 6 (I Sin[x])^6 Cos[x]^8 + 6 (I Sin[x])^8 Cos[x]^6 + 8 (I Sin[x])^7 Cos[x]^7) + Exp[-9 I y] (25 (I Sin[x])^5 Cos[x]^9 + 25 (I Sin[x])^9 Cos[x]^5 + 20 (I Sin[x])^6 Cos[x]^8 + 20 (I Sin[x])^8 Cos[x]^6 + 9 (I Sin[x])^3 Cos[x]^11 + 9 (I Sin[x])^11 Cos[x]^3 + 14 (I Sin[x])^4 Cos[x]^10 + 14 (I Sin[x])^10 Cos[x]^4 + 16 (I Sin[x])^7 Cos[x]^7 + 2 (I Sin[x])^2 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^2) + Exp[-7 I y] (117 (I Sin[x])^6 Cos[x]^8 + 117 (I Sin[x])^8 Cos[x]^6 + 29 (I Sin[x])^4 Cos[x]^10 + 29 (I Sin[x])^10 Cos[x]^4 + 67 (I Sin[x])^5 Cos[x]^9 + 67 (I Sin[x])^9 Cos[x]^5 + 136 (I Sin[x])^7 Cos[x]^7 + 5 (I Sin[x])^3 Cos[x]^11 + 5 (I Sin[x])^11 Cos[x]^3) + Exp[-5 I y] (118 (I Sin[x])^4 Cos[x]^10 + 118 (I Sin[x])^10 Cos[x]^4 + 220 (I Sin[x])^6 Cos[x]^8 + 220 (I Sin[x])^8 Cos[x]^6 + 161 (I Sin[x])^5 Cos[x]^9 + 161 (I Sin[x])^9 Cos[x]^5 + 59 (I Sin[x])^3 Cos[x]^11 + 59 (I Sin[x])^11 Cos[x]^3 + 244 (I Sin[x])^7 Cos[x]^7 + 26 (I Sin[x])^2 Cos[x]^12 + 26 (I Sin[x])^12 Cos[x]^2 + 8 (I Sin[x])^1 Cos[x]^13 + 8 (I Sin[x])^13 Cos[x]^1 + 1 Cos[x]^14 + 1 (I Sin[x])^14) + Exp[-3 I y] (320 (I Sin[x])^5 Cos[x]^9 + 320 (I Sin[x])^9 Cos[x]^5 + 524 (I Sin[x])^7 Cos[x]^7 + 456 (I Sin[x])^6 Cos[x]^8 + 456 (I Sin[x])^8 Cos[x]^6 + 162 (I Sin[x])^10 Cos[x]^4 + 162 (I Sin[x])^4 Cos[x]^10 + 67 (I Sin[x])^3 Cos[x]^11 + 67 (I Sin[x])^11 Cos[x]^3 + 18 (I Sin[x])^2 Cos[x]^12 + 18 (I Sin[x])^12 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^1) + Exp[-1 I y] (442 (I Sin[x])^5 Cos[x]^9 + 442 (I Sin[x])^9 Cos[x]^5 + 610 (I Sin[x])^7 Cos[x]^7 + 564 (I Sin[x])^6 Cos[x]^8 + 564 (I Sin[x])^8 Cos[x]^6 + 250 (I Sin[x])^4 Cos[x]^10 + 250 (I Sin[x])^10 Cos[x]^4 + 117 (I Sin[x])^3 Cos[x]^11 + 117 (I Sin[x])^11 Cos[x]^3 + 34 (I Sin[x])^2 Cos[x]^12 + 34 (I Sin[x])^12 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^1) + Exp[1 I y] (662 (I Sin[x])^6 Cos[x]^8 + 662 (I Sin[x])^8 Cos[x]^6 + 750 (I Sin[x])^7 Cos[x]^7 + 418 (I Sin[x])^9 Cos[x]^5 + 418 (I Sin[x])^5 Cos[x]^9 + 200 (I Sin[x])^4 Cos[x]^10 + 200 (I Sin[x])^10 Cos[x]^4 + 55 (I Sin[x])^3 Cos[x]^11 + 55 (I Sin[x])^11 Cos[x]^3 + 6 (I Sin[x])^2 Cos[x]^12 + 6 (I Sin[x])^12 Cos[x]^2) + Exp[3 I y] (488 (I Sin[x])^6 Cos[x]^8 + 488 (I Sin[x])^8 Cos[x]^6 + 158 (I Sin[x])^4 Cos[x]^10 + 158 (I Sin[x])^10 Cos[x]^4 + 310 (I Sin[x])^5 Cos[x]^9 + 310 (I Sin[x])^9 Cos[x]^5 + 562 (I Sin[x])^7 Cos[x]^7 + 45 (I Sin[x])^3 Cos[x]^11 + 45 (I Sin[x])^11 Cos[x]^3 + 5 (I Sin[x])^2 Cos[x]^12 + 5 (I Sin[x])^12 Cos[x]^2) + Exp[5 I y] (171 (I Sin[x])^5 Cos[x]^9 + 171 (I Sin[x])^9 Cos[x]^5 + 378 (I Sin[x])^7 Cos[x]^7 + 302 (I Sin[x])^6 Cos[x]^8 + 302 (I Sin[x])^8 Cos[x]^6 + 48 (I Sin[x])^10 Cos[x]^4 + 48 (I Sin[x])^4 Cos[x]^10 + 5 (I Sin[x])^11 Cos[x]^3 + 5 (I Sin[x])^3 Cos[x]^11) + Exp[7 I y] (73 (I Sin[x])^5 Cos[x]^9 + 73 (I Sin[x])^9 Cos[x]^5 + 142 (I Sin[x])^7 Cos[x]^7 + 120 (I Sin[x])^6 Cos[x]^8 + 120 (I Sin[x])^8 Cos[x]^6 + 20 (I Sin[x])^4 Cos[x]^10 + 20 (I Sin[x])^10 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^3) + Exp[9 I y] (41 (I Sin[x])^6 Cos[x]^8 + 41 (I Sin[x])^8 Cos[x]^6 + 50 (I Sin[x])^7 Cos[x]^7 + 11 (I Sin[x])^9 Cos[x]^5 + 11 (I Sin[x])^5 Cos[x]^9 + 1 (I Sin[x])^10 Cos[x]^4 + 1 (I Sin[x])^4 Cos[x]^10) + Exp[11 I y] (7 (I Sin[x])^6 Cos[x]^8 + 7 (I Sin[x])^8 Cos[x]^6 + 10 (I Sin[x])^7 Cos[x]^7 + 1 (I Sin[x])^5 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^5) + Exp[13 I y] (2 (I Sin[x])^7 Cos[x]^7))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-13 I y] (1 (I Sin[x])^4 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^4) + Exp[-11 I y] (3 (I Sin[x])^5 Cos[x]^9 + 3 (I Sin[x])^9 Cos[x]^5 + 6 (I Sin[x])^6 Cos[x]^8 + 6 (I Sin[x])^8 Cos[x]^6 + 8 (I Sin[x])^7 Cos[x]^7) + Exp[-9 I y] (25 (I Sin[x])^5 Cos[x]^9 + 25 (I Sin[x])^9 Cos[x]^5 + 20 (I Sin[x])^6 Cos[x]^8 + 20 (I Sin[x])^8 Cos[x]^6 + 9 (I Sin[x])^3 Cos[x]^11 + 9 (I Sin[x])^11 Cos[x]^3 + 14 (I Sin[x])^4 Cos[x]^10 + 14 (I Sin[x])^10 Cos[x]^4 + 16 (I Sin[x])^7 Cos[x]^7 + 2 (I Sin[x])^2 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^2) + Exp[-7 I y] (117 (I Sin[x])^6 Cos[x]^8 + 117 (I Sin[x])^8 Cos[x]^6 + 29 (I Sin[x])^4 Cos[x]^10 + 29 (I Sin[x])^10 Cos[x]^4 + 67 (I Sin[x])^5 Cos[x]^9 + 67 (I Sin[x])^9 Cos[x]^5 + 136 (I Sin[x])^7 Cos[x]^7 + 5 (I Sin[x])^3 Cos[x]^11 + 5 (I Sin[x])^11 Cos[x]^3) + Exp[-5 I y] (118 (I Sin[x])^4 Cos[x]^10 + 118 (I Sin[x])^10 Cos[x]^4 + 220 (I Sin[x])^6 Cos[x]^8 + 220 (I Sin[x])^8 Cos[x]^6 + 161 (I Sin[x])^5 Cos[x]^9 + 161 (I Sin[x])^9 Cos[x]^5 + 59 (I Sin[x])^3 Cos[x]^11 + 59 (I Sin[x])^11 Cos[x]^3 + 244 (I Sin[x])^7 Cos[x]^7 + 26 (I Sin[x])^2 Cos[x]^12 + 26 (I Sin[x])^12 Cos[x]^2 + 8 (I Sin[x])^1 Cos[x]^13 + 8 (I Sin[x])^13 Cos[x]^1 + 1 Cos[x]^14 + 1 (I Sin[x])^14) + Exp[-3 I y] (320 (I Sin[x])^5 Cos[x]^9 + 320 (I Sin[x])^9 Cos[x]^5 + 524 (I Sin[x])^7 Cos[x]^7 + 456 (I Sin[x])^6 Cos[x]^8 + 456 (I Sin[x])^8 Cos[x]^6 + 162 (I Sin[x])^10 Cos[x]^4 + 162 (I Sin[x])^4 Cos[x]^10 + 67 (I Sin[x])^3 Cos[x]^11 + 67 (I Sin[x])^11 Cos[x]^3 + 18 (I Sin[x])^2 Cos[x]^12 + 18 (I Sin[x])^12 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^1) + Exp[-1 I y] (442 (I Sin[x])^5 Cos[x]^9 + 442 (I Sin[x])^9 Cos[x]^5 + 610 (I Sin[x])^7 Cos[x]^7 + 564 (I Sin[x])^6 Cos[x]^8 + 564 (I Sin[x])^8 Cos[x]^6 + 250 (I Sin[x])^4 Cos[x]^10 + 250 (I Sin[x])^10 Cos[x]^4 + 117 (I Sin[x])^3 Cos[x]^11 + 117 (I Sin[x])^11 Cos[x]^3 + 34 (I Sin[x])^2 Cos[x]^12 + 34 (I Sin[x])^12 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^1) + Exp[1 I y] (662 (I Sin[x])^6 Cos[x]^8 + 662 (I Sin[x])^8 Cos[x]^6 + 750 (I Sin[x])^7 Cos[x]^7 + 418 (I Sin[x])^9 Cos[x]^5 + 418 (I Sin[x])^5 Cos[x]^9 + 200 (I Sin[x])^4 Cos[x]^10 + 200 (I Sin[x])^10 Cos[x]^4 + 55 (I Sin[x])^3 Cos[x]^11 + 55 (I Sin[x])^11 Cos[x]^3 + 6 (I Sin[x])^2 Cos[x]^12 + 6 (I Sin[x])^12 Cos[x]^2) + Exp[3 I y] (488 (I Sin[x])^6 Cos[x]^8 + 488 (I Sin[x])^8 Cos[x]^6 + 158 (I Sin[x])^4 Cos[x]^10 + 158 (I Sin[x])^10 Cos[x]^4 + 310 (I Sin[x])^5 Cos[x]^9 + 310 (I Sin[x])^9 Cos[x]^5 + 562 (I Sin[x])^7 Cos[x]^7 + 45 (I Sin[x])^3 Cos[x]^11 + 45 (I Sin[x])^11 Cos[x]^3 + 5 (I Sin[x])^2 Cos[x]^12 + 5 (I Sin[x])^12 Cos[x]^2) + Exp[5 I y] (171 (I Sin[x])^5 Cos[x]^9 + 171 (I Sin[x])^9 Cos[x]^5 + 378 (I Sin[x])^7 Cos[x]^7 + 302 (I Sin[x])^6 Cos[x]^8 + 302 (I Sin[x])^8 Cos[x]^6 + 48 (I Sin[x])^10 Cos[x]^4 + 48 (I Sin[x])^4 Cos[x]^10 + 5 (I Sin[x])^11 Cos[x]^3 + 5 (I Sin[x])^3 Cos[x]^11) + Exp[7 I y] (73 (I Sin[x])^5 Cos[x]^9 + 73 (I Sin[x])^9 Cos[x]^5 + 142 (I Sin[x])^7 Cos[x]^7 + 120 (I Sin[x])^6 Cos[x]^8 + 120 (I Sin[x])^8 Cos[x]^6 + 20 (I Sin[x])^4 Cos[x]^10 + 20 (I Sin[x])^10 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^3) + Exp[9 I y] (41 (I Sin[x])^6 Cos[x]^8 + 41 (I Sin[x])^8 Cos[x]^6 + 50 (I Sin[x])^7 Cos[x]^7 + 11 (I Sin[x])^9 Cos[x]^5 + 11 (I Sin[x])^5 Cos[x]^9 + 1 (I Sin[x])^10 Cos[x]^4 + 1 (I Sin[x])^4 Cos[x]^10) + Exp[11 I y] (7 (I Sin[x])^6 Cos[x]^8 + 7 (I Sin[x])^8 Cos[x]^6 + 10 (I Sin[x])^7 Cos[x]^7 + 1 (I Sin[x])^5 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^5) + Exp[13 I y] (2 (I Sin[x])^7 Cos[x]^7));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":502.0666666667,"max_line_length":3546,"alphanum_fraction":0.4979418404} {"size":10869,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 16;\nname = \"16v2 2 2 1 5 2 1 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^6 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^6) + Exp[-13 I y] (3 (I Sin[x])^5 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^5 + 5 (I Sin[x])^9 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^9 + 3 (I Sin[x])^6 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^6 + 6 (I Sin[x])^8 Cos[x]^8 + 1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4) + Exp[-11 I y] (39 (I Sin[x])^7 Cos[x]^9 + 39 (I Sin[x])^9 Cos[x]^7 + 17 (I Sin[x])^5 Cos[x]^11 + 17 (I Sin[x])^11 Cos[x]^5 + 30 (I Sin[x])^6 Cos[x]^10 + 30 (I Sin[x])^10 Cos[x]^6 + 3 (I Sin[x])^4 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^4 + 32 (I Sin[x])^8 Cos[x]^8) + Exp[-9 I y] (33 (I Sin[x])^4 Cos[x]^12 + 33 (I Sin[x])^12 Cos[x]^4 + 117 (I Sin[x])^10 Cos[x]^6 + 117 (I Sin[x])^6 Cos[x]^10 + 68 (I Sin[x])^5 Cos[x]^11 + 68 (I Sin[x])^11 Cos[x]^5 + 146 (I Sin[x])^9 Cos[x]^7 + 146 (I Sin[x])^7 Cos[x]^9 + 10 (I Sin[x])^3 Cos[x]^13 + 10 (I Sin[x])^13 Cos[x]^3 + 160 (I Sin[x])^8 Cos[x]^8 + 1 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^2) + Exp[-7 I y] (326 (I Sin[x])^6 Cos[x]^10 + 326 (I Sin[x])^10 Cos[x]^6 + 602 (I Sin[x])^8 Cos[x]^8 + 494 (I Sin[x])^7 Cos[x]^9 + 494 (I Sin[x])^9 Cos[x]^7 + 164 (I Sin[x])^5 Cos[x]^11 + 164 (I Sin[x])^11 Cos[x]^5 + 65 (I Sin[x])^4 Cos[x]^12 + 65 (I Sin[x])^12 Cos[x]^4 + 14 (I Sin[x])^3 Cos[x]^13 + 14 (I Sin[x])^13 Cos[x]^3 + 1 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^2) + Exp[-5 I y] (426 (I Sin[x])^5 Cos[x]^11 + 426 (I Sin[x])^11 Cos[x]^5 + 1015 (I Sin[x])^9 Cos[x]^7 + 1015 (I Sin[x])^7 Cos[x]^9 + 723 (I Sin[x])^6 Cos[x]^10 + 723 (I Sin[x])^10 Cos[x]^6 + 1116 (I Sin[x])^8 Cos[x]^8 + 192 (I Sin[x])^4 Cos[x]^12 + 192 (I Sin[x])^12 Cos[x]^4 + 69 (I Sin[x])^3 Cos[x]^13 + 69 (I Sin[x])^13 Cos[x]^3 + 18 (I Sin[x])^2 Cos[x]^14 + 18 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[-3 I y] (1830 (I Sin[x])^7 Cos[x]^9 + 1830 (I Sin[x])^9 Cos[x]^7 + 621 (I Sin[x])^5 Cos[x]^11 + 621 (I Sin[x])^11 Cos[x]^5 + 2026 (I Sin[x])^8 Cos[x]^8 + 1227 (I Sin[x])^6 Cos[x]^10 + 1227 (I Sin[x])^10 Cos[x]^6 + 232 (I Sin[x])^4 Cos[x]^12 + 232 (I Sin[x])^12 Cos[x]^4 + 68 (I Sin[x])^13 Cos[x]^3 + 68 (I Sin[x])^3 Cos[x]^13 + 13 (I Sin[x])^14 Cos[x]^2 + 13 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[-1 I y] (1578 (I Sin[x])^6 Cos[x]^10 + 1578 (I Sin[x])^10 Cos[x]^6 + 2336 (I Sin[x])^8 Cos[x]^8 + 2093 (I Sin[x])^7 Cos[x]^9 + 2093 (I Sin[x])^9 Cos[x]^7 + 940 (I Sin[x])^5 Cos[x]^11 + 940 (I Sin[x])^11 Cos[x]^5 + 446 (I Sin[x])^4 Cos[x]^12 + 446 (I Sin[x])^12 Cos[x]^4 + 158 (I Sin[x])^3 Cos[x]^13 + 158 (I Sin[x])^13 Cos[x]^3 + 42 (I Sin[x])^2 Cos[x]^14 + 42 (I Sin[x])^14 Cos[x]^2 + 9 (I Sin[x])^1 Cos[x]^15 + 9 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[1 I y] (2704 (I Sin[x])^8 Cos[x]^8 + 1572 (I Sin[x])^6 Cos[x]^10 + 1572 (I Sin[x])^10 Cos[x]^6 + 2321 (I Sin[x])^9 Cos[x]^7 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Cos[x]^12 + 1 (I Sin[x])^13 Cos[x]^3 + 1 (I Sin[x])^3 Cos[x]^13) + Exp[11 I y] (45 (I Sin[x])^7 Cos[x]^9 + 45 (I Sin[x])^9 Cos[x]^7 + 11 (I Sin[x])^5 Cos[x]^11 + 11 (I Sin[x])^11 Cos[x]^5 + 27 (I Sin[x])^6 Cos[x]^10 + 27 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^4 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^4 + 40 (I Sin[x])^8 Cos[x]^8) + Exp[13 I y] (7 (I Sin[x])^7 Cos[x]^9 + 7 (I Sin[x])^9 Cos[x]^7 + 1 (I Sin[x])^11 Cos[x]^5 + 1 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^10 Cos[x]^6 + 4 (I Sin[x])^6 Cos[x]^10 + 6 (I Sin[x])^8 Cos[x]^8) + Exp[15 I y] (2 (I Sin[x])^8 Cos[x]^8));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 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TRACKS (Y coordinates)\r\nsubjID,stim,order,condition,resp_1,resp_2,response,error,resp_num,RT,init time,distractor,ideal y-int,maxdev,real time,comments,timestamps,\r\n011,instruct.jpg,1,instruct,,,,0,,0,0,,0,0,12:55:52,,101,\r\n011,blank.jpg,2,inCongiMNL712,~8-.jpg,~1+.jpg,~1+.jpg,0,2,1719,78,1,0,0,12:56:19,,101,0.05,0.05,0.05,0.05,0.0766,0.0766,0.0766,0.0781,0.0781,0.0781,0.0781,0.0781,0.0781,0.0781,0.0781,0.0781,0.0781,0.0781,0.0781,0.0781,0.0781,0.0781,0.0781,0.0781,0.0781,0.0781,0.0781,0.0797,0.0797,0.1062,0.1062,0.1844,0.2438,0.2438,0.3297,0.3297,0.3672,0.4266,0.4609,0.5141,0.5516,0.6,0.6312,0.6766,0.7,0.7234,0.7234,0.7594,0.7594,0.8094,0.8094,0.8328,0.8609,0.8797,0.9016,0.9109,0.9234,0.9297,0.9375,0.9469,0.9531,0.9531,0.9797,0.9797,1.0078,1.0359,1.0797,1.1125,1.1594,1.2047,1.2344,1.2484,1.2703,1.2797,1.2938,1.2938,1.3141,1.3141,1.3172,1.325,1.325,1.3297,1.3359,1.3453,1.3484,1.3562,1.3609,1.3734,1.3812,1.3922,1.4016,1.4141,1.4234,1.4234,1.4312,1.4312,1.4375,1.4375,1.4375,1.4375,1.4375,1.4375,1.4375,1.4375,1.4391,1.4391,1.4391,1.4391,1.4391,1.4391,\r\n011,blank.jpg,3,CongMNL792,~2-.jpg,~9+.jpg,~9+.jpg,0,2,1266,219,1,0,0,12:56:22,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0641,0.0641,0.0688,0.0828,0.0828,0.0984,0.1625,0.1625,0.2188,0.2562,0.3109,0.3469,0.3953,0.4297,0.475,0.475,0.5578,0.5578,0.6375,0.6375,0.6938,0.6938,0.7172,0.75,0.7656,0.7812,0.7906,0.8094,0.8234,0.8453,0.8453,0.8938,0.8938,0.9594,0.9594,0.9875,1.0312,1.0609,1.1031,1.1328,1.1719,1.2047,1.2438,1.2703,1.3109,1.3375,1.375,1.3953,1.3953,1.4234,1.4234,1.4328,1.4469,1.4578,1.4609,1.4641,1.4656,1.4656,1.4672,1.4672,1.4672,1.4672,1.4672,1.4672,1.4672,1.4672,1.4672,1.4672,\r\n011,blank.jpg,4,CongiMNL711,~8+.jpg,~1-.jpg,~8+.jpg,0,1,1328,156,2,0,0,12:56:25,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0875,0.0891,0.0891,0.0891,0.0891,0.0891,0.0891,0.0891,0.0891,0.0891,0.0891,0.1125,0.1125,0.1406,0.2188,0.2188,0.2609,0.3,0.3859,0.4531,0.5719,0.6625,0.7953,0.9031,1.0047,1.0047,1.1156,1.1469,1.1469,1.1719,1.1844,1.1922,1.1969,1.2016,1.2031,1.2062,1.2094,1.2156,1.2234,1.2406,1.2547,1.2547,1.2859,1.2859,1.3156,1.3156,1.3312,1.3422,1.3484,1.3547,1.3578,1.3656,1.3719,1.3812,1.3922,1.4094,1.4094,1.4406,1.4406,1.4516,1.4562,1.4562,1.4562,1.4562,1.4547,1.4547,1.4547,1.4547,1.4547,1.4547,1.4547,1.4547,1.4547,1.4547,1.4547,1.4547,\r\n011,blank.jpg,5,CongMNL6non2,~2-.jpg,~8+.jpg,~8+.jpg,0,2,1297,265,1,0,0,12:56:28,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0578,0.075,0.075,0.1438,0.1438,0.2031,0.2547,0.3344,0.3844,0.4641,0.5219,0.6047,0.6594,0.6594,0.75,0.75,0.8266,0.8266,0.8719,0.9031,0.9484,0.975,1.0094,1.0266,1.0531,1.0766,1.0953,1.1141,1.1266,1.1266,1.1547,1.1547,1.1641,1.1922,1.1922,1.2094,1.225,1.2391,1.2562,1.2641,1.2766,1.2859,1.2938,1.3,1.3078,1.3078,1.3203,1.3203,1.3344,1.3344,1.3422,1.3594,1.3719,1.3859,1.3938,1.4047,1.4125,1.4219,1.4297,1.4344,1.4344,1.4344,1.4344,1.4344,1.4344,1.4344,1.4375,\r\n011,blank.jpg,6,CongMNL81_92,~1-.jpg,~9+.jpg,~9+.jpg,0,2,1343,297,1,0,0,12:56:30,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0531,0.0531,0.0953,0.0953,0.1391,0.1766,0.2562,0.3109,0.3797,0.4172,0.4766,0.5141,0.5641,0.6,0.6531,0.6875,0.6875,0.7656,0.7656,0.8,0.8219,0.85,0.8688,0.8969,0.9156,0.9391,0.9547,0.9797,0.9953,1.0219,1.0391,1.0391,1.0562,1.0766,1.0922,1.1094,1.1312,1.1484,1.1766,1.1922,1.2172,1.2359,1.2562,1.2797,1.2953,1.2953,1.3141,1.3391,1.3391,1.3469,1.3578,1.3641,1.3734,1.3812,1.3906,1.3984,1.4078,1.4109,1.4141,1.4141,1.4156,1.4156,1.4156,1.4156,1.4156,1.4172,1.4172,\r\n011,blank.jpg,7,inCongiMNL792,~9-.jpg,~2+.jpg,~2+.jpg,0,2,1219,156,1,0,0,12:56:33,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0453,0.0484,0.0578,0.0734,0.0875,0.1141,0.1328,0.1328,0.2125,0.25,0.25,0.3391,0.3391,0.3953,0.4281,0.4797,0.5375,0.5672,0.6172,0.6469,0.6734,0.6953,0.7047,0.725,0.7422,0.7641,0.7641,0.7781,0.7938,0.8156,0.8547,0.8859,0.925,0.9547,1.0047,1.0391,1.0859,1.0859,1.1578,1.1578,1.2328,1.2641,1.2641,1.3062,1.3375,1.3703,1.3922,1.4188,1.4344,1.4562,1.4672,1.475,1.475,1.4781,1.4781,1.4766,1.4766,1.4703,1.4703,1.4672,1.4641,1.4641,1.4641,1.4641,1.4641,1.4641,1.4625,1.4625,1.4625,\r\n011,blank.jpg,8,inCongiMNL6non2,~8-.jpg,~2+.jpg,~2+.jpg,0,2,1469,188,1,0,0,12:56:35,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0219,0.025,0.0266,0.0297,0.0297,0.0344,0.0344,0.0375,0.0375,0.0375,0.0375,0.0375,0.0406,0.0453,0.0531,0.0688,0.1203,0.1594,0.2188,0.2656,0.3531,0.4094,0.4938,0.5453,0.5453,0.6594,0.7172,0.7172,0.8,0.8,0.8328,0.8609,0.8734,0.8922,0.9,0.9125,0.9203,0.9266,0.9328,0.9422,0.9422,0.9625,0.9625,0.9922,0.9922,1.0125,1.0297,1.0516,1.0766,1.0922,1.1172,1.1328,1.1578,1.1719,1.1938,1.1938,1.2578,1.2578,1.2891,1.3062,1.3312,1.3469,1.3703,1.3859,1.4125,1.4312,1.4484,1.4578,1.4625,1.4625,1.4625,1.4625,1.4625,1.4625,1.4625,1.4594,1.4562,1.4547,1.4547,1.4547,1.4547,1.4531,1.4547,\r\n011,blank.jpg,9,inCongMNL711,~1+.jpg,~8-.jpg,~1+.jpg,0,1,1422,234,2,0,0,12:56:37,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0609,0.0609,0.0656,0.0734,0.0828,0.1016,0.125,0.1484,0.1766,0.1969,0.2266,0.2469,0.2469,0.3016,0.3016,0.3375,0.3656,0.4203,0.4641,0.5297,0.5797,0.65,0.6844,0.7328,0.7625,0.7625,0.8359,0.8359,0.8922,0.9156,0.9156,0.9344,0.9344,0.9406,0.9516,0.9625,0.9812,0.9938,1.0156,1.0281,1.05,1.0656,1.0656,1.0797,1.1156,1.1156,1.1297,1.1516,1.1688,1.1953,1.2141,1.2422,1.2625,1.2875,1.3078,1.3219,1.3422,1.3422,1.3672,1.3672,1.3766,1.3844,1.3891,1.3906,1.3906,1.3906,1.3906,1.3922,1.3984,1.4016,1.4031,1.4031,1.4047,1.4047,1.4047,1.4047,1.4078,\r\n011,blank.jpg,10,CongiMNL81_91,~9+.jpg,~1-.jpg,~9+.jpg,0,1,1781,266,2,0,0,12:56:40,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0625,0.0609,0.0609,0.0609,0.0609,0.0891,0.0891,0.1281,0.1562,0.1922,0.2531,0.2969,0.3484,0.3828,0.4359,0.4781,0.5422,0.5875,0.5875,0.6844,0.6844,0.7234,0.7734,0.7734,0.7953,0.8172,0.8328,0.8547,0.8688,0.8906,0.9031,0.9234,0.9344,0.9656,0.9656,0.9984,1.0859,1.0859,1.1422,1.1797,1.2312,1.2578,1.3031,1.3344,1.3719,1.3938,1.4156,1.4266,1.4312,1.4328,1.4328,1.4375,1.4391,1.4391,1.4406,1.4422,1.4438,1.4453,1.4453,1.4453,1.4438,1.4406,1.4406,1.4406,1.4406,1.4406,1.4406,1.4375,1.4375,1.4375,1.4375,1.4359,1.4328,1.4328,1.4328,1.4328,1.4328,1.4328,1.4328,1.4328,1.4328,1.4328,1.4328,1.4328,1.4328,1.4328,1.4328,1.4328,1.4328,1.4328,1.4328,1.4344,1.4344,1.4359,1.4375,1.4375,1.4375,1.4375,\r\n011,blank.jpg,11,CongiMNL111,~2+.jpg,~1-.jpg,~2+.jpg,0,1,1250,156,2,0,0,12:56:44,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0703,0.0719,0.0734,0.075,0.0766,0.0766,0.0797,0.0797,0.0797,0.0812,0.0859,0.0859,0.1109,0.1109,0.1797,0.1797,0.2266,0.2578,0.3172,0.3656,0.4422,0.4969,0.5672,0.5672,0.6094,0.7031,0.7031,0.7562,0.8484,0.8484,0.8812,0.9469,0.9469,0.9828,1.0078,1.0406,1.0625,1.0953,1.1172,1.15,1.15,1.2094,1.2094,1.2453,1.2453,1.2594,1.2812,1.2922,1.3125,1.3234,1.3391,1.35,1.3609,1.3719,1.3797,1.3859,1.3859,1.4,1.4,1.4062,1.4109,1.4156,1.4172,1.4172,1.4188,1.4172,1.4172,1.4172,1.4172,1.4172,\r\n011,blank.jpg,12,CongMNL192,~8-.jpg,~9+.jpg,~9+.jpg,0,2,1109,265,1,0,0,12:56:47,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0531,0.0594,0.0719,0.1062,0.1547,0.2219,0.275,0.275,0.4484,0.4484,0.6172,0.6172,0.7016,0.7547,0.8281,0.8828,0.925,0.9859,1.0219,1.0797,1.1125,1.1641,1.1641,1.2078,1.2656,1.2656,1.3,1.3,1.3125,1.3203,1.3266,1.3328,1.3438,1.3484,1.3562,1.3594,1.3625,1.3656,1.3656,1.3812,1.3812,1.3906,1.3984,1.4078,1.4156,1.4219,1.425,1.425,1.425,1.425,1.425,1.425,1.425,\r\n011,blank.jpg,13,inCongiMNL112,~2-.jpg,~1+.jpg,~1+.jpg,0,2,1500,47,1,0,0,12:56:49,,101,0.05,0.05,0.0156,0.0172,0.0188,0.0203,0.0203,0.0406,0.0406,0.0641,0.0828,0.1156,0.1406,0.1797,0.2062,0.2516,0.2797,0.325,0.35,0.35,0.3891,0.4547,0.4547,0.4844,0.525,0.5594,0.5875,0.6312,0.6578,0.6953,0.7172,0.7609,0.8062,0.8062,0.8938,0.8938,0.9578,0.9578,0.9797,1,1.0344,1.0547,1.0844,1.1109,1.15,1.1766,1.2125,1.2266,1.2266,1.2703,1.2703,1.2984,1.3469,1.3469,1.3719,1.4062,1.4281,1.4625,1.4828,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.4984,1.4953,1.4906,1.4844,1.475,1.4703,1.4625,1.4547,1.4469,1.4406,1.4312,1.4266,1.4219,1.4219,1.4203,1.4203,1.4203,1.4203,1.4203,1.4203,1.4203,1.4203,1.4203,1.4203,1.4203,\r\n011,blank.jpg,14,inCongMNL191,~8+.jpg,~9-.jpg,~8+.jpg,0,1,1250,31,2,0,0,12:56:51,,101,0.0453,0.05,0.0531,0.0578,0.0625,0.0703,0.0766,0.0922,0.1062,0.1281,0.1281,0.1688,0.1984,0.1984,0.2219,0.2609,0.3375,0.3375,0.3703,0.4078,0.4344,0.4734,0.5078,0.5531,0.5859,0.5859,0.6375,0.7281,0.7281,0.7625,0.8453,0.8453,0.8922,0.925,0.9828,1.0266,1.0828,1.1219,1.1828,1.225,1.2875,1.2875,1.3656,1.3922,1.3922,1.4312,1.4578,1.4844,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.4953,1.4859,1.4859,1.475,1.4672,1.4609,1.4531,1.4484,1.4469,1.4469,1.4469,1.4469,1.4469,1.4469,1.4469,1.4469,1.4469,1.4469,1.4469,1.4469,\r\n011,blank.jpg,15,CongiMNL6non1,~8+.jpg,~2-.jpg,~8+.jpg,0,1,1453,328,2,0,0,12:56:54,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0703,0.0703,0.0953,0.1281,0.1797,0.2156,0.2688,0.3109,0.3656,0.4062,0.475,0.5328,0.5328,0.6328,0.6328,0.6875,0.7234,0.775,0.8094,0.8547,0.8844,0.9266,0.9578,1,1.0328,1.0328,1.0906,1.0906,1.1344,1.1547,1.1547,1.1969,1.1969,1.2125,1.2328,1.2469,1.2688,1.2828,1.3047,1.3188,1.3375,1.35,1.35,1.3625,1.3891,1.3891,1.4,1.4109,1.4234,1.4328,1.4375,1.4438,1.4469,1.4484,1.4484,1.4484,1.4484,1.4484,1.4469,1.4469,1.4469,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,\r\n011,blank.jpg,16,inCongiMNL81_92,~9-.jpg,~1+.jpg,~1+.jpg,0,2,1218,62,1,0,0,12:56:57,,101,0.05,0.05,0.05,0.0547,0.0531,0.0531,0.0531,0.0531,0.0531,0.0531,0.0531,0.0547,0.0578,0.0641,0.0719,0.0766,0.0906,0.1078,0.1375,0.1641,0.1641,0.2125,0.2984,0.2984,0.3344,0.3891,0.4453,0.4906,0.5719,0.6219,0.6969,0.7422,0.8125,0.8797,0.9281,0.9938,0.9938,1.0828,1.0828,1.1359,1.1734,1.2188,1.2516,1.2906,1.3125,1.3391,1.3594,1.3812,1.3984,1.3984,1.4344,1.4344,1.4578,1.4578,1.4766,1.4766,1.4844,1.4875,1.4875,1.4875,1.4859,1.4828,1.4797,1.4781,1.4734,1.4703,1.4703,1.4656,1.4656,1.4641,1.4641,1.4625,1.4578,1.4562,1.4562,1.45,1.4469,1.4438,\r\n011,blank.jpg,17,inCongMNL111,~1+.jpg,~2-.jpg,~1+.jpg,0,1,1156,78,2,0,0,12:56:59,,101,0.05,0.05,0.05,0.05,0.0391,0.0391,0.0391,0.0406,0.0469,0.0594,0.0797,0.0797,0.1656,0.1656,0.2656,0.3031,0.3031,0.3188,0.3531,0.3766,0.4125,0.4391,0.4859,0.5172,0.5719,0.6188,0.6188,0.6922,0.6922,0.7672,0.7672,0.8406,0.8672,0.8672,0.8844,0.9125,0.9328,0.9719,0.9969,1.0203,1.0406,1.0672,1.0859,1.1156,1.1156,1.1688,1.1922,1.1922,1.2391,1.2391,1.2656,1.2797,1.2969,1.3094,1.3234,1.3328,1.3469,1.3562,1.3688,1.3688,1.3844,1.3844,1.3922,1.3922,1.3984,1.4031,1.4078,1.4078,1.4094,1.4094,1.4094,1.4094,1.4094,\r\n011,blank.jpg,18,inCongiMNL192,~9-.jpg,~8+.jpg,~8+.jpg,0,2,1109,47,1,0,0,12:57:02,,101,0.05,0.05,0.0594,0.0594,0.0609,0.0625,0.0625,0.0625,0.0641,0.0672,0.0703,0.0766,0.0766,0.0938,0.0938,0.1062,0.1547,0.1547,0.1922,0.225,0.2594,0.3359,0.3969,0.4844,0.5438,0.6219,0.6703,0.75,0.8109,0.8109,0.9062,0.9062,0.9484,0.9844,1.0328,1.0656,1.1078,1.1344,1.1688,1.1875,1.2156,1.2281,1.2281,1.2578,1.2578,1.275,1.2797,1.2797,1.2828,1.2859,1.2891,1.2938,1.3016,1.3094,1.3203,1.3359,1.35,1.3625,1.3703,1.3797,1.3797,1.3938,1.3938,1.4016,1.4016,1.4016,1.4016,1.4016,1.4016,1.4016,1.4016,\r\n011,blank.jpg,19,inCongMNL6non1,~2+.jpg,~8-.jpg,~2+.jpg,0,1,1047,32,2,0,0,12:57:04,,101,0.0406,0.0438,0.0453,0.0453,0.0469,0.0484,0.05,0.05,0.0578,0.0578,0.0797,0.0797,0.0922,0.1203,0.1453,0.1891,0.2188,0.25,0.2656,0.2953,0.3219,0.3688,0.3969,0.4422,0.4422,0.4734,0.5203,0.5562,0.6172,0.6594,0.7219,0.7672,0.8297,0.8641,0.9172,0.9578,0.9578,1.0422,1.0422,1.0953,1.1812,1.1812,1.2109,1.2469,1.2641,1.2891,1.3047,1.3266,1.3422,1.3578,1.3578,1.3766,1.3766,1.3938,1.3938,1.4062,1.4062,1.4094,1.4141,1.4172,1.4188,1.4203,1.4203,1.4219,1.4219,1.4219,1.4219,\r\n011,blank.jpg,20,CongiMNL791,~9+.jpg,~2-.jpg,~9+.jpg,0,1,1140,109,2,0,0,12:57:06,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.0578,0.0578,0.0703,0.0703,0.0875,0.1031,0.1344,0.1641,0.2078,0.2375,0.2891,0.3219,0.3828,0.4266,0.4266,0.55,0.55,0.5859,0.6891,0.6891,0.7312,0.7969,0.8391,0.9016,0.9359,0.9891,1.0234,1.075,1.075,1.1531,1.1531,1.2375,1.2375,1.3109,1.3109,1.3484,1.3734,1.4062,1.4297,1.4422,1.4547,1.4656,1.4734,1.4859,1.4922,1.4953,1.4953,1.4953,1.4969,1.4969,1.4969,1.4969,1.4953,1.4938,1.4875,1.4844,1.4766,1.4719,1.4672,1.4641,1.4625,1.4625,1.4625,1.4594,1.4594,1.4594,1.4594,\r\n011,blank.jpg,21,inCongMNL81_91,~1+.jpg,~9-.jpg,~1+.jpg,0,1,1281,94,2,0,0,12:57:08,,101,0.05,0.05,0.05,0.05,0.05,0.0688,0.0688,0.0766,0.0844,0.0844,0.0875,0.0922,0.0953,0.0984,0.1062,0.1203,0.1297,0.1562,0.1922,0.2234,0.2531,0.2531,0.2797,0.3578,0.3578,0.4078,0.5125,0.5125,0.5656,0.6016,0.6516,0.6938,0.7328,0.7891,0.8266,0.8766,0.9031,0.9031,0.9531,0.9531,0.9969,0.9969,1.0219,1.05,1.0906,1.1156,1.1531,1.1812,1.2078,1.2266,1.25,1.2672,1.2672,1.3078,1.3078,1.3391,1.3391,1.3516,1.3578,1.3656,1.3688,1.3719,1.375,1.3766,1.3797,1.3812,1.3828,1.3844,1.3844,1.3875,1.3875,1.3906,1.3906,1.3906,1.3906,1.3906,1.3906,1.3922,1.3922,1.3922,1.3922,1.3922,\r\n011,blank.jpg,22,CongMNL712,~1-.jpg,~8+.jpg,~8+.jpg,0,2,1391,172,1,0,0,12:57:10,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0672,0.0703,0.0719,0.075,0.0781,0.0875,0.1141,0.1484,0.1484,0.2188,0.2188,0.2672,0.2672,0.3016,0.3797,0.4375,0.5062,0.5531,0.6359,0.6844,0.7484,0.7484,0.8438,0.8438,0.8766,0.9453,0.9453,0.9969,0.9969,1.0219,1.0359,1.0516,1.0688,1.0906,1.1062,1.1312,1.1312,1.1734,1.1891,1.1891,1.2188,1.2188,1.2391,1.2562,1.275,1.2875,1.2953,1.3094,1.3156,1.3234,1.3281,1.3328,1.3328,1.3453,1.3453,1.3562,1.3609,1.3609,1.3656,1.3703,1.375,1.3781,1.3828,1.3859,1.3953,1.3984,1.4,1.4062,1.4125,1.4125,1.4172,1.4281,1.4281,1.4328,1.4328,1.4328,1.4328,1.4328,1.4344,\r\n011,blank.jpg,23,CongiMNL191,~9+.jpg,~8-.jpg,~9+.jpg,0,1,1187,109,2,0,0,12:57:13,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.0453,0.0453,0.0547,0.0547,0.0578,0.0656,0.0844,0.1016,0.1312,0.1531,0.1969,0.2297,0.3078,0.3781,0.4906,0.4906,0.6344,0.6344,0.7547,0.7547,0.8797,0.8797,0.9734,1.0203,1.0859,1.1406,1.175,1.2266,1.2625,1.3109,1.3391,1.3812,1.3812,1.4266,1.4266,1.4594,1.4594,1.4766,1.4828,1.4891,1.4906,1.4922,1.4953,1.4953,1.4953,1.4953,1.4859,1.4797,1.4734,1.4734,1.4688,1.4641,1.4609,1.4578,1.4562,1.4531,1.4484,1.4469,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4438,1.4438,1.4438,1.4438,1.4438,\r\n011,blank.jpg,24,inCongMNL791,~2+.jpg,~9-.jpg,~2+.jpg,0,1,1281,140,2,0,0,12:57:15,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0578,0.0625,0.0656,0.0812,0.0969,0.0969,0.1656,0.1656,0.2953,0.2953,0.4078,0.4078,0.5172,0.6016,0.725,0.7844,0.8609,0.9156,0.9656,1.0312,1.0312,1.1172,1.1172,1.1641,1.1641,1.2031,1.2031,1.2359,1.2516,1.2547,1.2547,1.2547,1.2547,1.2547,1.2547,1.2547,1.2578,1.2625,1.2625,1.2828,1.2828,1.2922,1.2969,1.3016,1.3094,1.3156,1.3203,1.3281,1.3328,1.3391,1.3438,1.3484,1.3531,1.3531,1.3641,1.3641,1.3734,1.3766,1.3797,1.3812,1.3844,1.3844,1.3844,1.3844,1.3844,1.3844,1.3844,1.3844,1.3844,1.3844,1.3844,1.3844,1.3844,\r\n011,blank.jpg,25,CongMNL112,~1-.jpg,~2+.jpg,~2+.jpg,0,2,1125,47,1,0,0,12:57:18,,101,0.05,0.05,0.0766,0.0766,0.0766,0.0781,0.0828,0.0938,0.1078,0.1312,0.1516,0.1766,0.1938,0.2188,0.2359,0.2359,0.3234,0.425,0.425,0.5031,0.6062,0.6797,0.7719,0.8328,0.8953,0.9297,0.975,1.0094,1.0641,1.1,1.1297,1.1297,1.1625,1.1625,1.1766,1.1766,1.1859,1.2016,1.2141,1.2359,1.2516,1.2688,1.2828,1.3,1.3141,1.3312,1.3312,1.3562,1.3562,1.3672,1.3797,1.3891,1.3969,1.3984,1.4,1.4016,1.4031,1.4047,1.4047,1.4062,1.4062,1.4062,1.4062,1.4062,1.4078,1.4078,1.4094,1.4094,1.4109,1.4109,1.4109,1.4109,\r\n011,break.jpg,26,,,,,0,,0,0,,0,0,12:57:20,,101,\r\n011,blank.jpg,27,inCongiMNL192,~9-.jpg,~8+.jpg,~8+.jpg,0,2,1079,125,1,0,0,12:57:24,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0812,0.0812,0.1203,0.1203,0.1453,0.1906,0.2891,0.2891,0.3344,0.4109,0.4734,0.5812,0.6562,0.7344,0.7734,0.7734,0.8172,0.8906,0.8906,0.9172,0.9453,0.9594,0.9781,0.9844,0.9891,0.9969,1.0094,1.025,1.0453,1.0641,1.0953,1.0953,1.1406,1.1406,1.1578,1.1828,1.1984,1.2156,1.2344,1.2469,1.2656,1.2781,1.2922,1.3016,1.3203,1.3328,1.3328,1.35,1.3766,1.3766,1.4078,1.4078,1.4203,1.4344,1.4422,1.4469,1.4469,1.4516,1.4516,1.4516,1.4516,1.4516,\r\n011,blank.jpg,28,inCongMNL81_91,~1+.jpg,~9-.jpg,~1+.jpg,0,1,1469,172,2,0,0,12:57:27,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0406,0.0453,0.0453,0.1156,0.1156,0.2,0.2531,0.3344,0.3891,0.4828,0.5484,0.6359,0.6938,0.7766,0.8312,0.9,0.9422,0.9422,1.0188,1.0453,1.0453,1.0828,1.0828,1.0938,1.1047,1.1109,1.1219,1.1297,1.1375,1.1438,1.1484,1.1484,1.1531,1.1531,1.1531,1.1547,1.1547,1.1594,1.1594,1.1719,1.1812,1.2,1.2172,1.2531,1.2891,1.3359,1.3359,1.3672,1.4328,1.4328,1.4641,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.4984,1.4953,1.4875,1.4766,1.4766,1.4609,1.4609,1.4531,1.4484,1.4469,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4469,1.4469,1.4469,\r\n011,blank.jpg,29,CongiMNL81_91,~9+.jpg,~1-.jpg,~9+.jpg,0,1,1156,78,2,0,0,12:57:29,,101,0.05,0.05,0.05,0.05,0.0625,0.0672,0.0812,0.1125,0.1438,0.1438,0.2219,0.2219,0.2688,0.4547,0.4547,0.5797,0.7094,0.7922,0.8938,0.9484,1.0047,1.0688,1.1062,1.15,1.1656,1.1812,1.1844,1.1844,1.1875,1.1875,1.1891,1.1891,1.1781,1.175,1.1766,1.1844,1.2031,1.2188,1.2516,1.2703,1.2922,1.2922,1.3188,1.3188,1.3375,1.3375,1.3406,1.3422,1.3453,1.3469,1.3484,1.3547,1.3609,1.3766,1.3891,1.4,1.4,1.4062,1.4125,1.4125,1.4125,1.4125,1.4125,1.4141,1.4141,1.4156,1.4172,1.4172,1.4172,1.4188,1.4188,1.4188,1.4188,\r\n011,blank.jpg,30,inCongiMNL712,~8-.jpg,~1+.jpg,~1+.jpg,0,2,1156,156,1,0,0,12:57:32,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0562,0.0562,0.0625,0.0812,0.1109,0.1312,0.1562,0.2016,0.2672,0.3156,0.3922,0.4312,0.4891,0.5359,0.6156,0.6156,0.6875,0.8328,0.8328,0.8766,0.9875,0.9875,1.0516,1.0938,1.1453,1.1797,1.2266,1.2703,1.2984,1.3391,1.3672,1.3672,1.4125,1.4125,1.4422,1.4422,1.45,1.4562,1.4562,1.4594,1.4594,1.4594,1.4594,1.4578,1.4578,1.4562,1.4562,1.4562,1.4562,1.4562,1.4562,1.4562,1.4547,1.4516,1.4469,1.4438,1.4422,1.4406,1.4406,1.4406,1.4391,1.4391,1.4391,1.4391,1.4391,\r\n011,blank.jpg,31,CongiMNL791,~9+.jpg,~2-.jpg,~9+.jpg,0,1,1266,125,2,0,0,12:57:34,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0578,0.0578,0.0578,0.0578,0.0578,0.0594,0.0594,0.0609,0.0609,0.0609,0.0625,0.0656,0.0734,0.0734,0.0828,0.1172,0.1172,0.1469,0.1734,0.2219,0.2609,0.3203,0.3703,0.4672,0.5328,0.6344,0.6953,0.7797,0.7797,0.9047,0.9047,0.9547,1.0438,1.0438,1.0953,1.0953,1.1078,1.125,1.1344,1.1375,1.1453,1.1516,1.1594,1.1594,1.1828,1.1828,1.2109,1.2109,1.2266,1.2359,1.2547,1.2672,1.2844,1.2984,1.3188,1.3375,1.3578,1.3688,1.3688,1.3953,1.3953,1.4203,1.4203,1.4328,1.4406,1.45,1.4547,1.4547,1.4547,1.4562,1.4562,1.4562,1.4562,1.4562,\r\n011,blank.jpg,32,inCongMNL6non1,~2+.jpg,~8-.jpg,~2+.jpg,0,1,1312,109,2,0,0,12:57:36,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.0297,0.0297,0.0359,0.0359,0.0375,0.0422,0.0484,0.0609,0.0609,0.0672,0.0797,0.0922,0.1109,0.1219,0.1547,0.1859,0.1859,0.2266,0.3094,0.3094,0.375,0.4266,0.4969,0.5438,0.6109,0.6547,0.7203,0.7641,0.8312,0.8812,0.9391,0.975,0.975,1.0625,1.0625,1.1078,1.1312,1.1547,1.1672,1.1859,1.1953,1.2094,1.2203,1.2312,1.2391,1.25,1.2578,1.2578,1.2688,1.2844,1.2844,1.3078,1.3078,1.3172,1.3297,1.3406,1.3562,1.3641,1.375,1.3844,1.3953,1.3953,1.4078,1.4078,1.4188,1.4188,1.4234,1.425,1.4297,1.4312,1.4312,1.4312,1.4312,1.4312,1.4312,1.4312,1.4312,1.4312,\r\n011,blank.jpg,33,CongiMNL111,~2+.jpg,~1-.jpg,~2+.jpg,0,1,1047,125,2,0,0,12:57:39,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0406,0.0406,0.0531,0.0531,0.0625,0.0906,0.0906,0.1094,0.1266,0.1656,0.1969,0.25,0.2859,0.3469,0.3906,0.4531,0.4531,0.5484,0.5844,0.5844,0.675,0.675,0.7625,0.7625,0.8094,0.8391,0.8828,0.9109,0.9516,0.9812,1.0188,1.0438,1.0438,1.1125,1.1125,1.1797,1.1797,1.2156,1.2406,1.2734,1.2969,1.3297,1.35,1.3766,1.3953,1.4188,1.4328,1.4328,1.4547,1.4609,1.4609,1.4656,1.4656,1.4656,1.4656,1.4672,1.4672,1.4672,1.4672,1.4672,\r\n011,blank.jpg,34,inCongiMNL792,~9-.jpg,~2+.jpg,~2+.jpg,0,2,1250,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1,1.4781,1.4781,1.4781,1.4766,1.4734,\r\n011,blank.jpg,49,CongMNL712,~1-.jpg,~8+.jpg,~8+.jpg,0,2,1391,94,1,0,0,12:58:17,,101,0.05,0.05,0.05,0.05,0.05,0.0703,0.0703,0.0703,0.0703,0.0703,0.0703,0.0703,0.0703,0.0703,0.0703,0.0703,0.0703,0.0703,0.0703,0.0703,0.0719,0.0719,0.0734,0.0766,0.0859,0.1047,0.1531,0.1969,0.2688,0.3266,0.4203,0.4203,0.5953,0.5953,0.6703,0.775,0.8406,0.9156,0.9672,1.0281,1.0656,1.1156,1.1438,1.1438,1.1766,1.1766,1.2047,1.2203,1.2203,1.2266,1.2266,1.2266,1.2281,1.2281,1.2281,1.2297,1.2359,1.2422,1.2484,1.2484,1.2688,1.2828,1.2828,1.3141,1.3141,1.3312,1.3422,1.3531,1.3703,1.3781,1.3875,1.3922,1.3953,1.3953,1.3953,1.3969,1.3969,1.4031,1.4031,1.4031,1.4062,1.4078,1.4094,1.4094,1.4094,1.4094,1.4078,1.4062,\r\n011,blank.jpg,50,CongiMNL191,~9+.jpg,~8-.jpg,~9+.jpg,0,1,1218,109,2,0,0,12:58:20,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.0391,0.0391,0.0406,0.0422,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0469,0.0594,0.0859,0.1031,0.1031,0.1719,0.1719,0.2625,0.2625,0.3797,0.3797,0.4453,0.5125,0.5844,0.6359,0.7031,0.7531,0.8203,0.8609,0.9234,0.9625,0.9625,1.0625,1.0625,1.1047,1.15,1.1797,1.2172,1.2344,1.2547,1.2672,1.2844,1.2969,1.3109,1.3203,1.3328,1.3328,1.3562,1.3672,1.3672,1.3922,1.3922,1.4094,1.4172,1.4328,1.4453,1.4562,1.4594,1.4594,1.4609,1.4609,1.4609,1.4609,1.4609,1.4609,\r\n011,break.jpg,51,,,,,0,,0,0,,0,0,12:58:23,,101,\r\n011,blank.jpg,52,inCongMNL111,~1+.jpg,~2-.jpg,~1+.jpg,0,1,1719,250,2,0,0,12:58:31,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0328,0.0375,0.0703,0.0969,0.1375,0.1688,0.1688,0.3109,0.3109,0.3875,0.5828,0.5828,0.7109,0.8031,0.925,0.9891,1.0938,1.1484,1.2172,1.2547,1.2906,1.3078,1.3203,1.3281,1.3281,1.3531,1.3531,1.3641,1.3641,1.3641,1.3703,1.3875,1.3984,1.4188,1.4328,1.4516,1.4625,1.4625,1.4797,1.4797,1.4844,1.4844,1.4859,1.4859,1.4844,1.4812,1.4797,1.4781,1.4766,1.475,1.4734,1.4719,1.4719,1.4719,1.4719,1.4719,1.4688,1.4688,1.4672,1.4672,1.4672,1.4672,1.4672,1.4672,1.4672,1.4672,1.4688,1.4703,1.4719,1.4719,1.4719,1.4719,1.4719,1.4719,1.4719,1.4703,1.4672,1.4672,1.4641,1.4625,1.4609,1.4594,1.4578,1.4578,1.4578,1.4578,1.4578,1.4516,1.4516,1.4484,1.45,1.45,1.45,1.45,1.45,\r\n011,blank.jpg,53,inCongiMNL112,~2-.jpg,~1+.jpg,~1+.jpg,0,2,1172,47,1,0,0,12:58:34,,101,0.05,0.05,0.0781,0.0781,0.0781,0.0781,0.0781,0.0781,0.0781,0.0781,0.0781,0.0781,0.0781,0.0781,0.0781,0.0781,0.0875,0.0938,0.1578,0.2141,0.2141,0.375,0.375,0.4609,0.6047,0.6047,0.7844,0.7844,0.8484,0.9359,0.9844,1.0531,1.0953,1.1516,1.1797,1.1797,1.2391,1.2391,1.2734,1.2734,1.2859,1.2984,1.3172,1.3312,1.3484,1.3578,1.3688,1.3781,1.3781,1.3922,1.3922,1.4094,1.4094,1.4234,1.4234,1.425,1.4266,1.4266,1.4281,1.4281,1.4281,1.4297,1.4312,1.4344,1.4391,1.4406,1.4406,1.4406,1.4406,1.4422,1.4422,1.4422,1.4422,1.4422,1.4422,\r\n011,blank.jpg,54,inCongiMNL6non2,~8-.jpg,~2+.jpg,~2+.jpg,0,2,1218,62,1,0,0,12:58:36,,101,0.05,0.05,0.05,0.0547,0.0562,0.0594,0.0703,0.0797,0.0797,0.1188,0.1188,0.1406,0.1766,0.2016,0.2406,0.2641,0.3078,0.3406,0.3938,0.4359,0.5016,0.5547,0.6281,0.6797,0.7656,0.8203,0.8203,0.9578,0.9578,1.0281,1.0703,1.1391,1.1797,1.2328,1.2609,1.3016,1.3297,1.3594,1.375,1.3969,1.3969,1.4312,1.4312,1.4578,1.4578,1.4688,1.4766,1.4891,1.4984,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.4953,1.4953,1.4797,1.4797,1.475,1.4688,1.4641,1.4625,1.4609,1.4594,1.4562,1.4547,1.45,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,\r\n011,blank.jpg,55,CongiMNL791,~9+.jpg,~2-.jpg,~9+.jpg,0,1,1328,141,2,0,0,12:58:38,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0312,0.0312,0.0422,0.0422,0.0484,0.0484,0.0594,0.0906,0.1188,0.1422,0.1703,0.225,0.2625,0.3281,0.3812,0.4547,0.4547,0.5578,0.5578,0.6,0.7,0.7,0.7547,0.7891,0.8359,0.8688,0.9188,0.95,0.9844,1.0094,1.0469,1.0703,1.0703,1.1156,1.1688,1.1688,1.2047,1.2453,1.2719,1.3016,1.3234,1.3531,1.375,1.4,1.4125,1.4297,1.4438,1.4438,1.4656,1.4656,1.4812,1.4812,1.4828,1.4828,1.4828,1.4828,1.4781,1.4672,1.4609,1.4531,1.45,1.4453,1.4453,1.4438,1.4438,1.4438,1.4438,1.4438,1.4438,1.4438,1.4438,1.4438,1.4453,1.4453,1.4422,1.4438,\r\n011,blank.jpg,56,inCongMNL791,~2+.jpg,~9-.jpg,~2+.jpg,0,1,937,109,2,0,0,12:58:40,,101,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0469,0.05,0.05,0.05,0.0625,0.0625,0.0719,0.0766,0.0766,0.0906,0.1047,0.1328,0.1328,0.1688,0.2016,0.2688,0.3219,0.4125,0.4844,0.5984,0.5984,0.6688,0.8125,0.8125,0.8875,0.9312,1,1.0453,1.0969,1.1641,1.2266,1.2734,1.3328,1.3672,1.4094,1.4281,1.4281,1.4625,1.4703,1.4703,1.475,1.4781,1.4812,1.4828,1.4828,1.4828,1.4828,1.4828,1.4828,1.4828,1.4828,1.4828,1.4828,1.4828,\r\n011,blank.jpg,57,inCongMNL6non1,~2+.jpg,~8-.jpg,~2+.jpg,0,1,1157,47,2,0,0,12:58:43,,101,0.05,0.05,0.0281,0.0281,0.0281,0.0297,0.0297,0.0312,0.0344,0.0359,0.0406,0.05,0.0609,0.0875,0.1078,0.1531,0.1859,0.2578,0.2578,0.4297,0.4297,0.6344,0.6344,0.7531,0.8391,0.8953,0.9688,1.0156,1.0828,1.1234,1.1703,1.1984,1.2359,1.2672,1.2672,1.3141,1.3875,1.3875,1.4062,1.4359,1.4531,1.475,1.4891,1.4891,1.4891,1.4891,1.4891,1.4891,1.5,1.5,1.5,1.5,1.4984,1.4953,1.4938,1.4922,1.4875,1.4859,1.4828,1.4781,1.4781,1.4703,1.4672,1.4672,1.4625,1.4625,1.4609,1.4578,1.4578,1.4547,1.4547,1.4547,1.4547,1.4547,\r\n011,blank.jpg,58,CongiMNL711,~8+.jpg,~1-.jpg,~8+.jpg,0,1,1312,62,2,0,0,12:58:45,,101,0.05,0.05,0.05,0.0625,0.0609,0.0609,0.0594,0.0594,0.0594,0.0594,0.0594,0.0594,0.0594,0.0594,0.0594,0.0594,0.0609,0.0609,0.0609,0.0609,0.0609,0.0609,0.0609,0.0609,0.0609,0.0609,0.0609,0.0609,0.0609,0.0609,0.0609,0.0609,0.0625,0.0641,0.0656,0.0656,0.0672,0.0719,0.0812,0.1016,0.1016,0.1594,0.1594,0.1953,0.2906,0.2906,0.3688,0.4203,0.5141,0.6047,0.6812,0.75,0.85,0.85,1.0281,1.0281,1.1891,1.2484,1.2484,1.3219,1.3594,1.4406,1.4406,1.475,1.4922,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.4984,1.4953,1.4891,1.4828,1.4766,1.4734,1.4719,1.4703,1.4688,1.4688,\r\n011,blank.jpg,59,CongiMNL6non1,~8+.jpg,~2-.jpg,~8+.jpg,0,1,938,32,2,0,0,12:58:47,,101,0.0188,0.025,0.025,0.0297,0.0359,0.0438,0.0547,0.0719,0.0859,0.1203,0.15,0.1906,0.1906,0.2641,0.2969,0.2969,0.3469,0.3797,0.4266,0.4656,0.5203,0.5641,0.6328,0.6781,0.7438,0.7828,0.8391,0.875,0.9266,0.9266,0.9984,0.9984,1.0203,1.05,1.0719,1.0922,1.1156,1.1359,1.1641,1.1859,1.2188,1.2375,1.2688,1.2688,1.3156,1.3156,1.3344,1.3547,1.3672,1.3828,1.3922,1.4,1.4047,1.4078,1.4078,1.4078,1.4078,1.4078,1.4094,1.4094,\r\n011,blank.jpg,60,CongMNL6non2,~2-.jpg,~8+.jpg,~8+.jpg,0,2,1328,31,1,0,0,12:58:49,,101,0.0547,0.0578,0.0641,0.0672,0.0703,0.075,0.0812,0.0922,0.0922,0.1422,0.1422,0.175,0.2578,0.2578,0.3547,0.3547,0.4391,0.5266,0.5906,0.7125,0.7938,0.8875,0.9953,0.9953,1.0938,1.0938,1.1703,1.1703,1.2031,1.2453,1.2672,1.2953,1.3078,1.3203,1.325,1.3297,1.3312,1.3328,1.3328,1.3328,1.3328,1.3344,1.3344,1.3375,1.3406,1.3469,1.3516,1.3562,1.3578,1.3594,1.3641,1.3656,1.3703,1.3703,1.3703,1.3703,1.3703,1.3703,1.3703,1.3703,1.3703,1.3703,1.3703,1.3719,1.3734,1.375,1.3781,1.3844,1.3891,1.3938,1.4,1.4,1.4125,1.4125,1.4156,1.4188,1.4234,1.425,1.4281,1.4281,1.4297,1.4297,1.4297,1.4297,1.4297,\r\n011,blank.jpg,61,CongMNL192,~8-.jpg,~9+.jpg,~9+.jpg,0,2,1078,47,1,0,0,12:58:53,,101,0.0656,0.0656,0.0688,0.0688,0.0688,0.0688,0.0688,0.0703,0.0781,0.0844,0.1016,0.1219,0.1484,0.1938,0.2266,0.2266,0.3203,0.3203,0.4281,0.4281,0.5453,0.5453,0.625,0.6875,0.775,0.8141,0.8703,0.9062,0.9547,0.9891,1.0375,1.0734,1.0734,1.1688,1.1688,1.2453,1.2453,1.2812,1.3031,1.3328,1.3469,1.3656,1.3812,1.3984,1.4078,1.4172,1.4172,1.4297,1.4297,1.4344,1.4422,1.4422,1.4438,1.4438,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4469,1.4469,1.4469,1.4469,1.4469,\r\n011,blank.jpg,62,inCongiMNL192,~9-.jpg,~8+.jpg,~8+.jpg,0,2,1250,109,1,0,0,12:58:56,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.0422,0.0422,0.0422,0.0422,0.0422,0.0438,0.0469,0.05,0.0578,0.0656,0.0797,0.0953,0.1219,0.1484,0.1484,0.2328,0.2328,0.2891,0.3344,0.4078,0.4516,0.5156,0.5625,0.6141,0.6516,0.6984,0.7312,0.7734,0.7734,0.8406,0.8406,0.8828,0.9562,0.9562,0.9922,1.0219,1.0578,1.0812,1.1078,1.1281,1.1469,1.1688,1.1859,1.2062,1.2062,1.2422,1.2422,1.2734,1.2734,1.3,1.3,1.3125,1.3203,1.3297,1.3422,1.3516,1.3641,1.3719,1.3828,1.3891,1.3891,1.4016,1.4094,1.4094,1.425,1.425,1.425,1.425,1.425,1.425,1.425,1.425,1.425,1.425,\r\n011,blank.jpg,63,CongMNL112,~1-.jpg,~2+.jpg,~2+.jpg,0,2,1375,47,1,0,0,12:58:58,,101,0.05,0.05,0.0656,0.0656,0.0672,0.0688,0.0719,0.0734,0.075,0.0797,0.0844,0.0953,0.1078,0.1234,0.1391,0.1625,0.1828,0.2203,0.2203,0.2938,0.2938,0.325,0.3766,0.425,0.4984,0.5484,0.6234,0.6719,0.7438,0.7906,0.8672,0.8672,0.9812,0.9812,1.0953,1.0953,1.1438,1.2109,1.2531,1.3188,1.3562,1.4078,1.4391,1.4734,1.4906,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.4953,1.4906,1.4797,1.4734,1.4641,1.4641,1.45,1.4438,1.4438,1.4406,1.4406,1.4406,1.4406,1.4406,1.4406,1.4406,1.4406,1.4391,1.4375,1.4375,1.4359,1.4344,1.4344,1.4344,1.4344,1.4344,1.4344,1.4344,1.4344,1.4344,1.4344,\r\n011,blank.jpg,64,CongMNL792,~2-.jpg,~9+.jpg,~9+.jpg,0,2,1360,31,1,0,0,12:59:01,,101,0.0812,0.0828,0.0859,0.0922,0.1,0.1078,0.1188,0.1188,0.1484,0.1484,0.1641,0.175,0.175,0.175,0.175,0.175,0.175,0.175,0.175,0.175,0.175,0.175,0.175,0.175,0.175,0.1766,0.1766,0.1781,0.1828,0.2297,0.2672,0.35,0.4312,0.525,0.5875,0.6859,0.7453,0.7453,0.8562,0.8562,0.9453,0.9969,0.9969,1.0656,1.0656,1.1016,1.1297,1.1469,1.1703,1.1812,1.1969,1.2031,1.2078,1.2078,1.2078,1.2078,1.2141,1.2141,1.2266,1.2266,1.2375,1.25,1.2609,1.2781,1.2906,1.3078,1.3188,1.3344,1.3484,1.3484,1.3641,1.3938,1.3938,1.4031,1.4156,1.4219,1.4312,1.4359,1.4406,1.4406,1.4406,1.4406,1.4406,1.4391,1.4391,1.4375,1.4375,\r\n011,blank.jpg,65,inCongiMNL712,~8-.jpg,~1+.jpg,~1+.jpg,0,2,1453,78,1,0,0,12:59:03,,101,0.05,0.05,0.05,0.05,0.0641,0.0625,0.0625,0.0594,0.0594,0.0562,0.0531,0.0531,0.0531,0.0531,0.0531,0.0531,0.0531,0.0516,0.0547,0.0875,0.1203,0.1734,0.1734,0.2547,0.2547,0.3562,0.3562,0.3906,0.4281,0.4531,0.4906,0.5203,0.5703,0.6125,0.675,0.7266,0.7938,0.7938,0.9016,0.9016,0.9922,0.9922,1.0281,1.0766,1.1078,1.1516,1.1812,1.2078,1.2266,1.2438,1.2531,1.2531,1.275,1.275,1.2875,1.3156,1.3156,1.3406,1.3406,1.35,1.3641,1.375,1.3844,1.3984,1.4047,1.4109,1.4156,1.4188,1.4188,1.4297,1.4297,1.4344,1.4344,1.4344,1.4359,1.4359,1.4359,1.4359,1.4344,1.4328,1.4312,1.4297,1.4266,1.4234,1.4203,1.4203,1.4188,1.4188,1.4188,1.4188,1.4188,1.4188,\r\n011,blank.jpg,66,CongiMNL81_91,~9+.jpg,~1-.jpg,~9+.jpg,0,1,1234,140,2,0,0,12:59:06,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0484,0.0516,0.0516,0.0797,0.0797,0.1172,0.1172,0.1781,0.1781,0.2359,0.2828,0.3672,0.4328,0.5547,0.6188,0.7078,0.7562,0.8203,0.8578,0.9094,0.9484,0.9484,1.0531,1.0531,1.1094,1.1422,1.1859,1.2109,1.2438,1.2688,1.2938,1.3062,1.3203,1.3297,1.3391,1.3391,1.3469,1.3469,1.3484,1.3484,1.3484,1.3484,1.3484,1.3484,1.3484,1.3484,1.3484,1.3484,1.3484,1.35,1.3531,1.3531,1.3609,1.375,1.375,1.3828,1.3891,1.3906,1.3953,1.3984,1.4016,1.4031,1.4031,1.4031,1.4031,1.4031,1.4047,1.4047,1.4047,1.4047,1.4062,\r\n011,blank.jpg,67,CongiMNL111,~2+.jpg,~1-.jpg,~2+.jpg,0,1,1922,93,2,0,0,12:59:08,,101,0.05,0.05,0.05,0.05,0.05,0.0578,0.0578,0.0578,0.0594,0.0625,0.0625,0.0656,0.075,0.075,0.0922,0.0922,0.1047,0.1219,0.1547,0.1844,0.2344,0.2906,0.3422,0.3422,0.475,0.5172,0.5172,0.675,0.675,0.7469,0.8062,0.9078,0.9703,1.0453,1.0922,1.1594,1.2,1.2562,1.2922,1.3453,1.3453,1.3891,1.3891,1.4,1.4109,1.4156,1.4234,1.4281,1.4312,1.4328,1.4328,1.4328,1.4297,1.4234,1.4188,1.4188,1.4125,1.4078,1.4078,1.3984,1.3953,1.3953,1.3953,1.3953,1.3938,1.3938,1.3906,1.3844,1.3797,1.3766,1.3766,1.3734,1.3734,1.3734,1.3734,1.375,1.375,1.375,1.375,1.375,1.375,1.3766,1.3766,1.3781,1.3781,1.3797,1.3844,1.3844,1.3859,1.3875,1.3875,1.3922,1.3953,1.3969,1.3969,1.3969,1.3969,1.3969,1.3969,1.3969,1.3969,1.3953,1.3953,1.3953,1.3953,1.3953,1.3953,1.3953,1.3953,1.3953,1.3953,1.3984,1.4031,1.4078,1.4109,1.4125,1.4125,1.4141,1.4141,1.4156,1.4156,1.4156,1.4156,\r\n011,blank.jpg,68,inCongMNL711,~1+.jpg,~8-.jpg,~1+.jpg,0,1,1656,47,2,0,0,12:59:12,,101,0.0297,0.0297,0.0297,0.0297,0.0312,0.0312,0.0312,0.0312,0.0297,0.0297,0.0297,0.0297,0.0297,0.0297,0.0297,0.0297,0.0297,0.0297,0.0297,0.0297,0.0297,0.0297,0.0297,0.0297,0.0297,0.0297,0.0297,0.0297,0.0297,0.0297,0.0297,0.0297,0.0297,0.0297,0.0312,0.0344,0.0391,0.0422,0.0453,0.0531,0.0859,0.1203,0.1203,0.1797,0.2938,0.2938,0.4203,0.4203,0.4672,0.5219,0.5562,0.5922,0.6109,0.6328,0.6484,0.6656,0.6812,0.7,0.7,0.7344,0.7344,0.7516,0.7766,0.7969,0.8312,0.8547,0.8891,0.9188,0.9609,0.9922,1.0312,1.0594,1.0875,1.0875,1.1469,1.1703,1.1703,1.2219,1.2219,1.2516,1.2672,1.2938,1.3109,1.3297,1.3406,1.3516,1.3641,1.375,1.3812,1.3812,1.3953,1.3953,1.4109,1.4109,1.4188,1.4219,1.4234,1.4234,1.4234,1.4234,1.425,1.425,1.425,1.425,1.425,1.425,\r\n011,blank.jpg,69,CongiMNL191,~9+.jpg,~8-.jpg,~9+.jpg,0,1,1219,31,2,0,0,12:59:15,,101,0.05,0.0625,0.0625,0.0625,0.0625,0.0641,0.0703,0.0703,0.0781,0.0922,0.1031,0.1219,0.1375,0.1625,0.1828,0.225,0.2547,0.3125,0.3125,0.4172,0.4172,0.5156,0.5156,0.5547,0.6156,0.6641,0.7391,0.7875,0.8578,0.9094,0.9766,1.0266,1.0906,1.1281,1.1875,1.1875,1.2281,1.2875,1.3281,1.3828,1.4156,1.4891,1.4891,1.5,1.5,1.5,1.5,1.5,1.5,1.4984,1.4984,1.4922,1.4922,1.475,1.475,1.4672,1.4625,1.4562,1.4516,1.45,1.4469,1.4422,1.4406,1.4391,1.4391,1.4375,1.4375,1.4359,1.4359,1.4359,1.4359,1.4359,1.4375,1.4375,1.4375,1.4375,1.4359,\r\n011,blank.jpg,70,inCongMNL81_91,~1+.jpg,~9-.jpg,~1+.jpg,0,1,875,31,2,0,0,12:59:17,,101,0.0609,0.0656,0.0766,0.0984,0.1469,0.1828,0.2344,0.2344,0.3422,0.3422,0.4891,0.4891,0.6625,0.6625,0.7312,0.8094,0.9141,1.0141,1.0734,1.1453,1.1906,1.2516,1.2891,1.3344,1.3547,1.3547,1.4,1.4,1.4156,1.4281,1.4375,1.4422,1.4438,1.4438,1.4438,1.4438,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4406,1.4406,1.4375,1.4375,1.4375,1.4375,1.4375,1.4375,1.4391,1.4391,1.4391,1.4391,1.4391,\r\n011,blank.jpg,71,inCongiMNL81_92,~9-.jpg,~1+.jpg,~1+.jpg,0,2,1640,31,1,0,0,12:59:19,,101,0.0766,0.0938,0.1125,0.1453,0.1703,0.2234,0.2719,0.2719,0.4141,0.4141,0.4938,0.5578,0.6047,0.6938,0.7625,0.8547,0.9203,1.0062,1.0797,1.1281,1.1844,1.1844,1.2609,1.2609,1.3266,1.3266,1.3578,1.3781,1.4016,1.4141,1.4297,1.4406,1.4484,1.4516,1.4516,1.4562,1.4562,1.4562,1.4562,1.4562,1.4531,1.4531,1.45,1.4469,1.4422,1.4375,1.4312,1.4219,1.4109,1.4094,1.4047,1.4,1.4,1.3906,1.3906,1.3891,1.3891,1.3891,1.3891,1.3891,1.3891,1.3891,1.3891,1.3891,1.3891,1.3891,1.3891,1.3891,1.3891,1.3891,1.3891,1.3891,1.3891,1.3891,1.3906,1.3922,1.3938,1.3969,1.4,1.4016,1.4016,1.4016,1.4016,1.4016,1.4016,1.4016,1.4016,1.4016,1.4016,1.4031,1.4047,1.4062,1.4078,1.4078,1.4078,1.4078,1.4078,1.4078,1.4078,1.4078,1.4078,1.4078,1.4078,1.4078,1.4078,\r\n011,blank.jpg,72,CongMNL712,~1-.jpg,~8+.jpg,~8+.jpg,0,2,1063,63,1,0,0,12:59:22,,101,0.05,0.05,0.0609,0.0641,0.0641,0.0734,0.0844,0.1125,0.1609,0.1953,0.25,0.3453,0.4109,0.5188,0.5875,0.7047,0.7844,0.7844,0.9531,0.9531,1.0234,1.0578,1.0844,1.1016,1.1234,1.1344,1.1531,1.1641,1.1859,1.2016,1.2375,1.2594,1.2594,1.3,1.3,1.3156,1.325,1.3266,1.3281,1.3297,1.3312,1.3328,1.3328,1.3359,1.3406,1.3438,1.3469,1.3469,1.3562,1.3562,1.3703,1.3703,1.3766,1.3859,1.3953,1.4047,1.4109,1.4203,1.4266,1.4328,1.4344,1.4344,1.4344,1.4344,1.434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blank.jpg,97,inCongMNL6non1,~2+.jpg,~8-.jpg,~2+.jpg,0,1,1187,94,2,0,0,13:00:30,,101,0.05,0.05,0.05,0.05,0.05,0.075,0.075,0.0906,0.0906,0.1078,0.1203,0.1438,0.1625,0.1984,0.2281,0.2703,0.3031,0.3484,0.3484,0.3797,0.4594,0.4594,0.5438,0.5438,0.5891,0.6219,0.6656,0.6984,0.7453,0.7766,0.8109,0.8469,0.8688,0.8688,0.9406,0.9406,1.0078,1.0078,1.0391,1.0766,1.0969,1.1297,1.1531,1.1797,1.2047,1.2234,1.2469,1.2672,1.2969,1.3125,1.3125,1.3375,1.375,1.375,1.3891,1.4062,1.4156,1.4266,1.4344,1.4406,1.4438,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,\r\n011,blank.jpg,98,CongiMNL111,~2+.jpg,~1-.jpg,~2+.jpg,0,1,1063,32,2,0,0,13:00:32,,101,0.05,0.0359,0.0359,0.0359,0.0375,0.0375,0.0375,0.0375,0.0391,0.0391,0.0391,0.0406,0.0406,0.0422,0.0422,0.0438,0.0453,0.0469,0.05,0.0562,0.0641,0.0812,0.0969,0.1312,0.1656,0.2078,0.2078,0.2594,0.3547,0.3547,0.3938,0.4656,0.5125,0.5859,0.6594,0.7062,0.7734,0.8234,0.8641,0.9172,0.9172,0.9547,1.0344,1.0344,1.0797,1.1125,1.1516,1.1812,1.2188,1.2453,1.2734,1.2922,1.3172,1.3344,1.3531,1.3531,1.3781,1.3781,1.3859,1.3969,1.3969,1.3984,1.3984,1.3984,1.3984,1.3984,1.3984,\r\n011,blank.jpg,99,inCongiMNL712,~8-.jpg,~1+.jpg,~1+.jpg,0,2,1188,110,1,0,0,13:00:34,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.0641,0.0656,0.0734,0.0781,0.0891,0.1031,0.1188,0.1328,0.1578,0.1781,0.2031,0.2031,0.2422,0.3219,0.3219,0.3547,0.4078,0.4422,0.4953,0.5297,0.5875,0.6391,0.6781,0.7234,0.7781,0.8172,0.8781,0.9094,0.9641,0.9641,1.0031,1.0594,1.0891,1.1266,1.1516,1.1812,1.1984,1.2203,1.2344,1.2547,1.2688,1.2688,1.3016,1.3016,1.3297,1.3297,1.3484,1.3609,1.3781,1.3906,1.4078,1.4188,1.4281,1.4344,1.4391,1.4391,1.4422,1.4422,1.4422,1.4422,1.4422,1.4422,1.4422,1.4422,1.4438,1.4438,1.4438,1.4438,1.4438,1.4438,\r\n011,blank.jpg,100,CongMNL712,~1-.jpg,~8+.jpg,~8+.jpg,0,2,1328,156,1,0,0,13:00:37,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0766,0.0766,0.0766,0.0797,0.0797,0.0844,0.0922,0.1031,0.1141,0.1391,0.1609,0.2125,0.2469,0.2969,0.3344,0.3922,0.3922,0.4969,0.4969,0.5406,0.5953,0.6375,0.6938,0.7312,0.7891,0.8266,0.8812,0.9156,0.9656,1.0016,1.0016,1.1031,1.1031,1.1594,1.2531,1.2531,1.2828,1.325,1.3422,1.3672,1.3844,1.4078,1.425,1.4391,1.4547,1.4547,1.4812,1.4938,1.4938,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.4953,1.4953,1.4734,1.4734,1.4469,1.4469,1.4391,1.4359,1.4359,1.4359,1.4359,1.4359,1.4359,1.4375,1.4375,1.4375,\r\n011,break.jpg,101,,,,,0,,0,0,,0,0,13:00:39,,101,\r\n011,blank.jpg,102,inCongMNL111,~1+.jpg,~2-.jpg,~1+.jpg,0,1,1266,94,2,0,0,13:00:41,,101,0.05,0.05,0.05,0.05,0.05,0.0828,0.0828,0.0828,0.0891,0.0953,0.1,0.1047,0.1109,0.1141,0.1234,0.1328,0.1484,0.1609,0.1797,0.1797,0.2,0.2266,0.2453,0.2891,0.3188,0.3734,0.4172,0.4719,0.5156,0.5703,0.6094,0.6641,0.7031,0.7031,0.7828,0.7828,0.8234,0.85,0.8984,0.9266,0.9703,1,1.0484,1.0719,1.1031,1.1359,1.1578,1.1766,1.1766,1.2109,1.2312,1.2312,1.2672,1.2672,1.2781,1.2922,1.3047,1.3125,1.3188,1.3234,1.325,1.3266,1.3281,1.3297,1.3312,1.3312,1.3375,1.3375,1.3609,1.3609,1.3734,1.3938,1.4078,1.4234,1.4297,1.4359,1.4375,1.4375,1.4375,1.4375,1.4375,\r\n011,blank.jpg,103,CongMNL112,~1-.jpg,~2+.jpg,~2+.jpg,0,2,1782,110,1,0,0,13:00:44,,101,0.025,0.025,0.025,0.025,0.025,0.025,0.0234,0.0234,0.0234,0.0234,0.0234,0.0234,0.0234,0.0234,0.0234,0.0234,0.0234,0.0219,0.0234,0.0266,0.0422,0.0422,0.1125,0.1125,0.225,0.225,0.2859,0.3766,0.4438,0.4969,0.5719,0.6188,0.6781,0.7109,0.7562,0.7953,0.7953,0.8453,0.8453,0.8625,0.9031,0.9031,0.9188,0.9422,0.9578,0.9859,1.0109,1.0406,1.0578,1.0797,1.0797,1.1156,1.1156,1.1281,1.1578,1.1578,1.1766,1.1906,1.2109,1.2266,1.2453,1.2594,1.275,1.2891,1.3047,1.3156,1.3328,1.3438,1.3438,1.3703,1.3703,1.3844,1.3938,1.4016,1.4094,1.4156,1.4234,1.4266,1.4266,1.4266,1.4266,1.4266,1.4266,1.4266,1.4266,1.425,1.425,1.4234,1.4141,1.4031,1.3969,1.3953,1.3953,1.3953,1.3953,1.3953,1.3953,1.3953,1.3953,1.3953,1.3953,1.3953,1.3953,1.3953,1.3969,1.3969,1.3969,1.3969,1.3969,1.3969,1.3969,1.3969,1.4,1.4,\r\n011,blank.jpg,104,inCongiMNL712,~8-.jpg,~1+.jpg,~1+.jpg,0,2,3313,156,1,0,0,13:00:47,,101,0.0719,0.0719,0.0719,0.0719,0.0719,0.0719,0.0719,0.0719,0.0719,0.0734,0.0828,0.0828,0.0859,0.0859,0.0859,0.0859,0.0859,0.0859,0.0859,0.0859,0.0859,0.0859,0.0875,0.0875,0.0875,0.0875,0.0953,0.1312,0.1656,0.225,0.2625,0.3312,0.375,0.45,0.45,0.5406,0.5406,0.6172,0.6172,0.6828,0.6828,0.7109,0.7453,0.7672,0.8062,0.8375,0.8734,0.8969,0.9344,0.9578,0.9906,1.0141,1.0141,1.0594,1.0594,1.0859,1.1,1.125,1.1422,1.1656,1.1781,1.1984,1.2141,1.2344,1.2469,1.2625,1.2734,1.2734,1.2938,1.2938,1.3047,1.3156,1.3234,1.3312,1.3359,1.3438,1.35,1.3609,1.3688,1.3766,1.3828,1.3922,1.3922,1.3984,1.4094,1.4094,1.4141,1.4172,1.4234,1.4266,1.4266,1.4266,1.4266,1.4266,1.4266,1.4266,1.4266,1.4266,1.4281,1.4281,1.4281,1.4266,1.4266,1.4266,1.425,1.4172,1.4,1.3859,1.3359,1.2969,1.2312,1.1859,1.1859,1.0641,1.0641,0.925,0.925,0.8344,0.775,0.6984,0.6344,0.5547,0.5047,0.4391,0.4062,0.3594,0.3594,0.2953,0.2812,0.2812,0.2578,0.2578,0.2516,0.2422,0.2344,0.2219,0.2078,0.1953,0.1891,0.1828,0.1797,0.1719,0.1641,0.1641,0.1516,0.1516,0.1516,0.1516,0.1516,0.1516,0.1516,0.1516,0.1516,0.1516,0.1516,0.1516,0.1484,0.1594,0.175,0.175,0.2109,0.2969,0.2969,0.35,0.4438,0.5516,0.6281,0.7375,0.8047,0.8766,0.9578,1.0031,1.0594,1.0875,1.0875,1.1578,1.1578,1.1922,1.2312,1.2312,1.2672,1.2672,1.2797,1.2969,1.3078,1.3219,1.3328,1.35,1.3641,1.3641,1.3953,1.3953,1.4234,1.4234,1.4328,1.4375,1.4422,1.4438,1.4438,1.4438,1.4438,1.4438,1.4438,1.4438,1.4438,1.4438,1.4438,1.4438,1.4438,1.4438,1.4438,1.4438,\r\n011,blank.jpg,105,CongMNL712,~1-.jpg,~8+.jpg,~8+.jpg,0,2,1359,203,1,0,0,13:00:51,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0719,0.0719,0.0766,0.0766,0.0812,0.1125,0.15,0.2188,0.2688,0.35,0.3906,0.4641,0.5156,0.5969,0.5969,0.7344,0.7344,0.8469,0.9094,0.9094,1.0031,1.0031,1.0547,1.0844,1.1344,1.1656,1.2203,1.2531,1.2531,1.3359,1.3359,1.3859,1.4047,1.4047,1.4266,1.4391,1.4688,1.4688,1.4844,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.4969,1.4969,1.4859,1.4859,1.4797,1.4719,1.4703,1.4672,1.4641,1.4625,1.4594,1.4578,1.4562,1.4562,1.4547,1.4547,1.45,1.4484,1.4484,1.4484,1.4484,1.4469,1.4453,1.4453,1.4453,1.4438,1.4438,1.4438,\r\n011,blank.jpg,106,CongiMNL191,~9+.jpg,~8-.jpg,~9+.jpg,0,1,1313,31,2,0,0,13:00:55,,101,0.0797,0.1047,0.1047,0.1047,0.1047,0.1047,0.1047,0.1047,0.1047,0.1047,0.1047,0.1047,0.1047,0.1047,0.1047,0.1047,0.1047,0.1047,0.1047,0.1047,0.1047,0.1047,0.1156,0.1344,0.2172,0.2812,0.3641,0.4188,0.4969,0.5484,0.6344,0.7094,0.7094,0.7844,0.8641,0.8641,0.8953,0.9438,1.0109,1.0578,1.125,1.1672,1.2328,1.2875,1.3219,1.3719,1.3719,1.4531,1.4531,1.4953,1.4953,1.5,1.5,1.5,1.5,1.5,1.4984,1.4969,1.4875,1.4797,1.4719,1.4656,1.4656,1.45,1.4484,1.4484,1.4469,1.4469,1.4469,1.4469,1.4469,1.4469,1.4469,1.4469,1.4469,1.4469,1.4453,1.4453,1.4469,1.4469,1.4469,1.4469,1.4469,1.4469,\r\n011,blank.jpg,107,inCongiMNL192,~9-.jpg,~8+.jpg,~8+.jpg,0,2,1922,63,1,0,0,13:00:57,,101,0.05,0.05,0.05,0.0578,0.0578,0.0578,0.0594,0.0609,0.0703,0.0797,0.0984,0.1141,0.1391,0.1734,0.2094,0.2094,0.2406,0.2844,0.3156,0.3609,0.3953,0.4422,0.475,0.5297,0.5641,0.6156,0.6531,0.7094,0.7094,0.8047,0.8359,0.8359,0.8812,0.9141,0.9562,0.9781,1.0078,1.0219,1.0438,1.0594,1.075,1.0844,1.1016,1.1016,1.1516,1.1516,1.2062,1.2344,1.2344,1.2719,1.2953,1.3281,1.3484,1.3734,1.3875,1.3984,1.4016,1.4031,1.4047,1.4047,1.4047,1.4047,1.4047,1.4047,1.4047,1.4016,1.3984,1.3984,1.3984,1.3953,1.3938,1.3938,1.3938,1.3953,1.3953,1.3969,1.3969,1.3969,1.3969,1.3969,1.3969,1.3969,1.3969,1.3969,1.3969,1.3953,1.3922,1.3906,1.3906,1.3906,1.3906,1.3906,1.3906,1.3906,1.3906,1.3906,1.3938,1.3953,1.4,1.4,1.4047,1.4062,1.4062,1.4062,1.4062,1.4078,1.4078,1.4078,1.4094,1.4094,1.4094,1.4094,1.4094,1.4094,1.4094,1.4094,1.4094,1.4094,1.4094,1.4094,1.4094,1.4094,1.4094,\r\n011,blank.jpg,108,CongMNL81_92,~1-.jpg,~9+.jpg,~9+.jpg,0,2,1125,94,1,0,0,13:01:00,,101,0.05,0.05,0.05,0.05,0.05,0.0453,0.0453,0.0469,0.0531,0.0594,0.0703,0.0781,0.0938,0.1062,0.1266,0.1391,0.1688,0.2188,0.2188,0.3125,0.3516,0.3516,0.4438,0.4438,0.4906,0.5281,0.5844,0.6406,0.6984,0.7578,0.8531,0.9188,0.9969,1.0438,1.1109,1.1109,1.1906,1.1906,1.2188,1.2438,1.2609,1.2797,1.2906,1.3031,1.3156,1.3281,1.3359,1.3438,1.35,1.35,1.3594,1.3594,1.3641,1.3703,1.3703,1.3766,1.3859,1.3953,1.4047,1.4125,1.4188,1.4203,1.4203,1.4203,1.4203,1.4219,1.4219,1.4219,1.4219,1.4219,1.4219,1.4219,\r\n011,blank.jpg,109,CongMNL192,~8-.jpg,~9+.jpg,~9+.jpg,0,2,1234,62,1,0,0,13:01:02,,101,0.05,0.05,0.05,0.0438,0.0469,0.0484,0.05,0.0516,0.0516,0.0531,0.0562,0.0562,0.0562,0.0562,0.0562,0.0562,0.0562,0.0562,0.0562,0.0734,0.0922,0.1422,0.1766,0.2297,0.2578,0.3125,0.3625,0.4516,0.4516,0.6031,0.6031,0.6703,0.7453,0.8297,0.9094,0.9594,1.0234,1.0625,1.1109,1.1406,1.1844,1.2141,1.2547,1.2547,1.3141,1.3547,1.3547,1.4094,1.4094,1.425,1.4469,1.4625,1.4688,1.475,1.4781,1.4797,1.4828,1.4828,1.4828,1.4828,1.475,1.475,1.4547,1.4547,1.4516,1.45,1.4484,1.4469,1.4469,1.4469,1.4469,1.4469,1.4469,1.4469,1.4469,1.4469,1.4469,1.4469,\r\n011,blank.jpg,110,inCongiMNL112,~2-.jpg,~1+.jpg,~1+.jpg,0,2,1375,62,1,0,0,13:01:05,,101,0.05,0.05,0.05,0.0766,0.0766,0.0797,0.0828,0.0844,0.0875,0.0891,0.0938,0.0953,0.0984,0.0984,0.1062,0.1062,0.1172,0.1172,0.1422,0.1422,0.1562,0.1781,0.1984,0.2312,0.2609,0.3125,0.3547,0.4172,0.4172,0.5109,0.5484,0.5484,0.5891,0.5891,0.6359,0.6719,0.7406,0.7828,0.8547,0.9047,0.9562,1.0219,1.0641,1.1016,1.1016,1.1469,1.1469,1.1719,1.1719,1.1797,1.1906,1.2016,1.2109,1.2219,1.2375,1.2531,1.2703,1.2844,1.3,1.3094,1.3094,1.3219,1.3391,1.3391,1.3609,1.3609,1.3703,1.3812,1.3906,1.4031,1.4109,1.4219,1.4281,1.4344,1.4391,1.4422,1.4422,1.4422,1.4422,1.4422,1.4422,1.4422,1.4422,1.4422,1.4422,1.4422,1.4422,1.4422,\r\n011,blank.jpg,111,inCongMNL191,~8+.jpg,~9-.jpg,~8+.jpg,0,1,1438,125,2,0,0,13:01:07,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0203,0.0203,0.0219,0.0234,0.025,0.0297,0.0375,0.0453,0.0562,0.075,0.0859,0.1109,0.1297,0.1297,0.1938,0.2453,0.2453,0.2812,0.3422,0.3812,0.4469,0.5062,0.5875,0.6312,0.6984,0.7422,0.7969,0.8344,0.8344,0.9172,0.9172,0.9703,0.9891,0.9891,1.0047,1.0266,1.0406,1.0672,1.0859,1.1062,1.1234,1.1453,1.1609,1.1828,1.1828,1.2188,1.2266,1.2266,1.2359,1.2438,1.2594,1.2688,1.2859,1.3016,1.3203,1.3359,1.3547,1.3672,1.3781,1.3781,1.3984,1.3984,1.4047,1.4047,1.4062,1.4062,1.4078,1.4078,1.4078,1.4078,1.4078,1.4094,1.4109,1.4141,1.4141,1.4219,1.4219,1.425,1.425,1.425,1.4266,1.4266,1.4266,1.4266,1.4266,\r\n011,blank.jpg,112,inCongMNL81_91,~1+.jpg,~9-.jpg,~1+.jpg,0,1,1422,110,2,0,0,13:01:09,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.0594,0.0625,0.0656,0.075,0.0859,0.1078,0.1078,0.1594,0.1594,0.1953,0.275,0.275,0.325,0.3641,0.4234,0.4719,0.5469,0.5938,0.6594,0.6984,0.7562,0.8,0.8,0.8984,0.8984,0.9578,0.9953,1.0797,1.0797,1.1234,1.1438,1.1625,1.1656,1.1672,1.1672,1.1672,1.1672,1.1672,1.1672,1.1828,1.1828,1.1906,1.2047,1.2156,1.2328,1.25,1.2641,1.2812,1.2922,1.3,1.3047,1.3125,1.3125,1.3234,1.3297,1.3297,1.3422,1.3422,1.3484,1.3531,1.3609,1.3672,1.3734,1.3781,1.3828,1.3859,1.3875,1.3906,1.3938,1.3938,1.3969,1.3969,1.3984,1.4016,1.4031,1.4062,1.4078,1.4094,1.4094,1.4094,1.4094,1.4094,1.4094,1.4094,1.4078,\r\n011,blank.jpg,113,CongiMNL711,~8+.jpg,~1-.jpg,~8+.jpg,0,1,1718,62,2,0,0,13:01:12,,101,0.05,0.05,0.05,0.0547,0.0578,0.0609,0.0609,0.0609,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0453,0.0422,0.0125,0.0016,0.0438,0.1984,0.4125,0.7172,0.9109,1.0547,1.0547,1.1953,1.1953,1.2312,1.2656,1.3109,1.3422,1.3844,1.4234,1.4531,1.4938,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.4922,1.475,1.4641,1.4484,1.4344,1.4312,1.4312,1.4297,1.4281,1.4281,1.4297,1.4328,1.4453,1.4531,1.4656,1.4797,1.4906,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.4875,1.475,1.4531,1.4422,1.4344,1.4328,1.4328,1.4328,1.4312,1.4328,1.4344,1.4359,1.4359,1.4359,1.4359,1.4359,1.4359,1.4359,1.4359,1.4375,1.4375,1.4375,\r\n011,blank.jpg,114,inCongiMNL792,~9-.jpg,~2+.jpg,~2+.jpg,0,2,1547,63,1,0,0,13:01:16,,101,0.05,0.05,0.05,0.0266,0.0266,0.0266,0.0266,0.0266,0.0266,0.0266,0.0266,0.0266,0.025,0.0219,0.0156,0.0062,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0109,0.025,0.0422,0.0969,0.0969,0.1422,0.1781,0.2297,0.2766,0.3609,0.425,0.5141,0.5797,0.6859,0.6859,0.8703,0.8703,0.9328,1.0125,1.0547,1.1031,1.1328,1.1672,1.1844,1.2016,1.2156,1.2281,1.2422,1.2422,1.2656,1.2781,1.2781,1.3141,1.3141,1.3344,1.3484,1.3656,1.3766,1.3922,1.4047,1.4125,1.4156,1.4156,1.4188,1.4188,1.4188,1.4188,1.4188,1.4188,1.4203,1.4234,1.425,1.425,1.425,1.425,1.425,1.425,1.425,1.425,\r\n011,blank.jpg,115,inCongMNL711,~1+.jpg,~8-.jpg,~1+.jpg,0,1,2047,93,2,0,0,13:01:19,,101,0.05,0.05,0.05,0.05,0.05,0.0656,0.0688,0.0734,0.0922,0.1047,0.1359,0.1641,0.2094,0.2547,0.2828,0.2828,0.3641,0.3641,0.4031,0.4641,0.5078,0.5828,0.6266,0.7016,0.7531,0.8219,0.8688,0.9328,0.9328,1.0375,1.0375,1.1234,1.1547,1.1547,1.2203,1.2203,1.2531,1.2734,1.2969,1.3156,1.3328,1.3422,1.3562,1.3609,1.3625,1.3625,1.3625,1.3625,1.3625,1.3625,1.3625,1.3625,1.3625,1.3625,1.3625,1.3625,1.3625,1.3625,1.3625,1.3641,1.3641,1.3734,1.3734,1.3781,1.3781,1.3828,1.3891,1.3891,1.3906,1.3891,1.3844,1.3828,1.3828,1.3828,1.3828,1.3828,1.3828,1.3828,1.3828,1.3828,1.3828,1.3828,1.3828,1.3828,1.3828,1.3844,1.3844,1.3875,1.3953,1.3984,1.4016,1.4016,1.4047,1.4047,1.4062,1.4062,1.4062,1.4062,1.4062,1.4062,1.4062,1.4062,1.4062,1.4062,1.4078,1.4078,1.4078,1.4109,1.4109,1.4125,1.4172,1.4172,1.4188,1.4203,1.4219,1.4219,1.4219,1.4219,1.4219,1.4219,1.4219,1.4219,1.4219,1.4219,1.4203,1.4203,1.4203,1.4203,1.4203,1.4203,1.4203,\r\n011,blank.jpg,116,inCongMNL6non1,~2+.jpg,~8-.jpg,~2+.jpg,0,1,1110,32,2,0,0,13:01:22,,101,0.05,0.075,0.0766,0.0781,0.0797,0.0797,0.0828,0.0828,0.0859,0.0859,0.0875,0.0891,0.0906,0.0922,0.0938,0.0938,0.0953,0.0969,0.0984,0.1031,0.1141,0.1141,0.1359,0.2297,0.2297,0.3766,0.3766,0.4297,0.5031,0.55,0.6297,0.6719,0.7547,0.8016,0.8016,0.95,1,1,1.1203,1.1203,1.1609,1.2062,1.2312,1.2578,1.2766,1.2969,1.3125,1.3266,1.3344,1.3469,1.3469,1.3594,1.3625,1.3672,1.3672,1.3766,1.3766,1.3812,1.3859,1.3906,1.3969,1.4031,1.4141,1.4219,1.4266,1.4266,1.4266,1.4266,1.4266,1.4266,\r\n011,blank.jpg,117,CongiMNL6non1,~8+.jpg,~2-.jpg,~8+.jpg,0,1,1312,109,2,0,0,13:01:24,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0547,0.0578,0.0641,0.0688,0.0781,0.0844,0.0922,0.0922,0.0969,0.1156,0.1156,0.1438,0.1438,0.1969,0.1969,0.2266,0.2828,0.3234,0.3891,0.4531,0.5,0.5625,0.6109,0.6109,0.7297,0.7797,0.8453,0.8453,0.8891,0.9594,1.0016,1.0656,1.1094,1.1672,1.2141,1.2641,1.2969,1.3422,1.3719,1.4125,1.4125,1.4625,1.4625,1.475,1.4922,1.5,1.5,1.5,1.5,1.5,1.4969,1.4938,1.4844,1.4797,1.4688,1.4609,1.4609,1.4516,1.4359,1.4359,1.4297,1.4219,1.4188,1.4141,1.4109,1.4109,1.4094,1.4094,1.4094,1.4094,1.4094,1.4109,1.4109,1.4109,1.4109,1.4125,\r\n011,blank.jpg,118,CongMNL792,~2-.jpg,~9+.jpg,~9+.jpg,0,2,1234,78,1,0,0,13:01:27,,101,0.05,0.05,0.05,0.05,0.0547,0.0547,0.0562,0.0578,0.0609,0.0625,0.0672,0.0719,0.0844,0.0938,0.1078,0.1219,0.1438,0.1438,0.1969,0.225,0.225,0.2953,0.2953,0.3328,0.3969,0.4438,0.5219,0.5812,0.6719,0.7344,0.8234,0.9,0.9391,0.9922,0.9922,1.0672,1.0672,1.1078,1.1297,1.1594,1.1828,1.2156,1.2344,1.2656,1.2859,1.3109,1.3312,1.3609,1.3609,1.4062,1.4062,1.4203,1.4484,1.4484,1.4609,1.4703,1.4766,1.4797,1.4797,1.4797,1.475,1.475,1.4672,1.4672,1.4594,1.4562,1.4562,1.4531,1.4516,1.4484,1.4484,1.4469,1.4438,1.4422,1.4422,1.4391,1.4406,1.4406,1.4406,\r\n011,blank.jpg,119,inCongiMNL6non2,~8-.jpg,~2+.jpg,~2+.jpg,0,2,1562,156,1,0,0,13:01:29,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0469,0.0531,0.0531,0.0734,0.0734,0.0922,0.1078,0.1453,0.175,0.2281,0.2719,0.3422,0.3969,0.4797,0.5312,0.5312,0.6625,0.6625,0.7953,0.8578,0.8578,0.9047,0.9766,1.0297,1.1016,1.1406,1.1875,1.2156,1.2453,1.2609,1.2609,1.2797,1.2797,1.275,1.25,1.25,1.2469,1.2469,1.2453,1.2453,1.2453,1.2516,1.2609,1.2828,1.3031,1.3172,1.35,1.35,1.3938,1.3938,1.4094,1.4297,1.4375,1.4406,1.4406,1.4406,1.4375,1.4359,1.4359,1.4281,1.4219,1.4109,1.4109,1.3953,1.3906,1.3906,1.3906,1.3906,1.3906,1.3922,1.3953,1.3953,1.3969,1.3984,1.4016,1.4047,1.4047,1.4094,1.4125,1.4141,1.4141,1.4156,1.4188,1.4188,1.4203,1.4203,1.4203,1.4203,1.4203,1.4203,1.4203,\r\n011,blank.jpg,120,CongMNL6non2,~2-.jpg,~8+.jpg,~8+.jpg,0,2,1328,110,1,0,0,13:01:32,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.0375,0.0391,0.0422,0.0453,0.0516,0.0516,0.0672,0.1094,0.1094,0.1781,0.2062,0.2062,0.2516,0.2828,0.3328,0.3688,0.4188,0.4688,0.5469,0.6,0.6,0.7406,0.7406,0.8812,0.9703,0.9703,1.0156,1.0688,1.1281,1.1281,1.1547,1.1812,1.1969,1.2188,1.2344,1.2562,1.2734,1.2734,1.2906,1.3188,1.3188,1.3266,1.3328,1.3359,1.3359,1.3375,1.3375,1.3344,1.3328,1.3266,1.3219,1.3203,1.3188,1.3188,1.3188,1.3188,1.3188,1.3188,1.3203,1.3266,1.3344,1.3422,1.3516,1.3594,1.3672,1.3781,1.3859,1.3906,1.3969,1.3969,1.4031,1.4031,1.4062,1.4062,1.4062,1.4062,1.4062,1.4078,1.4094,\r\n011,blank.jpg,121,inCongMNL791,~2+.jpg,~9-.jpg,~2+.jpg,0,1,1437,140,2,0,0,13:01:34,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0203,0.0188,0.0172,0.0109,0.0109,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0016,0.0031,0.0297,0.05,0.05,0.125,0.125,0.1781,0.3,0.3,0.45,0.45,0.5172,0.6109,0.6812,0.7797,0.8406,0.9391,0.9953,1.0625,1.0625,1.1453,1.1453,1.1953,1.1953,1.2219,1.2391,1.2609,1.2734,1.2906,1.3031,1.3141,1.3203,1.3281,1.3312,1.3344,1.3344,1.3438,1.3438,1.3484,1.3641,1.3641,1.3766,1.3859,1.3984,1.4094,1.4203,1.4266,1.4297,1.4297,1.4297,1.4297,1.4297,1.4297,\r\n011,blank.jpg,122,CongiMNL81_91,~9+.jpg,~1-.jpg,~9+.jpg,0,1,1094,78,2,0,0,13:01:37,,101,0.0594,0.0594,0.0594,0.0594,0.0609,0.0609,0.0625,0.0625,0.0641,0.0641,0.0641,0.0656,0.0672,0.0672,0.0672,0.0703,0.0734,0.0797,0.0797,0.1047,0.1047,0.1484,0.1484,0.2328,0.2328,0.2906,0.3359,0.4078,0.4859,0.5469,0.6188,0.7141,0.7781,0.8625,0.9156,0.9891,1.0328,1.0328,1.1156,1.1156,1.1594,1.1859,1.2188,1.2438,1.2719,1.2906,1.3156,1.3297,1.3453,1.3578,1.3703,1.3766,1.3766,1.3844,1.3906,1.3906,1.4,1.4031,1.4062,1.4125,1.4156,1.4234,1.4266,1.4297,1.4297,1.4297,1.4297,1.4297,1.4297,1.4297,\r\n011,blank.jpg,123,inCongiMNL81_92,~9-.jpg,~1+.jpg,~1+.jpg,0,2,1390,31,1,0,0,13:01:40,,101,0.05,0.0453,0.0484,0.05,0.05,0.0562,0.0562,0.0641,0.075,0.0891,0.1125,0.1312,0.175,0.2031,0.25,0.2953,0.3266,0.375,0.4094,0.4094,0.4578,0.5297,0.5297,0.5781,0.6141,0.6656,0.7,0.7516,0.7844,0.8328,0.8656,0.9141,0.95,1.0141,1.0609,1.0609,1.175,1.175,1.2219,1.2484,1.275,1.2906,1.3031,1.3094,1.3156,1.3203,1.325,1.3328,1.3406,1.3469,1.3562,1.3641,1.3641,1.3906,1.3906,1.4109,1.425,1.4453,1.4578,1.4688,1.4766,1.4812,1.4828,1.4828,1.4828,1.4828,1.4828,1.4828,1.4812,1.4781,1.4734,1.4703,1.4641,1.4594,1.45,1.4453,1.4391,1.4375,1.4359,1.4359,1.4344,1.4344,1.4344,1.4344,1.4359,1.4359,1.4359,1.4359,1.4359,\r\n011,blank.jpg,124,CongiMNL111,~2+.jpg,~1-.jpg,~2+.jpg,0,1,1078,93,2,0,0,13:01:42,,101,0.05,0.05,0.05,0.05,0.05,0.0531,0.0531,0.0547,0.0562,0.0594,0.0625,0.0688,0.0688,0.0969,0.1203,0.1203,0.1469,0.1469,0.1594,0.1766,0.1953,0.2281,0.2453,0.2734,0.3,0.3453,0.3812,0.4453,0.4453,0.5641,0.5641,0.6953,0.7531,0.7531,0.8094,0.8828,0.9266,0.9891,1.0438,1.0844,1.1406,1.1828,1.2344,1.2344,1.3078,1.3078,1.3359,1.3531,1.3734,1.3859,1.3984,1.4062,1.4125,1.4125,1.4125,1.4125,1.4125,1.4125,1.4141,1.4172,1.4172,1.4219,1.4219,1.4219,1.4219,1.4219,1.4219,1.4234,1.4234,\r\n011,blank.jpg,125,CongiMNL791,~9+.jpg,~2-.jpg,~9+.jpg,0,1,1375,31,2,0,0,13:01:44,,101,0.0469,0.0484,0.0484,0.05,0.0547,0.0578,0.0641,0.0703,0.0781,0.0859,0.1,0.1,0.1297,0.1297,0.1453,0.1734,0.2,0.2453,0.2812,0.3375,0.375,0.4406,0.4828,0.5516,0.6016,0.6016,0.7438,0.7438,0.9031,0.9031,0.9562,1.0297,1.0906,1.1297,1.1859,1.2188,1.2672,1.2906,1.2906,1.3156,1.3156,1.3234,1.3453,1.3453,1.3625,1.3625,1.3828,1.3922,1.4094,1.425,1.4344,1.4438,1.4453,1.4453,1.4453,1.4453,1.4453,1.4422,1.4422,1.4406,1.4406,1.4406,1.4406,1.4406,1.4406,1.4406,1.4406,1.4422,1.4422,1.4422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47,0.9297,1.0484,1.1156,1.2141,1.2656,1.3266,1.3625,1.3828,1.4062,1.4062,1.4156,1.4328,1.4328,1.4469,1.4469,1.4531,1.4562,1.4609,1.4609,1.4609,1.4609,1.4609,1.4594,1.4578,1.4547,1.4547,1.45,1.45,1.4484,1.4469,1.4469,1.4438,1.4422,1.4422,1.4422,1.4422,1.4422,\r\n011,blank.jpg,143,inCongiMNL81_92,~9-.jpg,~1+.jpg,~1+.jpg,0,2,1234,31,1,0,0,13:02:29,,101,0.05,0.0438,0.0438,0.0453,0.0453,0.0469,0.0484,0.05,0.0516,0.0531,0.0562,0.0609,0.0703,0.0797,0.0984,0.1188,0.15,0.15,0.1812,0.2703,0.2703,0.3422,0.3984,0.4953,0.5625,0.6641,0.7312,0.8203,0.8703,0.9453,0.9922,0.9922,1.0906,1.0906,1.1734,1.1734,1.2219,1.2516,1.2906,1.3094,1.325,1.3438,1.3516,1.3578,1.3578,1.3578,1.3578,1.3578,1.3578,1.3578,1.3578,1.3578,1.3578,1.3578,1.3594,1.3609,1.3625,1.3656,1.3688,1.3703,1.3703,1.3734,1.3734,1.3766,1.3766,1.3828,1.3828,1.3891,1.3953,1.4031,1.4094,1.4188,1.4219,1.425,1.425,1.425,1.425,1.425,\r\n011,blank.jpg,144,CongMNL6non2,~2-.jpg,~8+.jpg,~8+.jpg,0,2,1547,31,1,0,0,13:02:31,,101,0.05,0.0641,0.0641,0.0625,0.0625,0.0625,0.0625,0.0625,0.0625,0.0625,0.0625,0.0625,0.0625,0.0625,0.0625,0.0625,0.0625,0.0625,0.0625,0.0625,0.0625,0.0625,0.0625,0.0625,0.0625,0.0625,0.0641,0.0672,0.0688,0.0766,0.0797,0.0844,0.0891,0.0938,0.1016,0.1094,0.1172,0.1359,0.1359,0.1766,0.1766,0.2,0.25,0.2812,0.3359,0.3719,0.4328,0.4797,0.5312,0.5688,0.6188,0.6531,0.6531,0.7266,0.7266,0.7688,0.8484,0.8484,0.8875,0.9359,0.9609,1,1.0172,1.0328,1.0531,1.0766,1.0953,1.0953,1.1391,1.1641,1.1797,1.1797,1.1938,1.2047,1.2172,1.225,1.2328,1.2391,1.2484,1.2562,1.2641,1.2703,1.2781,1.2875,1.2875,1.3125,1.3125,1.3234,1.3406,1.3531,1.3688,1.3797,1.3938,1.4031,1.4109,1.4156,1.4172,1.4219,1.4234,\r\n011,blank.jpg,145,inCongMNL791,~2+.jpg,~9-.jpg,~2+.jpg,0,1,1234,391,2,0,0,13:02:35,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0547,0.0547,0.0797,0.0938,0.0938,0.1578,0.1578,0.2109,0.2453,0.3,0.3344,0.3953,0.4453,0.5109,0.5578,0.625,0.675,0.675,0.7766,0.7766,0.8641,0.8641,0.9094,0.9406,0.9734,0.9922,1.0156,1.0344,1.0562,1.0719,1.0938,1.1094,1.1094,1.15,1.15,1.1906,1.2484,1.2484,1.2672,1.2969,1.3156,1.3375,1.35,1.3625,1.3688,1.3766,1.3812,1.3891,1.3891,1.3922,1.3922,1.3922,1.3922,1.3938,\r\n011,blank.jpg,146,inCongiMNL192,~9-.jpg,~8+.jpg,~8+.jpg,0,2,1203,94,1,0,0,13:02:38,,101,0.05,0.05,0.05,0.05,0.05,0.0453,0.0453,0.0469,0.0484,0.0484,0.0484,0.0516,0.0516,0.0516,0.0609,0.0609,0.0734,0.0734,0.0812,0.0969,0.1125,0.1469,0.175,0.2219,0.2734,0.3109,0.3781,0.4422,0.4422,0.6031,0.6031,0.6672,0.7672,0.8359,0.9172,0.9688,1.0344,1.0703,1.1156,1.1469,1.1781,1.1781,1.2203,1.2203,1.2562,1.2719,1.2719,1.2969,1.3141,1.3391,1.3578,1.3781,1.3906,1.4078,1.4203,1.4328,1.4328,1.4531,1.4531,1.4562,1.4594,1.4594,1.4594,1.4594,1.4594,1.4578,1.4562,1.4547,1.4516,1.4469,1.4453,1.4391,1.4359,1.4359,1.4312,1.4312,\r\n011,blank.jpg,147,inCongMNL111,~1+.jpg,~2-.jpg,~1+.jpg,0,1,1407,219,2,0,0,13:02:40,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0734,0.0734,0.0734,0.0734,0.0734,0.0734,0.075,0.075,0.075,0.075,0.0766,0.0766,0.0781,0.0781,0.0797,0.0828,0.0891,0.0969,0.1109,0.1344,0.1547,0.1953,0.225,0.2734,0.3234,0.3625,0.3625,0.4641,0.4641,0.5203,0.5578,0.6,0.6531,0.6875,0.7375,0.7719,0.8203,0.8469,0.8953,0.925,0.975,1.0188,1.0188,1.05,1.1203,1.1203,1.15,1.1938,1.2172,1.2469,1.2641,1.2875,1.3031,1.3156,1.325,1.325,1.3391,1.3484,1.3484,1.3625,1.3625,1.3812,1.3812,1.3875,1.3969,1.4062,1.4172,1.4234,1.4344,1.4438,1.4438,1.4484,1.4531,1.4531,1.4531,1.4531,1.4531,\r\n011,blank.jpg,148,CongMNL792,~2-.jpg,~9+.jpg,~9+.jpg,0,2,1328,109,1,0,0,13:02:43,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.0547,0.0547,0.0547,0.0547,0.0547,0.0547,0.0547,0.0547,0.0547,0.0578,0.0578,0.0594,0.0609,0.0625,0.0672,0.0703,0.0766,0.0844,0.0969,0.0969,0.1609,0.1609,0.2641,0.2641,0.325,0.4234,0.5016,0.5828,0.6875,0.75,0.8297,0.8719,0.9328,0.9797,1.0109,1.0484,1.0484,1.0906,1.0906,1.1094,1.1266,1.1469,1.1609,1.1859,1.2031,1.2234,1.2344,1.2516,1.2578,1.2688,1.2688,1.2859,1.2859,1.3047,1.3047,1.3156,1.3234,1.3328,1.3422,1.3469,1.3547,1.3594,1.3656,1.3719,1.3766,1.3844,1.3891,1.3969,1.4047,1.4047,1.4172,1.4172,1.4219,1.4281,1.4312,1.4312,1.4328,1.4328,1.4328,\r\n011,blank.jpg,149,CongMNL81_92,~1-.jpg,~9+.jpg,~9+.jpg,0,2,1297,344,1,0,0,13:02:46,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0359,0.0359,0.0469,0.0469,0.0562,0.075,0.0859,0.1094,0.125,0.1594,0.1875,0.2359,0.2719,0.3391,0.3984,0.4734,0.4734,0.5312,0.6875,0.6875,0.7828,0.8453,0.9234,0.9688,1.0297,1.0594,1.1,1.1219,1.1344,1.1531,1.1531,1.1781,1.1781,1.2,1.2,1.2094,1.2172,1.2297,1.2375,1.2453,1.2609,1.2719,1.2891,1.3016,1.3156,1.3156,1.3375,1.3375,1.3453,1.3641,1.3641,1.3703,1.3781,1.3875,1.3922,1.3984,1.4031,1.4031,1.4062,1.4062,1.4078,1.4078,\r\n011,blank.jpg,150,inCongMNL191,~8+.jpg,~9-.jpg,~8+.jpg,0,1,1406,78,2,0,0,13:02:48,,101,0.05,0.05,0.05,0.05,0.0266,0.0266,0.0266,0.0281,0.0312,0.0344,0.0375,0.0375,0.0406,0.0469,0.0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0.4438,0.5141,0.6328,0.7422,0.8141,0.8797,0.9422,0.9781,1.0203,1.0203,1.0625,1.0625,1.0922,1.0922,1.1047,1.1281,1.1422,1.1672,1.1875,1.2172,1.2359,1.2625,1.2812,1.3047,1.3047,1.3422,1.3422,1.3797,1.3797,1.4125,1.4125,1.425,1.4422,1.4531,1.4625,1.4703,1.475,1.475,1.475,1.475,1.4766,1.4766,1.4766,1.4766,1.4766,\r\n011,blank.jpg,167,CongMNL192,~8-.jpg,~9+.jpg,~9+.jpg,0,2,1360,78,1,0,0,13:03:30,,101,0.05,0.05,0.05,0.05,0.0453,0.0453,0.0453,0.0469,0.0469,0.0469,0.0469,0.0484,0.0484,0.05,0.0516,0.0531,0.0594,0.0719,0.0891,0.1047,0.1266,0.1453,0.1797,0.2062,0.2516,0.2516,0.3453,0.3453,0.4219,0.4797,0.5719,0.6438,0.7125,0.8172,0.8812,0.9719,1.0234,1.0859,1.1266,1.1781,1.1781,1.2094,1.275,1.275,1.2922,1.3031,1.3156,1.3203,1.3234,1.3266,1.3281,1.3281,1.3297,1.3328,1.3328,1.3328,1.3406,1.3406,1.35,1.3562,1.3672,1.3734,1.3875,1.3969,1.4141,1.425,1.4391,1.4453,1.4484,1.4484,1.4484,1.4484,1.4484,1.4453,1.4453,1.4391,1.4359,1.4359,1.4359,1.4359,1.4359,1.4359,1.4359,1.4359,1.4359,1.4359,1.4359,\r\n011,blank.jpg,168,CongMNL792,~2-.jpg,~9+.jpg,~9+.jpg,0,2,1500,78,1,0,0,13:03:32,,101,0.05,0.05,0.05,0.05,0.075,0.075,0.0781,0.0781,0.0797,0.0844,0.0906,0.0984,0.1109,0.1297,0.1594,0.1844,0.2297,0.2297,0.3297,0.3297,0.4562,0.4562,0.55,0.6125,0.7047,0.7609,0.8359,0.8812,0.9406,0.9734,1.0172,1.0469,1.0469,1.1031,1.1031,1.1359,1.1516,1.175,1.1938,1.2141,1.2328,1.2672,1.2844,1.3062,1.3234,1.3438,1.3594,1.3734,1.3797,1.3797,1.3906,1.3906,1.3953,1.3969,1.3969,1.3969,1.3969,1.3984,1.4094,1.4203,1.4344,1.4406,1.4406,1.4547,1.4547,1.4594,1.4625,1.4625,1.4641,1.4641,1.4641,1.4641,1.4656,1.4656,1.4656,1.4656,1.4656,1.4656,1.4656,1.4656,1.4656,1.4531,1.4531,1.4406,1.4406,1.4375,1.4375,1.4375,1.4375,1.4375,1.4375,1.4359,1.4359,1.4359,1.4375,1.4375,\r\n011,blank.jpg,169,inCongMNL111,~1+.jpg,~2-.jpg,~1+.jpg,0,1,1109,156,2,0,0,13:03:34,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0438,0.0469,0.0562,0.0688,0.0859,0.0859,0.1391,0.1391,0.2172,0.2172,0.2594,0.3359,0.3922,0.4781,0.5328,0.6062,0.6484,0.7125,0.7484,0.7984,0.8281,0.8281,0.8797,0.8797,0.9031,0.9297,0.9297,0.9469,0.9594,0.9734,0.9828,0.9953,1.0125,1.0234,1.0438,1.0656,1.1047,1.1047,1.1703,1.1703,1.2078,1.2328,1.2734,1.2734,1.2984,1.3156,1.3391,1.3547,1.3734,1.3828,1.3953,1.4031,1.4109,1.4109,1.4203,1.4203,1.4219,1.4219,1.4219,1.4219,1.4219,1.4219,\r\n011,blank.jpg,170,inCongiMNL112,~2-.jpg,~1+.jpg,~1+.jpg,0,2,1375,63,1,0,0,13:03:36,,101,0.05,0.05,0.05,0.0875,0.0906,0.0906,0.0953,0.0953,0.1,0.1,0.1016,0.1016,0.1016,0.1062,0.1125,0.1188,0.1266,0.1484,0.1719,0.2219,0.2219,0.375,0.375,0.4594,0.5828,0.675,0.7969,0.8594,0.95,0.9969,1.0609,1.0984,1.1422,1.1672,1.1859,1.1859,1.2172,1.2172,1.2297,1.2484,1.2609,1.2828,1.2984,1.3234,1.3375,1.3625,1.3797,1.4,1.4141,1.4312,1.4312,1.4391,1.45,1.4547,1.4578,1.4578,1.4578,1.4578,1.4516,1.4469,1.4438,1.4422,1.4406,1.4391,1.4391,1.4375,1.4344,1.4344,1.4344,1.4344,1.4344,1.4344,1.4344,1.4344,1.4344,1.4344,1.4344,1.4344,1.4344,1.4344,1.4344,1.4281,1.4281,1.425,1.4219,1.4219,1.4219,1.4219,\r\n011,blank.jpg,171,inCongMNL81_91,~1+.jpg,~9-.jpg,~1+.jpg,0,1,1469,344,2,0,0,13:03:39,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0234,0.025,0.025,0.0266,0.0266,0.0328,0.0328,0.0438,0.0438,0.0516,0.0609,0.0719,0.0953,0.1266,0.1703,0.2062,0.2656,0.3109,0.3781,0.4219,0.4219,0.525,0.525,0.5781,0.6172,0.6688,0.7016,0.7469,0.7812,0.8266,0.8562,0.9,0.9297,0.9734,1.0016,1.0016,1.0781,1.0781,1.1062,1.1469,1.1766,1.2203,1.2484,1.2906,1.3156,1.3469,1.3719,1.3891,1.4031,1.4172,1.4172,1.4219,1.4266,1.4266,1.4266,1.4266,1.4266,1.4266,1.4203,1.4141,1.4109,1.4094,1.4094,1.4094,1.4094,1.4094,1.4094,1.4094,1.4094,1.4109,1.4109,1.4109,1.4125,\r\n011,blank.jpg,172,CongiMNL791,~9+.jpg,~2-.jpg,~9+.jpg,0,1,1468,140,2,0,0,13:03:41,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0422,0.0422,0.0422,0.0422,0.0422,0.0422,0.0438,0.0438,0.0453,0.0469,0.0484,0.0484,0.0484,0.0484,0.0484,0.05,0.05,0.05,0.05,0.05,0.05,0.0531,0.0531,0.0531,0.0547,0.0609,0.0734,0.1062,0.1328,0.1766,0.2156,0.2719,0.3109,0.3109,0.3984,0.3984,0.4812,0.5281,0.5281,0.5656,0.6219,0.6609,0.7188,0.7594,0.8094,0.8422,0.8906,0.9188,0.9188,0.9922,0.9922,1.0375,1.0656,1.1047,1.1328,1.1688,1.1875,1.2109,1.2297,1.2516,1.2656,1.2812,1.2906,1.3031,1.3125,1.3125,1.3297,1.3297,1.3391,1.3484,1.3547,1.3656,1.3719,1.3797,1.3859,1.3969,1.4031,1.4078,1.4078,1.4109,1.4109,1.4109,1.4125,1.4125,1.4141,1.4141,\r\n011,blank.jpg,173,CongiMNL111,~2+.jpg,~1-.jpg,~2+.jpg,0,1,1343,203,2,0,0,13:03:44,,101,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.0422,0.0422,0.0312,0.0312,0.0312,0.0312,0.0312,0.0312,0.0312,0.0312,0.0312,0.0312,0.0281,0.0281,0.0297,0.0453,0.0453,0.0875,0.1797,0.1797,0.2797,0.2797,0.3203,0.3703,0.4016,0.4469,0.4812,0.5297,0.5578,0.6078,0.6406,0.6891,0.6891,0.7719,0.7719,0.8094,0.8547,0.8844,0.9281,0.9516,0.9828,1.0047,1.0391,1.0656,1.1031,1.1328,1.1328,1.1906,1.1906,1.2234,1.2656,1.2656,1.2797,1.3031,1.3141,1.3344,1.3438,1.3562,1.3641,1.3672,1.3734,1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.jpg,~2+.jpg,0,1,1141,32,2,0,0,13:04:47,,101,0.05,0.0406,0.0406,0.0406,0.0422,0.0438,0.0453,0.0516,0.0641,0.1016,0.1359,0.1891,0.2297,0.3125,0.3125,0.5047,0.5047,0.5922,0.7312,0.8203,0.9609,1.0641,1.1406,1.2469,1.3312,1.375,1.4234,1.4234,1.4625,1.4625,1.4828,1.4828,1.4859,1.4859,1.4859,1.4844,1.4844,1.4844,1.4828,1.4828,1.4859,1.4859,1.4969,1.4969,1.4969,1.4984,1.4984,1.4844,1.4844,1.4672,1.4562,1.4406,1.4297,1.4188,1.4109,1.4047,1.4047,1.4047,1.4047,1.4078,1.4078,1.4125,1.4125,1.4125,1.4125,1.4125,1.4125,1.4141,1.4141,1.4141,1.4141,1.4156,1.4156,\r\n011,blank.jpg,198,inCongMNL111,~1+.jpg,~2-.jpg,~1+.jpg,0,1,1187,31,2,0,0,13:04:49,,101,0.0484,0.0484,0.0484,0.0484,0.0484,0.05,0.0531,0.0594,0.0703,0.0703,0.1062,0.1062,0.1719,0.1719,0.2328,0.2922,0.3906,0.4703,0.6,0.6891,0.8219,0.9328,0.9906,1.0641,1.1047,1.1422,1.1422,1.1828,1.2203,1.2203,1.2328,1.25,1.2609,1.2781,1.2938,1.3062,1.3156,1.325,1.3297,1.3297,1.3375,1.3375,1.3375,1.3375,1.3375,1.3391,1.3391,1.3406,1.3453,1.35,1.3547,1.3594,1.3625,1.3656,1.3672,1.3688,1.3688,1.3703,1.3703,1.3734,1.375,1.3812,1.3859,1.3906,1.3984,1.4047,1.4141,1.4203,1.4266,1.4297,1.4312,1.4312,1.4312,1.4312,1.4312,\r\n011,blank.jpg,199,CongiMNL191,~9+.jpg,~8-.jpg,~9+.jpg,0,1,1328,78,2,0,0,13:04:51,,101,0.05,0.05,0.05,0.05,0.0609,0.0672,0.0672,0.0828,0.1016,0.1422,0.1844,0.2344,0.3297,0.4109,0.5344,0.6234,0.6234,0.8438,0.8438,0.9734,1.0656,1.1938,1.3047,1.3641,1.4047,1.4469,1.4672,1.4891,1.4984,1.5,1.5,1.5,1.5,1.5,1.5,1.5,1.4953,1.4797,1.4656,1.4422,1.4219,1.4016,1.3922,1.3891,1.3891,1.3875,1.3875,1.3875,1.3922,1.3922,1.3969,1.4062,1.4125,1.4203,1.425,1.4297,1.4312,1.4328,1.4328,1.4328,1.4328,1.4328,1.4328,1.4328,1.4328,1.4297,1.4297,1.4266,1.4234,1.4234,1.4219,1.4219,1.4219,1.4219,1.4219,1.4234,1.4234,1.4234,1.4234,1.4234,1.4234,1.4234,1.4266,1.4266,1.4266,\r\n011,blank.jpg,200,CongiMNL6non1,~8+.jpg,~2-.jpg,~8+.jpg,0,1,1031,31,2,0,0,13:04:53,,101,0.05,0.0422,0.0422,0.0438,0.0453,0.0469,0.0516,0.0578,0.0719,0.0844,0.0844,0.1141,0.1812,0.1812,0.2469,0.3047,0.4156,0.4984,0.6297,0.7141,0.8438,0.9234,1.0375,1.1125,1.1125,1.2062,1.3312,1.3312,1.3672,1.4094,1.4344,1.4594,1.4703,1.4859,1.4891,1.4969,1.4969,1.4969,1.4969,1.4969,1.4969,1.4969,1.4969,1.4969,1.4984,1.4953,1.4891,1.4797,1.4688,1.4594,1.4547,1.45,1.4469,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4453,1.4469,1.4469,1.4469,1.4469,\r\n\r\n\r\nRAW TRACKS (X coordinates)\r\nsubjID,stim,order,condition,resp_1,resp_2,response,error,resp_num,RT,init time,distractor,ideal y-int,maxdev,real time,comments,timestamps,\r\n011,instruct.jpg,1,instruct,,,,0,,0,0,,0,0,12:55:52,,101,\r\n011,blank.jpg,2,inCongiMNL712,~8-.jpg,~1+.jpg,~1+.jpg,0,2,1719,78,1,0,0,12:56:19,,101,640,640,640,640,629,629,629,628,627,627,627,627,627,627,627,627,627,627,627,627,627,627,627,627,627,627,627,627,627,628,628,635,636,636,637,637,642,656,669,694,717,757,794,866,911,950,950,984,984,1010,1010,1017,1022,1022,1020,1016,1014,1014,1018,1025,1030,1030,1049,1049,1065,1078,1100,1116,1138,1153,1158,1161,1164,1167,1169,1169,1170,1170,1171,1174,1174,1179,1183,1187,1187,1189,1191,1195,1197,1201,1205,1208,1211,1211,1212,1212,1213,1213,1213,1213,1213,1213,1213,1213,1213,1213,1213,1213,1213,1213,\r\n011,blank.jpg,3,CongMNL792,~2-.jpg,~9+.jpg,~9+.jpg,0,2,1266,219,1,0,0,12:56:22,,101,640,640,640,640,640,640,640,640,640,640,640,640,640,659,659,659,659,659,659,670,670,687,702,724,736,752,763,777,777,802,802,826,826,848,848,859,875,883,892,898,910,921,935,935,957,957,984,984,995,1011,1021,1036,1046,1063,1079,1101,1116,1139,1155,1172,1179,1179,1184,1184,1187,1191,1193,1194,1194,1195,1196,1197,1197,1197,1197,1197,1197,1197,1197,1197,1197,\r\n011,blank.jpg,4,CongiMNL711,~8+.jpg,~1-.jpg,~8+.jpg,0,1,1328,156,2,0,0,12:56:25,,101,640,640,640,640,640,640,640,640,640,629,629,629,629,629,629,629,630,636,636,651,640,640,621,570,570,546,527,488,457,396,348,265,200,158,158,133,127,127,123,122,124,128,136,140,141,141,141,137,128,116,116,101,101,96,96,96,96,96,96,96,96,95,93,90,84,84,65,65,58,55,55,55,55,54,54,54,54,54,54,54,54,54,54,54,54,\r\n011,blank.jpg,5,CongMNL6non2,~2-.jpg,~8+.jpg,~8+.jpg,0,2,1297,265,1,0,0,12:56:28,,101,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,637,649,649,686,686,712,729,761,785,822,847,880,902,902,943,943,967,967,981,991,1005,1010,1018,1021,1028,1036,1045,1054,1061,1061,1074,1074,1078,1090,1090,1098,1106,1112,1121,1124,1129,1131,1134,1137,1138,1138,1140,1140,1149,1149,1156,1167,1177,1185,1189,1196,1199,1203,1205,1208,1208,1208,1208,1208,1208,1208,1208,\r\n011,blank.jpg,6,CongMNL81_92,~1-.jpg,~9+.jpg,~9+.jpg,0,2,1343,297,1,0,0,12:56:30,,101,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,650,650,653,653,661,673,704,728,770,798,842,866,899,922,955,975,975,1009,1009,1021,1030,1040,1046,1059,1068,1082,1090,1103,1110,1123,1130,1130,1135,1138,1140,1145,1154,1159,1168,1172,1182,1188,1196,1204,1208,1208,1213,1218,1218,1220,1223,1224,1224,1224,1222,1219,1217,1215,1214,1214,1213,1213,1213,1213,1212,1211,1211,\r\n011,blank.jpg,7,inCongiMNL792,~9-.jpg,~2+.jpg,~2+.jpg,0,2,1219,156,1,0,0,12:56:33,,101,640,640,640,640,640,640,640,640,640,650,651,654,661,668,680,691,691,719,729,729,742,742,736,723,688,638,604,533,490,456,446,447,463,488,558,558,619,715,779,854,890,924,946,978,999,1020,1020,1047,1047,1073,1082,1082,1095,1101,1113,1122,1134,1142,1152,1156,1159,1159,1165,1165,1178,1178,1186,1186,1191,1196,1196,1196,1198,1197,1197,1198,1198,1198,\r\n011,blank.jpg,8,inCongiMNL6non2,~8-.jpg,~2+.jpg,~2+.jpg,0,2,1469,188,1,0,0,12:56:35,,101,640,640,640,640,640,640,640,640,640,640,640,624,624,624,625,625,626,626,626,626,629,629,629,630,633,638,650,683,708,742,761,796,816,851,871,871,917,940,940,966,966,977,986,988,992,995,999,1001,1004,1006,1012,1012,1025,1025,1043,1043,1050,1055,1063,1071,1075,1081,1085,1094,1101,1111,1111,1136,1136,1148,1152,1157,1162,1171,1176,1183,1189,1197,1200,1202,1202,1202,1202,1202,1203,1203,1204,1204,1205,1205,1205,1205,1206,1206,\r\n011,blank.jpg,9,inCongMNL711,~1+.jpg,~8-.jpg,~1+.jpg,0,1,1422,234,2,0,0,12:56:37,,101,640,640,640,640,640,640,640,640,640,640,640,640,640,640,674,674,674,675,675,674,666,656,647,643,642,642,642,646,646,641,627,594,555,484,436,378,356,334,329,329,323,323,307,293,293,282,282,280,274,266,253,234,200,174,144,132,132,123,114,114,112,108,104,97,94,89,84,77,70,67,63,63,55,55,52,51,50,50,50,49,49,49,49,48,48,48,47,47,47,47,47,\r\n011,blank.jpg,10,CongiMNL81_91,~9+.jpg,~1-.jpg,~9+.jpg,0,1,1781,266,2,0,0,12:56:40,,101,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,645,643,643,639,639,639,639,641,641,641,633,615,583,560,526,495,448,412,412,351,351,343,338,338,336,334,330,321,310,287,273,253,242,214,214,192,133,133,93,69,45,40,38,38,38,42,49,55,56,57,57,58,58,58,59,60,62,64,66,69,71,73,73,73,73,73,73,72,72,70,70,69,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,67,68,69,69,69,\r\n011,blank.jpg,11,CongiMNL111,~2+.jpg,~1-.jpg,~2+.jpg,0,1,1250,156,2,0,0,12:56:44,,101,640,640,640,640,640,640,640,640,640,611,611,611,611,611,610,610,610,610,610,609,609,607,607,591,591,577,569,554,535,498,470,429,429,401,338,338,304,252,252,243,235,235,230,225,217,211,202,195,181,181,157,157,136,136,129,116,109,99,95,87,82,76,67,61,57,57,51,51,47,45,42,41,41,40,39,39,38,38,38,\r\n011,blank.jpg,12,CongMNL192,~8-.jpg,~9+.jpg,~9+.jpg,0,2,1109,265,1,0,0,12:56:47,,101,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,689,689,689,690,693,704,721,737,737,786,786,831,831,860,884,919,949,969,1004,1025,1059,1078,1105,1105,1125,1150,1150,1173,1173,118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TRACKS (Y coordinates)\r\nsubjID,stim,order,condition,resp_1,resp_2,response,error,resp_num,RT,init time,distractor,ideal y-int,maxdev,real 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ngMNL81_91,~1+.jpg,~9-.jpg,~1+.jpg,0,1,1469,172,2,0,0,12:57:27,,101,928,928,928,928,928,928,928,928,928,928,934,931,931,886,886,832,798,746,711,651,609,553,516,463,428,384,357,357,308,291,291,267,267,260,253,249,242,237,232,228,225,225,222,222,222,221,221,218,218,210,204,192,181,158,135,105,105,85,43,43,23,0,0,0,0,0,0,0,0,0,0,1,3,8,15,15,25,25,30,33,34,35,35,35,35,35,35,35,35,35,35,34,34,34,\r\n011,blank.jpg,29,CongiMNL81_91,~9+.jpg,~1-.jpg,~9+.jpg,0,1,1156,78,2,0,0,12:57:29,,101,928,928,928,928,920,917,908,888,868,868,818,818,788,669,669,589,506,453,388,353,317,276,252,224,214,204,202,202,200,200,199,199,206,208,207,202,190,180,159,147,133,133,116,116,104,104,102,101,99,98,97,93,89,79,71,64,64,60,56,56,56,56,56,55,55,54,53,53,53,52,52,52,52,\r\n011,blank.jpg,30,inCongiMNL712,~8-.jpg,~1+.jpg,~1+.jpg,0,2,1156,156,1,0,0,12:57:32,,101,928,928,928,928,928,928,928,928,928,924,924,920,908,889,876,860,831,789,758,709,684,647,617,566,566,520,427,427,399,328,328,287,260,227,205,175,147,129,103,85,85,56,56,37,37,32,28,28,26,26,26,26,27,27,28,28,28,28,28,28,28,29,31,34,36,37,38,38,38,39,39,39,39,39,\r\n011,blank.jpg,31,CongiMNL791,~9+.jpg,~2-.jpg,~9+.jpg,0,1,1266,125,2,0,0,12:57:34,,101,928,928,928,928,928,928,928,923,923,923,923,923,922,922,921,921,921,920,918,913,913,907,885,885,866,849,818,793,755,723,661,619,554,515,461,461,381,381,349,292,292,259,259,251,240,234,232,227,223,218,218,203,203,185,185,175,169,157,149,138,129,116,104,91,84,84,67,67,51,51,43,38,32,29,29,29,28,28,28,28,28,\r\n011,blank.jpg,32,inCongMNL6non1,~2+.jpg,~8-.jpg,~2+.jpg,0,1,1312,109,2,0,0,12:57:36,,101,928,928,928,928,928,928,941,941,937,937,936,933,929,921,921,917,909,901,889,882,861,841,841,815,762,762,720,687,642,612,569,541,499,471,428,396,359,336,336,280,280,251,236,221,213,201,195,186,179,172,167,160,155,155,148,138,138,123,123,117,109,102,92,87,80,74,67,67,59,59,52,52,49,48,45,44,44,44,44,44,44,44,44,44,\r\n011,blank.jpg,33,CongiMNL111,~2+.jpg,~1-.jpg,~2+.jpg,0,1,1047,125,2,0,0,12:57:39,,101,928,928,928,928,928,928,928,934,934,926,926,920,902,902,890,879,854,834,800,777,738,710,670,670,609,586,586,528,528,472,472,442,423,395,377,351,332,308,292,292,248,248,205,205,182,166,145,130,109,96,79,67,52,43,43,29,25,25,22,22,22,22,21,21,21,21,21,\r\n011,blank.jpg,34,inCongiMNL792,~9-.jpg,~2+.jpg,~2+.jpg,0,2,1250,31,1,0,0,12:57:41,,101,940,938,936,935,935,934,929,929,924,920,911,902,892,885,872,862,840,840,785,762,762,710,710,679,657,619,599,570,549,518,498,466,444,411,388,388,326,297,297,280,250,230,204,189,171,159,139,127,127,106,106,100,88,88,83,80,80,81,81,82,82,82,82,82,81,81,78,78,68,68,61,53,50,49,48,48,48,48,48,\r\n011,blank.jpg,35,CongMNL112,~1-.jpg,~2+.jpg,~2+.jpg,0,2,1578,344,1,0,0,12:57:43,,101,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,945,944,918,885,821,787,744,717,671,632,632,530,530,487,455,418,398,370,353,332,323,308,306,299,299,288,288,284,280,280,272,265,255,250,241,233,223,215,201,194,194,180,153,153,138,122,105,94,79,70,54,45,31,22,18,18,15,15,15,16,16,20,20,24,28,31,37,39,43,46,46,48,50,49,49,49,49,50,48,\r\n011,blank.jpg,36,CongMNL81_92,~1-.jpg,~9+.jpg,~9+.jpg,0,2,1468,156,1,0,0,12:57:46,,101,928,928,928,928,928,928,928,928,928,923,923,922,922,920,918,912,906,891,879,851,830,786,758,758,697,697,663,636,594,569,534,512,482,467,449,441,432,432,418,418,413,399,399,388,381,370,360,346,333,321,304,285,271,255,243,243,217,217,202,192,175,165,151,132,120,100,88,76,67,67,54,54,51,51,51,51,51,51,48,47,46,46,46,44,44,43,43,43,43,43,43,43,43,43,\r\n011,blank.jpg,37,CongiMNL711,~8+.jpg,~1-.jpg,~8+.jpg,0,1,1907,266,2,0,0,12:57:48,,101,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,947,943,937,920,920,854,854,807,730,730,689,626,579,518,479,431,403,367,344,317,301,301,277,277,260,250,232,216,196,184,168,159,143,132,118,108,108,89,89,80,75,68,64,59,56,52,48,45,43,42,42,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,40,40,40,40,40,40,40,\r\n011,blank.jpg,38,inCongMNL791,~2+.jpg,~9-.jpg,~2+.jpg,0,1,1172,63,2,0,0,12:57:51,,101,928,928,928,916,916,917,917,917,917,917,917,917,917,916,916,914,914,899,899,890,875,863,835,812,774,723,689,689,601,601,525,525,448,448,423,384,356,320,295,264,248,228,217,202,191,191,171,171,160,151,142,137,131,128,123,118,112,107,100,94,87,81,81,69,69,64,61,61,59,59,59,59,59,59,\r\n011,blank.jpg,39,inCongiMNL81_92,~9-.jpg,~1+.jpg,~1+.jpg,0,2,1328,63,1,0,0,12:57:53,,101,928,928,928,937,937,937,937,936,935,933,931,929,925,920,915,902,902,869,869,852,825,808,779,747,724,689,661,630,586,556,512,479,479,434,371,371,301,301,273,228,200,164,144,111,88,88,49,31,23,23,12,6,1,0,0,0,0,0,0,0,0,1,1,7,7,14,24,24,27,29,30,30,31,32,32,32,32,35,34,40,40,42,42,42,\r\n011,blank.jpg,40,inCongMNL111,~1+.jpg,~2-.jpg,~1+.jpg,0,1,1031,125,2,0,0,12:57:56,,101,928,928,928,928,928,928,928,928,928,928,926,923,919,908,900,884,868,837,813,775,741,741,628,628,548,494,418,374,318,289,258,239,21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68,834,816,816,771,771,747,706,676,626,588,530,490,433,384,359,325,325,277,277,251,237,218,203,182,170,150,137,121,108,89,89,60,60,51,33,33,25,19,15,13,13,13,16,16,21,21,26,28,28,30,31,33,33,34,36,37,37,39,38,38,38,\r\n011,blank.jpg,119,inCongiMNL6non2,~8-.jpg,~2+.jpg,~2+.jpg,0,2,1562,156,1,0,0,13:01:29,,101,928,928,928,928,928,928,928,928,928,930,926,926,913,913,901,891,867,848,814,786,741,706,653,620,620,536,536,451,411,411,381,335,301,255,230,200,182,163,153,153,141,141,144,160,160,162,162,163,163,163,159,153,139,126,117,96,96,68,68,58,45,40,38,38,38,40,41,41,46,50,57,57,67,70,70,70,70,70,69,67,67,66,65,63,61,61,58,56,55,55,54,52,52,51,51,51,51,51,51,51,\r\n011,blank.jpg,120,CongMNL6non2,~2-.jpg,~8+.jpg,~8+.jpg,0,2,1328,110,1,0,0,13:01:32,,101,928,928,928,928,928,928,936,935,933,931,927,927,917,890,890,846,828,828,799,779,747,724,692,660,610,576,576,486,486,396,339,339,310,276,238,238,221,204,194,180,170,156,145,145,134,116,116,111,107,105,105,104,104,106,107,111,114,115,116,116,116,116,116,116,115,111,106,101,95,90,85,78,73,70,66,66,62,62,60,60,60,60,60,59,58,\r\n011,blank.jpg,121,inCongMNL791,~2+.jpg,~9-.jpg,~2+.jpg,0,1,1437,140,2,0,0,13:01:34,,101,928,928,928,928,928,928,928,928,947,948,949,953,953,959,959,959,959,959,959,959,959,959,959,959,959,959,959,959,959,959,959,959,959,959,959,959,959,959,959,958,941,928,928,880,880,846,768,768,672,672,629,569,524,461,422,359,323,280,280,227,227,195,195,178,167,153,145,134,126,119,115,110,108,106,106,100,100,97,87,87,79,73,65,58,51,47,45,45,45,45,45,45,\r\n011,blank.jpg,122,CongiMNL81_91,~9+.jpg,~1-.jpg,~9+.jpg,0,1,1094,78,2,0,0,13:01:37,,101,922,922,922,922,921,921,920,920,919,919,919,918,917,917,917,915,913,909,909,893,893,865,865,811,811,774,745,699,649,610,564,503,462,408,374,327,299,299,246,246,218,201,180,164,146,134,118,109,99,91,83,79,79,74,70,70,64,62,60,56,54,49,47,45,45,45,45,45,45,45,\r\n011,blank.jpg,123,inCongiMNL81_92,~9-.jpg,~1+.jpg,~1+.jpg,0,2,1390,31,1,0,0,13:01:40,,101,928,931,929,928,928,924,924,919,912,903,888,876,848,830,800,771,751,720,698,698,667,621,621,590,567,534,512,479,458,427,406,375,352,311,281,281,208,208,178,161,144,134,126,122,118,115,112,107,102,98,92,87,87,70,70,57,48,35,27,20,15,12,11,11,11,11,11,11,12,14,17,19,23,26,32,35,39,40,41,41,42,42,42,42,41,41,41,41,41,\r\n011,blank.jpg,124,CongiMNL111,~2+.jpg,~1-.jpg,~2+.jpg,0,1,1078,93,2,0,0,13:01:42,,101,928,928,928,928,928,926,926,925,924,922,920,916,916,898,883,883,866,866,858,847,835,814,803,785,768,739,716,675,675,599,599,515,478,478,442,395,367,327,292,266,230,203,170,170,123,123,105,94,81,73,65,60,56,56,56,56,56,56,55,53,53,50,50,50,50,50,50,49,49,\r\n011,blank.jpg,125,CongiMNL791,~9+.jpg,~2-.jpg,~9+.jpg,0,1,1375,31,2,0,0,13:01:44,,101,930,929,929,928,925,923,919,915,910,905,896,896,877,877,867,849,832,803,780,744,720,678,651,607,575,575,484,484,382,382,348,301,262,237,201,180,149,134,134,118,118,113,99,99,88,88,75,69,58,48,42,36,35,35,35,35,35,37,37,38,38,38,38,38,38,38,38,37,37,37,37,37,37,37,37,37,37,38,38,39,40,41,41,41,41,41,41,41,\r\n011,break.jpg,126,,,,,0,,0,0,,0,0,13:01:47,,101,\r\n011,blank.jpg,127,inCongiMNL112,~2-.jpg,~1+.jpg,~1+.jpg,0,2,1313,63,1,0,0,13:01:48,,101,928,928,928,944,944,942,942,940,938,935,930,926,919,912,912,888,862,862,801,801,774,728,699,650,616,564,529,479,442,412,366,366,307,307,279,224,224,195,154,128,96,81,72,61,57,57,47,47,44,42,42,42,39,38,35,32,27,23,21,20,20,20,20,19,19,21,30,30,33,33,33,33,34,34,35,36,39,39,40,40,40,40,40,41,\r\n011,blank.jpg,128,CongiMNL81_91,~9+.jpg,~1-.jpg,~9+.jpg,0,1,1297,31,2,0,0,13:01:51,,101,928,919,919,915,910,899,889,868,850,818,785,735,699,644,644,607,509,509,447,402,334,293,231,184,131,100,61,61,11,0,0,0,0,0,0,0,0,3,4,5,7,16,21,29,29,43,43,46,49,51,53,53,53,53,51,49,49,47,46,46,46,46,46,43,43,43,43,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,\r\n011,blank.jpg,129,inCongMNL6non1,~2+.jpg,~8-.jpg,~2+.jpg,0,1,1188,63,2,0,0,13:01:53,,101,934,934,934,934,934,929,929,918,918,907,897,875,856,822,796,750,716,659,659,534,472,472,421,346,301,232,193,135,90,63,24,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,3,3,3,8,8,11,11,16,19,21,24,29,33,36,37,37,39,40,40,40,40,40,40,40,40,40,\r\n011,blank.jpg,130,CongMNL712,~1-.jpg,~8+.jpg,~8+.jpg,0,2,1656,93,1,0,0,13:01:55,,101,928,928,928,928,928,920,919,917,911,904,895,875,875,858,803,803,763,684,684,647,585,558,507,458,387,341,276,241,241,148,148,75,75,45,28,14,4,0,0,0,0,0,0,0,0,0,0,0,1,3,6,10,20,26,27,28,28,27,20,20,8,8,1,0,0,0,0,0,0,0,0,0,1,4,4,10,10,13,14,16,18,22,22,24,25,27,29,29,30,30,30,30,30,30,30,30,30,31,31,31,31,31,31,31,31,\r\n011,blank.jpg,131,CongMNL192,~8-.jpg,~9+.jpg,~9+.jpg,0,2,1125,63,1,0,0,13:01:59,,101,928,928,928,919,918,914,907,892,874,856,856,856,856,856,856,856,856,856,856,856,856,856,854,850,824,776,739,677,630,630,501,501,438,360,312,245,207,159,127,106,82,72,60,51,44,37,37,27,27,22,18,15,9,6,6,6,7,13,18,18,28,28,33,35,35,36,35,35,35,35,35,35,\r\n011,blank.jpg,132,inCongiMNL6non2,~8-.jpg,~2+.jpg,~2+.jpg,0,2,1438,63,1,0,0,13:02:01,,101,928,928,928,923,922,921,918,915,910,910,897,897,890,864,864,825,825,806,773,751,714,683,636,588,550,517,468,468,389,389,359,319,291,253,228,200,184,168,157,146,146,132,132,119,115,115,113,113,112,112,112,110,103,96,83,74,59,59,53,39,39,37,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,37,39,40,41,41,42,42,42,42,42,42,42,42,\r\n011,blank.jpg,133,inCongiMNL712,~8-.jpg,~1+.jpg,~1+.jpg,0,2,1797,94,1,0,0,13:02:04,,101,939,939,939,939,939,938,936,936,934,931,924,916,898,880,855,837,837,785,785,725,725,646,646,594,555,512,483,441,411,369,338,302,282,258,247,247,226,226,220,212,207,200,193,186,180,169,162,151,140,124,124,112,97,87,74,68,60,55,48,44,39,34,33,32,32,32,32,32,32,32,32,32,33,35,38,43,51,65,69,77,77,87,87,87,87,87,87,84,84,83,82,81,80,80,77,77,71,71,68,68,66,65,64,62,61,59,57,54,53,53,52,50,50,50,50,\r\n011,blank.jpg,134,CongiMNL6non1,~8+.jpg,~2-.jpg,~8+.jpg,0,1,1000,219,2,0,0,13:02:06,,101,928,928,928,928,928,928,928,928,928,928,928,928,928,916,914,914,907,907,894,849,849,822,771,731,674,632,569,524,477,425,393,349,326,326,258,258,239,218,207,191,181,174,165,158,149,143,143,125,125,111,85,85,59,59,50,42,39,37,37,37,37,37,37,37,\r\n011,blank.jpg,135,inCongiMNL792,~9-.jpg,~2+.jpg,~2+.jpg,0,2,1156,47,1,0,0,13:02:10,,101,928,928,916,914,910,906,898,892,892,881,858,858,846,830,817,798,783,755,737,707,683,661,627,602,558,516,516,488,440,409,363,327,286,255,230,191,162,121,121,55,55,9,9,0,0,0,0,0,0,0,2,3,4,6,9,9,13,13,14,15,16,18,18,18,18,18,18,18,18,18,17,17,20,20,\r\n011,blank.jpg,136,inCongMNL81_91,~1+.jpg,~9-.jpg,~1+.jpg,0,1,1110,157,2,0,0,13:02:12,,101,928,928,928,928,928,928,928,928,928,912,912,911,911,908,905,896,888,869,853,822,794,743,706,641,585,521,521,349,349,294,220,173,117,85,53,32,6,6,6,6,6,6,6,6,6,6,6,6,6,1,3,6,10,15,15,24,24,27,32,32,34,34,34,34,35,34,34,34,34,35,35,\r\n011,blank.jpg,137,CongiMNL711,~8+.jpg,~1-.jpg,~8+.jpg,0,1,1250,265,2,0,0,13:02:15,,101,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,923,922,921,921,921,919,918,918,915,915,910,910,906,906,902,900,899,897,896,890,874,855,820,790,790,692,692,595,595,532,485,427,395,345,310,262,226,178,152,115,115,70,70,58,49,42,40,40,40,40,41,42,44,46,48,50,50,50,50,50,50,50,50,50,\r\n011,blank.jpg,138,CongiMNL191,~9+.jpg,~8-.jpg,~9+.jpg,0,1,1266,375,2,0,0,13:02:18,,101,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,931,930,929,928,927,926,924,920,915,915,909,870,870,809,809,759,720,653,604,529,481,418,418,315,275,222,188,188,143,114,80,61,39,29,19,16,15,15,15,15,15,15,16,19,19,22,27,27,33,35,36,36,36,36,35,35,35,35,\r\n011,blank.jpg,139,inCongMNL711,~1+.jpg,~8-.jpg,~1+.jpg,0,1,1187,437,2,0,0,13:02:20,,101,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,913,912,900,882,846,812,752,709,639,591,591,523,424,424,347,347,319,284,260,231,210,181,160,131,115,98,98,72,72,55,55,49,45,44,43,42,41,41,41,40,40,40,40,40,39,39,39,39,39,\r\n011,blank.jpg,140,CongiMNL791,~9+.jpg,~2-.jpg,~9+.jpg,0,1,1187,406,2,0,0,13:02:22,,101,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,913,913,903,903,893,870,849,813,778,723,679,623,583,524,482,482,382,382,334,303,262,241,213,196,180,169,158,151,141,135,125,120,120,113,107,101,93,87,78,69,63,53,47,39,36,36,34,34,34,34,34,\r\n011,blank.jpg,141,CongMNL112,~1-.jpg,~2+.jpg,~2+.jpg,0,2,1344,359,1,0,0,13:02:25,,101,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,927,927,926,924,924,922,918,910,900,875,856,821,795,749,749,651,604,604,537,485,423,395,362,342,318,303,288,277,265,254,254,230,230,205,195,195,180,170,156,142,134,122,114,107,99,99,86,86,81,74,70,63,60,56,54,53,53,53,53,53,54,\r\n011,blank.jpg,142,CongiMNL111,~2+.jpg,~1-.jpg,~2+.jpg,0,1,1188,78,2,0,0,13:02:27,,101,928,928,928,928,926,926,926,926,926,926,926,926,926,926,926,926,925,925,925,924,924,923,922,921,919,916,911,900,887,861,839,795,759,759,630,630,578,497,445,365,289,246,183,150,111,88,75,60,60,54,43,43,34,34,30,28,25,25,25,25,25,26,27,29,29,32,32,33,34,34,36,37,37,37,37,37,\r\n011,blank.jpg,143,inCongiMNL81_92,~9-.jpg,~1+.jpg,~1+.jpg,0,2,1234,31,1,0,0,13:02:29,,101,928,932,932,931,931,930,929,928,927,926,924,921,915,909,897,884,864,864,844,787,787,741,705,643,600,535,492,435,403,355,325,325,262,262,209,209,178,159,134,122,112,100,95,91,91,91,91,91,91,91,91,91,91,91,90,89,88,86,84,83,83,81,81,79,79,75,75,71,67,62,58,52,50,48,48,48,48,48,\r\n011,blank.jpg,144,CongMNL6non2,~2-.jpg,~8+.jpg,~8+.jpg,0,2,1547,31,1,0,0,13:02:31,,101,928,919,919,920,920,920,920,920,920,920,920,920,920,920,920,920,920,920,920,920,920,920,920,920,920,920,919,917,916,911,909,906,903,900,895,890,885,873,873,847,847,832,800,780,745,722,683,653,620,596,564,542,542,495,495,468,417,417,392,361,345,320,309,299,286,271,259,259,231,215,205,205,196,189,181,176,171,167,161,156,151,147,142,136,136,120,120,113,102,94,84,77,68,62,57,54,53,50,49,\r\n011,blank.jpg,145,inCongMNL791,~2+.jpg,~9-.jpg,~2+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24,24,26,29,29,32,35,35,37,37,38,39,38,38,38,39,38,37,\r\n011,blank.jpg,158,inCongiMNL81_92,~9-.jpg,~1+.jpg,~1+.jpg,0,2,1188,125,1,0,0,13:03:08,,101,928,928,928,928,928,928,928,915,913,911,911,908,908,907,907,907,906,903,889,872,841,810,767,693,639,639,534,534,496,441,441,424,414,410,407,403,401,400,395,395,378,378,341,341,293,293,268,238,219,190,172,145,128,106,92,79,79,63,63,60,60,59,58,58,58,57,55,54,54,54,53,53,53,53,53,\r\n011,blank.jpg,159,inCongiMNL192,~9-.jpg,~8+.jpg,~8+.jpg,0,2,1266,63,1,0,0,13:03:10,,101,928,928,928,933,932,932,931,931,931,931,930,930,929,929,927,927,926,925,922,909,899,880,859,821,794,750,720,720,643,643,604,552,505,470,427,400,362,341,310,289,262,262,224,224,188,188,170,162,150,143,140,136,134,133,133,130,130,128,126,126,118,118,110,103,91,82,70,61,58,52,50,49,49,46,46,47,47,50,51,51,\r\n011,blank.jpg,160,inCongiMNL712,~8-.jpg,~1+.jpg,~1+.jpg,0,2,1282,47,1,0,0,13:03:13,,101,934,934,933,932,931,931,930,930,930,930,929,929,929,924,924,920,920,915,904,892,861,839,809,789,767,746,717,717,664,664,645,590,590,556,538,511,499,476,457,434,416,387,367,367,315,315,272,272,252,241,228,220,211,205,199,194,186,180,170,164,153,146,146,126,126,111,102,93,79,68,61,49,42,37,32,32,32,32,32,32,32,32,\r\n011,blank.jpg,161,CongiMNL6non1,~8+.jpg,~2-.jpg,~8+.jpg,0,1,1109,78,2,0,0,13:03:15,,101,928,928,928,928,910,909,907,904,900,894,887,887,867,867,851,839,819,803,773,747,714,686,653,632,600,600,527,496,450,450,413,385,340,299,275,248,238,229,224,216,216,204,204,196,196,190,177,177,172,159,150,137,130,117,107,97,97,76,76,57,57,49,38,33,27,26,25,25,25,25,26,\r\n011,blank.jpg,162,inCongMNL6non1,~2+.jpg,~8-.jpg,~2+.jpg,0,1,1203,47,2,0,0,13:03:17,,101,928,928,915,915,915,915,915,913,910,904,899,899,878,861,861,848,828,812,787,770,744,726,697,674,629,597,597,545,481,481,426,426,404,369,351,326,309,285,271,247,247,220,220,189,189,180,168,159,150,140,135,127,120,111,100,92,92,76,76,67,57,57,52,48,44,43,41,41,41,41,41,41,41,41,41,41,41,\r\n011,blank.jpg,163,CongMNL81_92,~1-.jpg,~9+.jpg,~9+.jpg,0,2,1125,157,1,0,0,13:03:19,,101,928,928,928,928,928,928,928,928,928,924,923,922,920,918,912,903,885,876,866,866,833,833,786,786,736,736,713,676,638,576,536,477,441,406,387,387,366,338,338,310,310,297,279,263,243,229,216,196,181,161,161,130,130,103,86,86,76,65,53,53,50,48,47,46,46,46,46,45,45,45,45,45,\r\n011,blank.jpg,164,inCongMNL791,~2+.jpg,~9-.jpg,~2+.jpg,0,1,1297,47,2,0,0,13:03:23,,101,928,928,945,945,945,945,945,945,944,944,943,943,943,942,942,942,942,940,939,938,936,934,929,922,906,894,871,871,809,809,780,696,696,643,601,566,511,479,437,409,373,353,353,296,268,250,250,227,212,194,179,158,143,122,109,90,78,61,50,50,31,31,26,23,23,23,23,24,26,27,29,30,31,32,33,33,33,33,33,33,33,33,\r\n011,blank.jpg,165,CongiMNL81_91,~9+.jpg,~1-.jpg,~9+.jpg,0,1,1110,63,2,0,0,13:03:25,,101,928,928,928,930,930,927,927,923,923,921,918,917,916,912,909,900,891,878,868,868,840,840,808,781,739,708,665,635,592,564,519,495,459,459,394,394,368,313,313,283,262,235,216,190,174,154,140,130,114,100,100,83,83,68,68,63,56,52,46,41,38,33,32,32,32,32,32,32,32,32,32,\r\n011,blank.jpg,166,inCongiMNL792,~9-.jpg,~2+.jpg,~2+.jpg,0,2,1219,172,1,0,0,13:03:27,,101,928,928,928,928,928,928,928,928,928,928,942,942,942,942,942,942,942,942,942,942,940,938,931,923,907,891,872,872,844,777,777,739,676,631,555,485,439,397,357,334,307,307,280,280,261,261,253,238,229,213,200,181,169,152,140,125,125,101,101,77,77,56,56,48,37,30,24,19,16,16,16,16,15,15,15,15,15,\r\n011,blank.jpg,167,CongMNL192,~8-.jpg,~9+.jpg,~9+.jpg,0,2,1360,78,1,0,0,13:03:30,,101,928,928,928,928,931,931,931,930,930,930,930,929,929,928,927,926,922,914,903,893,879,867,845,828,799,799,739,739,690,653,594,548,504,437,396,338,305,265,239,206,206,186,144,144,133,126,118,115,113,111,110,110,109,107,107,107,102,102,96,92,85,81,72,66,55,48,39,35,33,33,33,33,33,35,35,39,41,41,41,41,41,41,41,41,41,41,41,\r\n011,blank.jpg,168,CongMNL792,~2-.jpg,~9+.jpg,~9+.jpg,0,2,1500,78,1,0,0,13:03:32,,101,928,928,928,928,912,912,910,910,909,906,902,897,889,877,858,842,813,813,749,749,668,668,608,568,509,473,425,396,358,337,309,290,290,254,254,233,223,208,196,183,171,149,138,124,113,100,90,81,77,77,70,70,67,66,66,66,66,65,58,51,42,38,38,29,29,26,24,24,23,23,23,23,22,22,22,22,22,22,22,22,22,30,30,38,38,40,40,40,40,40,40,41,41,41,40,40,\r\n011,blank.jpg,169,inCongMNL111,~1+.jpg,~2-.jpg,~1+.jpg,0,1,1109,156,2,0,0,13:03:34,,101,928,928,928,928,928,928,928,928,928,932,930,924,916,905,905,871,871,821,821,794,745,709,654,619,572,545,504,481,449,430,430,397,397,382,365,365,354,346,337,331,323,312,305,292,278,253,253,211,211,187,171,145,145,129,118,103,93,81,75,67,62,57,57,51,51,50,50,50,50,50,50,\r\n011,blank.jpg,170,inCongiMNL112,~2-.jpg,~1+.jpg,~1+.jpg,0,2,1375,63,1,0,0,13:03:36,,101,928,928,928,904,902,902,899,899,896,896,895,895,895,892,888,884,879,865,850,818,818,720,720,666,587,528,450,410,352,322,281,257,229,213,201,201,181,181,173,161,153,139,129,113,104,88,77,64,55,44,44,39,32,29,27,27,27,27,31,34,36,37,38,39,39,40,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,46,46,48,50,50,50,50,\r\n011,blank.jpg,171,inCongMNL81_91,~1+.jpg,~9-.jpg,~1+.jpg,0,1,1469,344,2,0,0,13:03:39,,101,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,945,944,944,943,943,939,939,932,932,927,921,914,899,879,851,828,790,761,718,690,690,624,624,590,565,532,511,482,460,431,412,384,365,337,319,319,270,270,252,226,207,179,161,134,118,98,82,71,62,53,53,50,47,47,47,47,47,47,51,55,57,58,58,58,58,58,58,58,58,57,57,57,56,\r\n011,blank.jpg,172,CongiMNL791,~9+.jpg,~2-.jpg,~9+.jpg,0,1,1468,140,2,0,0,13:03:41,,101,928,928,928,928,928,928,928,928,933,933,933,933,933,933,932,932,931,930,929,929,929,929,929,928,928,928,928,928,928,926,926,926,925,921,913,892,875,847,822,786,761,761,705,705,652,622,622,598,562,537,500,474,442,421,390,372,372,325,325,296,278,253,235,212,200,185,173,159,150,140,134,126,120,120,109,109,103,97,93,86,82,77,73,66,62,59,59,57,57,57,56,56,55,55,\r\n011,blank.jpg,173,CongiMNL111,~2+.jpg,~1-.jpg,~2+.jpg,0,1,1343,203,2,0,0,13:03:44,,101,928,928,928,928,928,928,928,928,928,928,928,928,933,933,940,940,940,940,940,940,940,940,940,940,942,942,941,931,931,904,845,845,781,781,755,723,703,674,652,621,603,571,550,519,519,466,466,442,413,394,366,351,331,317,295,278,254,235,235,198,198,177,150,150,141,126,119,106,100,92,87,85,81,78,78,74,74,67,67,61,61,61,61,61,60,59,\r\n011,blank.jpg,174,inCongMNL191,~8+.jpg,~9-.jpg,~8+.jpg,0,1,1312,78,2,0,0,13:03:46,,101,928,928,928,928,929,929,929,929,929,929,930,933,933,934,934,934,934,934,931,924,912,903,881,881,822,822,744,744,714,664,630,578,551,515,493,460,441,409,387,351,326,289,289,268,236,216,186,166,139,122,96,78,52,37,19,19,0,0,0,0,0,0,1,3,7,20,27,37,40,44,44,44,44,44,44,43,41,41,41,40,40,40,39,37,\r\n011,blank.jpg,175,CongMNL112,~1-.jpg,~2+.jpg,~2+.jpg,0,2,1329,32,1,0,0,13:03:48,,101,928,927,927,929,930,931,931,937,959,959,959,959,959,959,959,959,959,959,959,959,959,959,959,959,959,959,959,959,959,959,959,957,936,936,852,803,723,723,565,565,504,414,368,308,277,245,225,207,199,191,187,182,181,180,180,178,178,176,173,166,156,126,106,78,62,41,30,30,11,11,8,8,8,8,9,11,12,13,12,12,12,12,12,12,12,\r\n011,break.jpg,176,,,,,0,,0,0,,0,0,13:03:51,,101,\r\n011,blank.jpg,177,CongiMNL81_91,~9+.jpg,~1-.jpg,~9+.jpg,0,1,1391,94,2,0,0,13:03:56,,101,928,928,928,928,928,913,913,913,913,913,913,913,912,912,912,912,912,912,910,909,905,897,886,858,858,790,790,704,704,637,637,608,574,534,500,455,425,378,355,322,288,288,241,241,208,208,196,191,187,184,181,179,176,173,167,158,158,134,134,118,111,99,93,85,79,73,70,70,67,66,65,64,63,63,63,59,59,57,57,57,57,57,57,57,57,57,57,57,\r\n011,blank.jpg,178,CongMNL81_92,~1-.jpg,~9+.jpg,~9+.jpg,0,2,1297,219,1,0,0,13:03:59,,101,928,928,928,928,928,928,928,928,928,928,928,928,928,917,915,909,896,896,883,831,831,777,777,743,717,675,651,599,556,481,429,345,306,306,245,245,215,192,154,137,119,107,86,67,43,32,20,20,9,9,5,5,9,15,15,15,16,17,19,20,21,21,21,21,21,21,21,21,21,20,19,18,18,19,21,23,28,32,32,32,31,31,\r\n011,blank.jpg,179,inCongMNL791,~2+.jpg,~9-.jpg,~2+.jpg,0,1,1422,63,2,0,0,13:04:01,,101,928,928,928,925,925,925,925,925,925,925,925,925,925,925,926,926,926,926,926,926,924,920,917,908,898,861,830,784,784,719,719,659,659,633,593,567,529,500,459,431,409,381,363,337,318,318,289,269,241,220,190,174,161,152,140,129,111,111,77,77,67,67,67,67,68,70,71,71,71,71,71,71,70,66,66,61,61,60,60,60,60,60,59,59,59,59,59,58,58,58,\r\n011,blank.jpg,180,CongMNL192,~8-.jpg,~9+.jpg,~9+.jpg,0,2,1688,141,1,0,0,13:04:04,,101,928,928,928,928,928,928,928,928,943,944,944,944,944,944,944,944,944,944,944,944,934,904,881,845,822,787,764,731,731,667,667,611,611,576,551,516,451,451,415,392,360,339,309,286,266,266,238,195,195,181,165,154,144,139,133,131,131,131,131,131,131,131,132,132,132,132,132,132,132,131,128,123,119,110,106,99,99,94,89,89,87,87,86,84,82,78,71,65,59,54,48,46,46,46,46,46,46,46,45,45,45,45,45,45,45,45,47,48,\r\n011,blank.jpg,181,inCongMNL191,~8+.jpg,~9-.jpg,~8+.jpg,0,1,1375,140,2,0,0,13:04:07,,101,933,933,933,933,933,933,933,933,933,932,932,932,932,931,929,921,921,860,789,789,686,686,593,593,555,523,504,480,466,452,442,442,429,408,408,393,372,372,362,346,337,328,324,317,312,308,306,306,304,295,295,275,275,265,254,249,240,229,214,202,188,177,162,162,136,136,111,102,102,93,84,80,73,70,67,64,62,57,57,54,48,44,44,44,44,44,42,41,\r\n011,blank.jpg,182,CongiMNL791,~9+.jpg,~2-.jpg,~9+.jpg,0,1,1234,141,2,0,0,13:04:09,,101,928,928,928,928,928,928,928,928,928,927,927,924,924,921,918,914,911,902,893,876,861,833,810,810,744,744,697,666,611,573,528,466,428,374,340,291,256,256,173,173,103,103,50,50,25,10,0,0,0,0,0,0,0,1,1,9,9,23,23,33,38,45,49,55,58,61,62,63,63,63,63,62,61,61,61,61,61,60,59,\r\n011,blank.jpg,183,inCongMNL81_91,~1+.jpg,~9-.jpg,~1+.jpg,0,1,1078,125,2,0,0,13:04:12,,101,928,928,928,928,928,928,928,935,935,933,931,926,923,914,906,892,881,881,845,845,794,794,763,738,703,671,621,579,517,473,417,342,342,236,236,201,152,107,84,52,32,8,0,0,0,0,0,0,0,0,0,3,3,5,8,13,16,21,26,32,35,40,42,42,42,42,42,42,42,\r\n011,blank.jpg,184,CongMNL712,~1-.jpg,~8+.jpg,~8+.jpg,0,2,2062,78,1,0,0,13:04:14,,101,928,928,928,927,927,913,905,905,887,865,832,810,772,750,717,693,654,628,628,565,527,527,498,450,383,383,356,317,296,268,250,230,220,220,208,195,195,190,173,173,165,159,151,147,140,137,133,132,129,129,129,129,129,129,128,128,128,128,128,128,127,125,122,119,111,111,94,94,75,75,67,55,46,36,29,25,23,22,22,22,22,26,26,27,31,31,32,32,33,35,36,38,39,41,41,41,41,41,41,41,40,40,39,38,38,38,38,38,38,38,38,39,39,39,41,41,41,42,42,43,45,45,45,45,46,46,46,46,46,46,\r\n011,blank.jpg,185,CongMNL112,~1-.jpg,~2+.jpg,~2+.jpg,0,2,1687,47,1,0,0,13:04:17,,101,928,928,924,924,924,924,924,924,924,924,924,924,924,924,924,924,924,924,924,924,924,924,924,924,924,917,891,821,761,678,624,560,527,495,495,447,447,419,411,411,391,391,377,359,321,292,249,220,183,157,123,123,103,50,50,23,10,0,0,0,0,0,0,0,0,0,0,0,0,0,2,6,11,18,23,27,28,29,29,29,29,29,28,28,28,29,29,30,31,33,35,37,39,40,41,42,42,42,43,43,43,43,43,43,43,43,43,44,\r\n011,blank.jpg,186,inCongiMNL712,~8-.jpg,~1+.jpg,~1+.jpg,0,2,1235,47,1,0,0,13:04:20,,101,928,928,950,950,949,948,948,947,947,946,945,943,939,929,929,922,877,877,850,820,785,757,702,654,582,555,523,502,502,436,436,378,378,356,326,310,293,286,277,271,269,268,268,268,265,265,261,261,254,254,248,235,223,205,190,168,152,134,124,124,110,92,92,75,75,67,62,55,51,48,48,48,48,48,48,48,48,49,\r\n011,blank.jpg,187,CongiMNL711,~8+.jpg,~1-.jpg,~8+.jpg,0,1,1156,125,2,0,0,13:04:22,,101,928,928,928,928,928,928,928,928,925,921,916,904,904,881,881,866,838,818,784,759,726,679,654,611,588,588,535,535,482,482,447,423,384,358,322,300,269,247,217,200,200,155,155,130,88,88,74,59,51,44,42,41,41,41,41,41,41,41,41,41,41,41,42,45,48,49,48,48,48,48,48,49,49,\r\n011,blank.jpg,188,inCongiMNL792,~9-.jpg,~2+.jpg,~2+.jpg,0,2,1109,78,1,0,0,13:04:24,,101,928,928,928,928,925,924,923,922,921,920,917,909,902,902,880,880,859,841,811,789,754,732,694,667,628,600,553,553,461,461,364,364,330,274,239,191,161,121,99,72,53,27,10,0,0,0,0,0,0,0,0,2,6,11,21,29,36,44,44,46,46,46,46,46,46,45,45,45,45,45,\r\n011,blank.jpg,189,inCongiMNL6non2,~8-.jpg,~2+.jpg,~2+.jpg,0,2,1515,47,1,0,0,13:04:27,,101,928,928,940,938,937,937,936,936,935,935,935,935,935,932,925,901,878,852,808,780,743,743,655,655,602,524,524,499,469,446,433,422,415,407,402,395,394,394,393,393,387,387,367,367,346,331,309,294,272,258,236,219,200,200,175,175,164,148,138,124,115,103,96,83,73,59,50,50,30,24,24,12,12,10,10,10,11,12,12,17,21,25,28,30,30,33,33,33,32,32,32,32,32,32,32,32,32,\r\n011,blank.jpg,190,CongMNL792,~2-.jpg,~9+.jpg,~9+.jpg,0,2,1203,78,1,0,0,13:04:29,,101,928,928,928,928,946,944,944,938,938,934,925,915,892,875,845,817,774,735,659,659,553,553,464,464,381,381,354,320,303,281,270,257,247,236,227,227,214,185,185,169,142,123,94,74,45,28,8,0,0,0,0,0,0,0,1,3,6,10,14,19,23,26,28,31,32,33,33,33,33,33,32,31,31,31,31,31,31,\r\n011,blank.jpg,191,inCongiMNL192,~9-.jpg,~8+.jpg,~8+.jpg,0,2,1438,110,1,0,0,13:04:32,,101,928,928,928,928,928,928,926,925,924,923,923,923,922,922,920,920,904,904,884,846,816,759,723,662,621,576,552,530,530,516,516,512,510,510,504,496,477,459,435,416,392,377,356,356,312,296,296,254,254,229,214,193,175,152,139,122,111,97,87,76,76,60,60,53,46,41,36,32,29,27,25,25,25,25,28,28,34,37,37,40,40,41,41,41,41,41,42,42,43,43,43,42,\r\n011,blank.jpg,192,CongiMNL111,~2+.jpg,~1-.jpg,~2+.jpg,0,1,1407,94,2,0,0,13:04:35,,101,928,928,928,928,928,915,914,913,912,911,909,909,909,909,909,909,909,909,909,909,909,909,909,909,909,909,909,905,902,902,867,867,811,811,776,753,713,680,629,597,546,504,474,422,422,360,360,328,310,287,274,261,253,242,234,228,217,209,197,188,188,174,146,146,134,119,108,97,90,82,78,70,66,62,59,58,58,51,51,47,44,40,40,38,38,37,37,37,37,\r\n011,blank.jpg,193,inCongMNL711,~1+.jpg,~8-.jpg,~1+.jpg,0,1,1110,32,2,0,0,13:04:37,,101,921,920,919,919,919,917,915,915,911,907,903,897,893,885,876,862,849,826,826,769,736,736,628,628,564,517,468,395,320,265,189,143,91,62,27,27,0,0,0,0,0,0,0,0,1,13,26,47,62,71,74,74,74,73,73,69,56,56,52,51,50,50,50,50,50,50,50,50,50,50,\r\n011,blank.jpg,194,inCongiMNL81_92,~9-.jpg,~1+.jpg,~1+.jpg,0,2,1297,125,1,0,0,13:04:39,,101,928,928,928,928,928,928,928,929,927,921,916,907,898,886,875,875,848,822,822,798,767,716,681,624,564,519,456,408,408,314,314,221,221,153,153,130,97,81,62,53,42,36,30,29,29,29,29,29,34,34,34,34,34,34,34,34,34,35,35,36,36,36,36,36,36,36,36,36,36,37,37,37,38,39,40,40,40,40,40,40,40,40,40,\r\n011,blank.jpg,195,CongMNL6non2,~2-.jpg,~8+.jpg,~8+.jpg,0,2,1312,78,1,0,0,13:04:42,,101,928,928,928,928,940,939,938,937,937,935,935,935,934,934,933,932,930,925,918,902,887,863,840,819,777,777,679,631,631,554,506,445,392,359,327,293,270,239,221,204,196,190,190,182,182,180,175,166,148,131,105,84,56,37,37,5,5,0,0,0,10,10,18,22,27,30,32,33,33,33,33,33,37,37,40,42,42,42,42,42,41,41,41,39,\r\n011,blank.jpg,196,inCongiMNL112,~2-.jpg,~1+.jpg,~1+.jpg,0,2,1453,266,1,0,0,13:04:44,,101,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,928,932,930,917,917,865,865,800,800,730,675,591,532,453,400,326,283,219,219,137,137,114,71,71,38,38,23,17,11,9,9,9,9,9,9,9,12,12,13,13,14,16,18,22,24,25,27,28,28,28,28,28,28,28,28,28,28,28,28,28,28,29,29,29,29,33,33,40,40,45,45,45,44,44,44,43,43,\r\n011,blank.jpg,197,inCongMNL6non1,~2+.jpg,~8-.jpg,~2+.jpg,0,1,1141,32,2,0,0,13:04:47,,101,928,934,934,934,933,932,931,927,919,895,873,839,813,760,760,637,637,581,492,435,345,279,230,162,108,80,49,49,24,24,11,11,9,9,9,10,10,10,11,11,9,9,2,2,2,1,1,10,10,21,28,38,45,52,57,61,61,61,61,59,59,56,56,56,56,56,56,55,55,55,55,54,54,\r\n011,blank.jpg,198,inCongMNL111,~1+.jpg,~2-.jpg,~1+.jpg,0,1,1187,31,2,0,0,13:04:49,,101,929,929,929,929,929,928,926,922,915,915,892,892,850,850,811,773,710,659,576,519,434,363,326,279,253,229,229,203,179,179,171,160,153,142,132,124,118,112,109,109,104,104,104,104,104,103,103,102,99,96,93,90,88,86,85,84,84,83,83,81,80,76,73,70,65,61,55,51,47,45,44,44,44,44,44,\r\n011,blank.jpg,199,CongiMNL191,~9+.jpg,~8-.jpg,~9+.jpg,0,1,1328,78,2,0,0,13:04:51,,101,928,928,928,928,921,917,917,907,895,869,842,810,749,697,618,561,561,420,420,337,278,196,125,87,61,34,21,7,1,0,0,0,0,0,0,0,3,13,22,37,50,63,69,71,71,72,72,72,69,69,66,60,56,51,48,45,44,43,43,43,43,43,43,43,43,45,45,47,49,49,50,50,50,50,50,49,49,49,49,49,49,49,47,47,47,\r\n011,blank.jpg,200,CongiMNL6non1,~8+.jpg,~2-.jpg,~8+.jpg,0,1,1031,31,2,0,0,13:04:53,,101,928,933,933,932,931,930,927,923,914,906,906,887,844,844,802,765,694,641,557,503,420,369,296,248,248,188,108,108,85,58,42,26,19,9,7,2,2,2,2,2,2,2,2,2,1,3,7,13,20,26,29,32,34,35,35,35,35,35,35,35,35,34,34,34,34,\r\n\r\n\r\nRAW TRACKS (time)\r\nsubjID,stim,order,condition,resp_1,resp_2,response,error,resp_num,RT,init time,distractor,ideal y-int,maxdev,real 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453,469,485,500,516,532,547,563,578,594,610,625,641,657,672,688,703,719,735,750,766,782,797,813,828,844,860,875,891,907,922,938,953,969,985,1000,1016,1032,1047,1063,1078,1094,1110,1125,1141,1157,1172,1188,1203,1219,\r\n011,blank.jpg,187,CongiMNL711,~8+.jpg,~1-.jpg,~8+.jpg,0,1,1156,125,2,0,0,13:04:22,,101,15,31,47,62,78,93,109,125,140,156,172,187,203,218,234,250,265,281,297,312,328,343,359,375,390,406,422,437,453,468,484,500,515,531,547,562,578,593,609,625,640,656,672,687,703,718,734,750,765,781,797,812,828,843,859,875,890,906,922,937,953,968,984,1000,1015,1031,1047,1062,1078,1093,1109,1125,1140,\r\n011,blank.jpg,188,inCongiMNL792,~9-.jpg,~2+.jpg,~2+.jpg,0,2,1109,78,1,0,0,13:04:24,,101,15,31,47,62,78,93,109,125,140,156,172,187,203,218,234,250,265,281,297,312,328,343,359,375,390,406,422,437,453,468,484,500,515,531,547,562,578,593,609,625,640,656,672,687,703,718,734,750,765,781,797,812,828,843,859,875,890,906,922,937,953,968,984,1000,1015,1031,1047,1062,1078,1093,\r\n011,blank.jpg,189,inCongiMNL6non2,~8-.jpg,~2+.jpg,~2+.jpg,0,2,1515,47,1,0,0,13:04:27,,101,15,31,47,62,78,93,109,125,140,156,172,187,203,218,234,250,265,281,297,312,328,343,359,375,390,406,422,437,453,468,484,500,515,531,547,562,578,593,609,625,640,656,672,687,703,718,734,750,765,781,797,812,828,843,859,875,890,906,922,937,953,968,984,1000,1015,1031,1047,1062,1078,1093,1109,1125,1140,1156,1172,1187,1203,1218,1234,1250,1265,1281,1297,1312,1328,1343,1359,1375,1390,1406,1422,1437,1453,1468,1484,1500,1515,\r\n011,blank.jpg,190,CongMNL792,~2-.jpg,~9+.jpg,~9+.jpg,0,2,1203,78,1,0,0,13:04:29,,101,15,31,46,62,78,93,109,125,140,156,171,187,203,218,234,250,265,281,296,312,328,343,359,375,390,406,421,437,453,468,484,500,515,531,546,562,578,593,609,625,640,656,671,687,703,718,734,750,765,781,796,812,828,843,859,875,890,906,921,937,953,968,984,1000,1015,1031,1046,1062,1078,1093,1109,1125,1140,1156,1171,1187,1203,\r\n011,blank.jpg,191,inCongiMNL192,~9-.jpg,~8+.jpg,~8+.jpg,0,2,1438,110,1,0,0,13:04:32,,101,16,31,47,63,78,94,110,125,141,156,172,188,203,219,235,250,266,281,297,313,328,344,360,375,391,406,422,438,453,469,485,500,516,531,547,563,578,594,610,625,641,656,672,688,703,719,735,750,766,781,797,813,828,844,860,875,891,906,922,938,953,969,985,1000,1016,1031,1047,1063,1078,1094,1110,1125,1141,1156,1172,1188,1203,1219,1235,1250,1266,1281,1297,1313,1328,1344,1360,1375,1391,1406,1422,1438,\r\n011,blank.jpg,192,CongiMNL111,~2+.jpg,~1-.jpg,~2+.jpg,0,1,1407,94,2,0,0,13:04:35,,101,16,32,47,63,79,94,110,125,141,157,172,188,204,219,235,250,266,282,297,313,329,344,360,375,391,407,422,438,454,469,485,500,516,532,547,563,579,594,610,625,641,657,672,688,704,719,735,750,766,782,797,813,829,844,860,875,891,907,922,938,954,969,985,1000,1016,1032,1047,1063,1079,1094,1110,1125,1141,1157,1172,1188,1204,1219,1235,1250,1266,1282,1297,1313,1329,1344,1360,1375,1391,\r\n011,blank.jpg,193,inCongMNL711,~1+.jpg,~8-.jpg,~1+.jpg,0,1,1110,32,2,0,0,13:04:37,,101,16,32,47,63,78,94,110,125,141,157,172,188,203,219,235,250,266,282,297,313,328,344,360,375,391,407,422,438,453,469,485,500,516,532,547,563,578,594,610,625,641,657,672,688,703,719,735,750,766,782,797,813,828,844,860,875,891,907,922,938,953,969,985,1000,1016,1032,1047,1063,1078,1094,\r\n011,blank.jpg,194,inCongiMNL81_92,~9-.jpg,~1+.jpg,~1+.jpg,0,2,1297,125,1,0,0,13:04:39,,101,16,31,47,62,78,94,109,125,141,156,172,187,203,219,234,250,266,281,297,312,328,344,359,375,391,406,422,437,453,469,484,500,516,531,547,562,578,594,609,625,641,656,672,687,703,719,734,750,766,781,797,812,828,844,859,875,891,906,922,937,953,969,984,1000,1016,1031,1047,1062,1078,1094,1109,1125,1141,1156,1172,1187,1203,1219,1234,1250,1266,1281,1297,\r\n011,blank.jpg,195,CongMNL6non2,~2-.jpg,~8+.jpg,~8+.jpg,0,2,1312,78,1,0,0,13:04:42,,101,16,31,47,62,78,94,109,125,141,156,172,187,203,219,234,250,266,281,297,312,328,344,359,375,391,406,422,437,453,469,484,500,516,531,547,562,578,594,609,625,641,656,672,687,703,719,734,750,766,781,797,812,828,844,859,875,891,906,922,937,953,969,984,1000,1016,1031,1047,1062,1078,1094,1109,1125,1141,1156,1172,1187,1203,1219,1234,1250,1266,1281,1297,1312,\r\n011,blank.jpg,196,inCongiMNL112,~2-.jpg,~1+.jpg,~1+.jpg,0,2,1453,266,1,0,0,13:04:44,,101,16,32,47,63,78,94,110,125,141,157,172,188,203,219,235,250,266,282,297,313,328,344,360,375,391,407,422,438,453,469,485,500,516,532,547,563,578,594,610,625,641,657,672,688,703,719,735,750,766,782,797,813,828,844,860,875,891,907,922,938,953,969,985,1000,1016,1032,1047,1063,1078,1094,1110,1125,1141,1157,1172,1188,1203,1219,1235,1250,1266,1282,1297,1313,1328,1344,1360,1375,1391,1407,1422,1438,\r\n011,blank.jpg,197,inCongMNL6non1,~2+.jpg,~8-.jpg,~2+.jpg,0,1,1141,32,2,0,0,13:04:47,,101,16,32,47,63,78,94,110,125,141,157,172,188,203,219,235,250,266,282,297,313,328,344,360,375,391,407,422,438,453,469,485,500,516,532,547,563,578,594,610,625,641,657,672,688,703,719,735,750,766,782,797,813,828,844,860,875,891,907,922,938,953,969,985,1000,1016,1032,1047,1063,1078,1094,1110,1125,1141,\r\n011,blank.jpg,198,inCongMNL111,~1+.jpg,~2-.jpg,~1+.jpg,0,1,1187,31,2,0,0,13:04:49,,101,15,31,47,62,78,93,109,125,140,156,172,187,203,218,234,250,265,281,297,312,328,343,359,375,390,406,422,437,453,468,484,500,515,531,547,562,578,593,609,625,640,656,672,687,703,718,734,750,765,781,797,812,828,843,859,875,890,906,922,937,953,968,984,1000,1015,1031,1047,1062,1078,1093,1109,1125,1140,1156,1172,\r\n011,blank.jpg,199,CongiMNL191,~9+.jpg,~8-.jpg,~9+.jpg,0,1,1328,78,2,0,0,13:04:51,,101,15,31,47,62,78,94,109,125,140,156,172,187,203,219,234,250,265,281,297,312,328,344,359,375,390,406,422,437,453,469,484,500,515,531,547,562,578,594,609,625,640,656,672,687,703,719,734,750,765,781,797,812,828,844,859,875,890,906,922,937,953,969,984,1000,1015,1031,1047,1062,1078,1094,1109,1125,1140,1156,1172,1187,1203,1219,1234,1250,1265,1281,1297,1312,1328,\r\n011,blank.jpg,200,CongiMNL6non1,~8+.jpg,~2-.jpg,~8+.jpg,0,1,1031,31,2,0,0,13:04:53,,101,15,31,47,62,78,94,109,125,140,156,172,187,203,219,234,250,265,281,297,312,328,344,359,375,390,406,422,437,453,469,484,500,515,531,547,562,578,594,609,625,640,656,672,687,703,719,734,750,765,781,797,812,828,844,859,875,890,906,922,937,953,969,984,1000,1015,\r\n\r\n","avg_line_length":426.2243066884,"max_line_length":1594,"alphanum_fraction":0.6990207654} {"size":9039,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 15;\nname = \"15v1 1 3 2 1 2 1 1 1 1 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-14 I y] (1 (I Sin[x])^7 Cos[x]^8 + 1 (I Sin[x])^8 Cos[x]^7) + Exp[-12 I y] (10 (I Sin[x])^8 Cos[x]^7 + 10 (I Sin[x])^7 Cos[x]^8 + 3 (I Sin[x])^6 Cos[x]^9 + 3 (I Sin[x])^9 Cos[x]^6 + 1 (I Sin[x])^5 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^5) + Exp[-10 I y] (34 (I Sin[x])^6 Cos[x]^9 + 34 (I Sin[x])^9 Cos[x]^6 + 40 (I Sin[x])^8 Cos[x]^7 + 40 (I Sin[x])^7 Cos[x]^8 + 14 (I Sin[x])^10 Cos[x]^5 + 14 (I Sin[x])^5 Cos[x]^10 + 3 (I Sin[x])^4 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^4) + Exp[-8 I y] (128 (I Sin[x])^9 Cos[x]^6 + 128 (I Sin[x])^6 Cos[x]^9 + 184 (I Sin[x])^7 Cos[x]^8 + 184 (I Sin[x])^8 Cos[x]^7 + 44 (I Sin[x])^5 Cos[x]^10 + 44 (I Sin[x])^10 Cos[x]^5 + 8 (I Sin[x])^4 Cos[x]^11 + 8 (I Sin[x])^11 Cos[x]^4) + Exp[-6 I y] (168 (I Sin[x])^5 Cos[x]^10 + 168 (I Sin[x])^10 Cos[x]^5 + 455 (I Sin[x])^7 Cos[x]^8 + 455 (I Sin[x])^8 Cos[x]^7 + 312 (I Sin[x])^9 Cos[x]^6 + 312 (I Sin[x])^6 Cos[x]^9 + 56 (I Sin[x])^4 Cos[x]^11 + 56 (I Sin[x])^11 Cos[x]^4 + 10 (I Sin[x])^3 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^3) + Exp[-4 I y] (329 (I Sin[x])^10 Cos[x]^5 + 329 (I Sin[x])^5 Cos[x]^10 + 920 (I Sin[x])^8 Cos[x]^7 + 920 (I Sin[x])^7 Cos[x]^8 + 639 (I Sin[x])^6 Cos[x]^9 + 639 (I Sin[x])^9 Cos[x]^6 + 99 (I Sin[x])^4 Cos[x]^11 + 99 (I Sin[x])^11 Cos[x]^4 + 15 (I Sin[x])^3 Cos[x]^12 + 15 (I Sin[x])^12 Cos[x]^3) + Exp[-2 I y] (249 (I Sin[x])^4 Cos[x]^11 + 249 (I Sin[x])^11 Cos[x]^4 + 944 (I Sin[x])^6 Cos[x]^9 + 944 (I Sin[x])^9 Cos[x]^6 + 1176 (I Sin[x])^8 Cos[x]^7 + 1176 (I Sin[x])^7 Cos[x]^8 + 548 (I Sin[x])^5 Cos[x]^10 + 548 (I Sin[x])^10 Cos[x]^5 + 74 (I Sin[x])^3 Cos[x]^12 + 74 (I Sin[x])^12 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^13 + 12 (I Sin[x])^13 Cos[x]^2) + Exp[0 I y] (1084 (I Sin[x])^9 Cos[x]^6 + 1084 (I Sin[x])^6 Cos[x]^9 + 259 (I Sin[x])^11 Cos[x]^4 + 259 (I Sin[x])^4 Cos[x]^11 + 1406 (I Sin[x])^7 Cos[x]^8 + 1406 (I Sin[x])^8 Cos[x]^7 + 602 (I Sin[x])^5 Cos[x]^10 + 602 (I Sin[x])^10 Cos[x]^5 + 71 (I Sin[x])^3 Cos[x]^12 + 71 (I Sin[x])^12 Cos[x]^3 + 10 (I Sin[x])^2 Cos[x]^13 + 10 (I Sin[x])^13 Cos[x]^2) + Exp[2 I y] (622 (I Sin[x])^5 Cos[x]^10 + 622 (I Sin[x])^10 Cos[x]^5 + 1019 (I Sin[x])^7 Cos[x]^8 + 1019 (I Sin[x])^8 Cos[x]^7 + 136 (I Sin[x])^3 Cos[x]^12 + 136 (I Sin[x])^12 Cos[x]^3 + 854 (I Sin[x])^6 Cos[x]^9 + 854 (I Sin[x])^9 Cos[x]^6 + 328 (I Sin[x])^4 Cos[x]^11 + 328 (I Sin[x])^11 Cos[x]^4 + 38 (I Sin[x])^2 Cos[x]^13 + 38 (I Sin[x])^13 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^14 + 6 (I Sin[x])^14 Cos[x]^1) + Exp[4 I y] (776 (I Sin[x])^8 Cos[x]^7 + 776 (I Sin[x])^7 Cos[x]^8 + 381 (I Sin[x])^10 Cos[x]^5 + 381 (I Sin[x])^5 Cos[x]^10 + 607 (I Sin[x])^6 Cos[x]^9 + 607 (I Sin[x])^9 Cos[x]^6 + 57 (I Sin[x])^12 Cos[x]^3 + 57 (I Sin[x])^3 Cos[x]^12 + 165 (I Sin[x])^4 Cos[x]^11 + 165 (I Sin[x])^11 Cos[x]^4 + 14 (I Sin[x])^13 Cos[x]^2 + 14 (I Sin[x])^2 Cos[x]^13 + 2 (I Sin[x])^1 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^1) + Exp[6 I y] (142 (I Sin[x])^4 Cos[x]^11 + 142 (I Sin[x])^11 Cos[x]^4 + 268 (I Sin[x])^6 Cos[x]^9 + 268 (I Sin[x])^9 Cos[x]^6 + 295 (I Sin[x])^8 Cos[x]^7 + 295 (I Sin[x])^7 Cos[x]^8 + 198 (I Sin[x])^5 Cos[x]^10 + 198 (I Sin[x])^10 Cos[x]^5 + 67 (I Sin[x])^3 Cos[x]^12 + 67 (I Sin[x])^12 Cos[x]^3 + 24 (I Sin[x])^2 Cos[x]^13 + 24 (I Sin[x])^13 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^14 + 6 (I Sin[x])^14 Cos[x]^1 + 1 Cos[x]^15 + 1 (I Sin[x])^15) + Exp[8 I y] (108 (I Sin[x])^9 Cos[x]^6 + 108 (I Sin[x])^6 Cos[x]^9 + 130 (I Sin[x])^8 Cos[x]^7 + 130 (I Sin[x])^7 Cos[x]^8 + 41 (I Sin[x])^11 Cos[x]^4 + 41 (I Sin[x])^4 Cos[x]^11 + 70 (I Sin[x])^10 Cos[x]^5 + 70 (I Sin[x])^5 Cos[x]^10 + 2 (I Sin[x])^13 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^13 + 13 (I Sin[x])^3 Cos[x]^12 + 13 (I Sin[x])^12 Cos[x]^3) + Exp[10 I y] (23 (I Sin[x])^5 Cos[x]^10 + 23 (I Sin[x])^10 Cos[x]^5 + 17 (I Sin[x])^7 Cos[x]^8 + 17 (I Sin[x])^8 Cos[x]^7 + 19 (I Sin[x])^9 Cos[x]^6 + 19 (I Sin[x])^6 Cos[x]^9 + 14 (I Sin[x])^4 Cos[x]^11 + 14 (I Sin[x])^11 Cos[x]^4 + 12 (I Sin[x])^3 Cos[x]^12 + 12 (I Sin[x])^12 Cos[x]^3 + 5 (I Sin[x])^2 Cos[x]^13 + 5 (I Sin[x])^13 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^1) + Exp[12 I y] (3 (I Sin[x])^10 Cos[x]^5 + 3 (I Sin[x])^5 Cos[x]^10 + 6 (I Sin[x])^8 Cos[x]^7 + 6 (I Sin[x])^7 Cos[x]^8 + 5 (I Sin[x])^9 Cos[x]^6 + 5 (I Sin[x])^6 Cos[x]^9) + Exp[14 I y] (1 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^4))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-14 I y] (1 (I Sin[x])^7 Cos[x]^8 + 1 (I Sin[x])^8 Cos[x]^7) + Exp[-12 I y] (10 (I Sin[x])^8 Cos[x]^7 + 10 (I Sin[x])^7 Cos[x]^8 + 3 (I Sin[x])^6 Cos[x]^9 + 3 (I Sin[x])^9 Cos[x]^6 + 1 (I Sin[x])^5 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^5) + Exp[-10 I y] (34 (I Sin[x])^6 Cos[x]^9 + 34 (I Sin[x])^9 Cos[x]^6 + 40 (I Sin[x])^8 Cos[x]^7 + 40 (I Sin[x])^7 Cos[x]^8 + 14 (I Sin[x])^10 Cos[x]^5 + 14 (I Sin[x])^5 Cos[x]^10 + 3 (I Sin[x])^4 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^4) + Exp[-8 I y] (128 (I Sin[x])^9 Cos[x]^6 + 128 (I Sin[x])^6 Cos[x]^9 + 184 (I Sin[x])^7 Cos[x]^8 + 184 (I Sin[x])^8 Cos[x]^7 + 44 (I Sin[x])^5 Cos[x]^10 + 44 (I Sin[x])^10 Cos[x]^5 + 8 (I Sin[x])^4 Cos[x]^11 + 8 (I Sin[x])^11 Cos[x]^4) + Exp[-6 I y] (168 (I Sin[x])^5 Cos[x]^10 + 168 (I Sin[x])^10 Cos[x]^5 + 455 (I Sin[x])^7 Cos[x]^8 + 455 (I Sin[x])^8 Cos[x]^7 + 312 (I Sin[x])^9 Cos[x]^6 + 312 (I Sin[x])^6 Cos[x]^9 + 56 (I Sin[x])^4 Cos[x]^11 + 56 (I Sin[x])^11 Cos[x]^4 + 10 (I Sin[x])^3 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^3) + Exp[-4 I y] (329 (I Sin[x])^10 Cos[x]^5 + 329 (I Sin[x])^5 Cos[x]^10 + 920 (I Sin[x])^8 Cos[x]^7 + 920 (I Sin[x])^7 Cos[x]^8 + 639 (I Sin[x])^6 Cos[x]^9 + 639 (I Sin[x])^9 Cos[x]^6 + 99 (I Sin[x])^4 Cos[x]^11 + 99 (I Sin[x])^11 Cos[x]^4 + 15 (I Sin[x])^3 Cos[x]^12 + 15 (I Sin[x])^12 Cos[x]^3) + Exp[-2 I y] (249 (I Sin[x])^4 Cos[x]^11 + 249 (I Sin[x])^11 Cos[x]^4 + 944 (I Sin[x])^6 Cos[x]^9 + 944 (I Sin[x])^9 Cos[x]^6 + 1176 (I Sin[x])^8 Cos[x]^7 + 1176 (I Sin[x])^7 Cos[x]^8 + 548 (I Sin[x])^5 Cos[x]^10 + 548 (I Sin[x])^10 Cos[x]^5 + 74 (I Sin[x])^3 Cos[x]^12 + 74 (I Sin[x])^12 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^13 + 12 (I Sin[x])^13 Cos[x]^2) + Exp[0 I y] (1084 (I Sin[x])^9 Cos[x]^6 + 1084 (I Sin[x])^6 Cos[x]^9 + 259 (I Sin[x])^11 Cos[x]^4 + 259 (I Sin[x])^4 Cos[x]^11 + 1406 (I Sin[x])^7 Cos[x]^8 + 1406 (I Sin[x])^8 Cos[x]^7 + 602 (I Sin[x])^5 Cos[x]^10 + 602 (I Sin[x])^10 Cos[x]^5 + 71 (I Sin[x])^3 Cos[x]^12 + 71 (I Sin[x])^12 Cos[x]^3 + 10 (I Sin[x])^2 Cos[x]^13 + 10 (I Sin[x])^13 Cos[x]^2) + Exp[2 I y] (622 (I Sin[x])^5 Cos[x]^10 + 622 (I Sin[x])^10 Cos[x]^5 + 1019 (I Sin[x])^7 Cos[x]^8 + 1019 (I Sin[x])^8 Cos[x]^7 + 136 (I Sin[x])^3 Cos[x]^12 + 136 (I Sin[x])^12 Cos[x]^3 + 854 (I Sin[x])^6 Cos[x]^9 + 854 (I Sin[x])^9 Cos[x]^6 + 328 (I Sin[x])^4 Cos[x]^11 + 328 (I Sin[x])^11 Cos[x]^4 + 38 (I Sin[x])^2 Cos[x]^13 + 38 (I Sin[x])^13 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^14 + 6 (I Sin[x])^14 Cos[x]^1) + Exp[4 I y] (776 (I Sin[x])^8 Cos[x]^7 + 776 (I Sin[x])^7 Cos[x]^8 + 381 (I Sin[x])^10 Cos[x]^5 + 381 (I Sin[x])^5 Cos[x]^10 + 607 (I Sin[x])^6 Cos[x]^9 + 607 (I Sin[x])^9 Cos[x]^6 + 57 (I Sin[x])^12 Cos[x]^3 + 57 (I Sin[x])^3 Cos[x]^12 + 165 (I Sin[x])^4 Cos[x]^11 + 165 (I Sin[x])^11 Cos[x]^4 + 14 (I Sin[x])^13 Cos[x]^2 + 14 (I Sin[x])^2 Cos[x]^13 + 2 (I Sin[x])^1 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^1) + Exp[6 I y] (142 (I Sin[x])^4 Cos[x]^11 + 142 (I Sin[x])^11 Cos[x]^4 + 268 (I Sin[x])^6 Cos[x]^9 + 268 (I Sin[x])^9 Cos[x]^6 + 295 (I Sin[x])^8 Cos[x]^7 + 295 (I Sin[x])^7 Cos[x]^8 + 198 (I Sin[x])^5 Cos[x]^10 + 198 (I Sin[x])^10 Cos[x]^5 + 67 (I Sin[x])^3 Cos[x]^12 + 67 (I Sin[x])^12 Cos[x]^3 + 24 (I Sin[x])^2 Cos[x]^13 + 24 (I Sin[x])^13 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^14 + 6 (I Sin[x])^14 Cos[x]^1 + 1 Cos[x]^15 + 1 (I Sin[x])^15) + Exp[8 I y] (108 (I Sin[x])^9 Cos[x]^6 + 108 (I Sin[x])^6 Cos[x]^9 + 130 (I Sin[x])^8 Cos[x]^7 + 130 (I Sin[x])^7 Cos[x]^8 + 41 (I Sin[x])^11 Cos[x]^4 + 41 (I Sin[x])^4 Cos[x]^11 + 70 (I Sin[x])^10 Cos[x]^5 + 70 (I Sin[x])^5 Cos[x]^10 + 2 (I Sin[x])^13 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^13 + 13 (I Sin[x])^3 Cos[x]^12 + 13 (I Sin[x])^12 Cos[x]^3) + Exp[10 I y] (23 (I Sin[x])^5 Cos[x]^10 + 23 (I Sin[x])^10 Cos[x]^5 + 17 (I Sin[x])^7 Cos[x]^8 + 17 (I Sin[x])^8 Cos[x]^7 + 19 (I Sin[x])^9 Cos[x]^6 + 19 (I Sin[x])^6 Cos[x]^9 + 14 (I Sin[x])^4 Cos[x]^11 + 14 (I Sin[x])^11 Cos[x]^4 + 12 (I Sin[x])^3 Cos[x]^12 + 12 (I Sin[x])^12 Cos[x]^3 + 5 (I Sin[x])^2 Cos[x]^13 + 5 (I Sin[x])^13 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^1) + Exp[12 I y] (3 (I Sin[x])^10 Cos[x]^5 + 3 (I Sin[x])^5 Cos[x]^10 + 6 (I Sin[x])^8 Cos[x]^7 + 6 (I Sin[x])^7 Cos[x]^8 + 5 (I Sin[x])^9 Cos[x]^6 + 5 (I Sin[x])^6 Cos[x]^9) + Exp[14 I y] (1 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^4));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":602.6,"max_line_length":4294,"alphanum_fraction":0.5020466866} {"size":9227,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 15;\nname = \"15v1 1 3 2 3 4 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-14 I y] (1 (I Sin[x])^7 Cos[x]^8 + 1 (I Sin[x])^8 Cos[x]^7) + Exp[-12 I y] (6 (I Sin[x])^8 Cos[x]^7 + 6 (I Sin[x])^7 Cos[x]^8 + 4 (I Sin[x])^6 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^6 + 3 (I Sin[x])^5 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^5 + 1 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^4) + Exp[-10 I y] (32 (I Sin[x])^6 Cos[x]^9 + 32 (I Sin[x])^9 Cos[x]^6 + 38 (I Sin[x])^8 Cos[x]^7 + 38 (I Sin[x])^7 Cos[x]^8 + 15 (I Sin[x])^5 Cos[x]^10 + 15 (I Sin[x])^10 Cos[x]^5 + 5 (I Sin[x])^4 Cos[x]^11 + 5 (I Sin[x])^11 Cos[x]^4 + 1 (I Sin[x])^3 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^3) + Exp[-8 I y] (145 (I Sin[x])^7 Cos[x]^8 + 145 (I Sin[x])^8 Cos[x]^7 + 118 (I Sin[x])^6 Cos[x]^9 + 118 (I Sin[x])^9 Cos[x]^6 + 65 (I Sin[x])^5 Cos[x]^10 + 65 (I Sin[x])^10 Cos[x]^5 + 27 (I Sin[x])^4 Cos[x]^11 + 27 (I Sin[x])^11 Cos[x]^4 + 8 (I Sin[x])^3 Cos[x]^12 + 8 (I Sin[x])^12 Cos[x]^3 + 1 (I Sin[x])^2 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^2) + Exp[-6 I y] (194 (I Sin[x])^5 Cos[x]^10 + 194 (I Sin[x])^10 Cos[x]^5 + 375 (I Sin[x])^7 Cos[x]^8 + 375 (I Sin[x])^8 Cos[x]^7 + 288 (I Sin[x])^9 Cos[x]^6 + 288 (I Sin[x])^6 Cos[x]^9 + 98 (I Sin[x])^4 Cos[x]^11 + 98 (I Sin[x])^11 Cos[x]^4 + 36 (I Sin[x])^3 Cos[x]^12 + 36 (I Sin[x])^12 Cos[x]^3 + 9 (I Sin[x])^2 Cos[x]^13 + 9 (I Sin[x])^13 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^1) + Exp[-4 I y] (590 (I Sin[x])^6 Cos[x]^9 + 590 (I Sin[x])^9 Cos[x]^6 + 375 (I Sin[x])^5 Cos[x]^10 + 375 (I Sin[x])^10 Cos[x]^5 + 771 (I Sin[x])^8 Cos[x]^7 + 771 (I Sin[x])^7 Cos[x]^8 + 183 (I Sin[x])^4 Cos[x]^11 + 183 (I Sin[x])^11 Cos[x]^4 + 65 (I Sin[x])^3 Cos[x]^12 + 65 (I Sin[x])^12 Cos[x]^3 + 16 (I Sin[x])^2 Cos[x]^13 + 16 (I Sin[x])^13 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^1) + Exp[-2 I y] (903 (I Sin[x])^6 Cos[x]^9 + 903 (I Sin[x])^9 Cos[x]^6 + 1081 (I Sin[x])^8 Cos[x]^7 + 1081 (I Sin[x])^7 Cos[x]^8 + 569 (I Sin[x])^5 Cos[x]^10 + 569 (I Sin[x])^10 Cos[x]^5 + 290 (I Sin[x])^4 Cos[x]^11 + 290 (I Sin[x])^11 Cos[x]^4 + 116 (I Sin[x])^3 Cos[x]^12 + 116 (I Sin[x])^12 Cos[x]^3 + 35 (I Sin[x])^2 Cos[x]^13 + 35 (I Sin[x])^13 Cos[x]^2 + 8 (I Sin[x])^1 Cos[x]^14 + 8 (I Sin[x])^14 Cos[x]^1 + 1 Cos[x]^15 + 1 (I Sin[x])^15) + Exp[0 I y] (1374 (I Sin[x])^7 Cos[x]^8 + 1374 (I Sin[x])^8 Cos[x]^7 + 1090 (I Sin[x])^6 Cos[x]^9 + 1090 (I Sin[x])^9 Cos[x]^6 + 260 (I Sin[x])^4 Cos[x]^11 + 260 (I Sin[x])^11 Cos[x]^4 + 629 (I Sin[x])^5 Cos[x]^10 + 629 (I Sin[x])^10 Cos[x]^5 + 70 (I Sin[x])^3 Cos[x]^12 + 70 (I Sin[x])^12 Cos[x]^3 + 9 (I Sin[x])^2 Cos[x]^13 + 9 (I Sin[x])^13 Cos[x]^2) + Exp[2 I y] (1135 (I Sin[x])^7 Cos[x]^8 + 1135 (I Sin[x])^8 Cos[x]^7 + 568 (I Sin[x])^5 Cos[x]^10 + 568 (I Sin[x])^10 Cos[x]^5 + 870 (I Sin[x])^9 Cos[x]^6 + 870 (I Sin[x])^6 Cos[x]^9 + 286 (I Sin[x])^4 Cos[x]^11 + 286 (I Sin[x])^11 Cos[x]^4 + 110 (I Sin[x])^3 Cos[x]^12 + 110 (I Sin[x])^12 Cos[x]^3 + 30 (I Sin[x])^2 Cos[x]^13 + 30 (I Sin[x])^13 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^1) + Exp[4 I y] (644 (I Sin[x])^6 Cos[x]^9 + 644 (I Sin[x])^9 Cos[x]^6 + 313 (I Sin[x])^5 Cos[x]^10 + 313 (I Sin[x])^10 Cos[x]^5 + 13 (I Sin[x])^3 Cos[x]^12 + 13 (I Sin[x])^12 Cos[x]^3 + 938 (I Sin[x])^8 Cos[x]^7 + 938 (I Sin[x])^7 Cos[x]^8 + 94 (I Sin[x])^4 Cos[x]^11 + 94 (I Sin[x])^11 Cos[x]^4) + Exp[6 I y] (312 (I Sin[x])^6 Cos[x]^9 + 312 (I Sin[x])^9 Cos[x]^6 + 348 (I Sin[x])^8 Cos[x]^7 + 348 (I Sin[x])^7 Cos[x]^8 + 200 (I Sin[x])^5 Cos[x]^10 + 200 (I Sin[x])^10 Cos[x]^5 + 102 (I Sin[x])^4 Cos[x]^11 + 102 (I Sin[x])^11 Cos[x]^4 + 34 (I Sin[x])^3 Cos[x]^12 + 34 (I Sin[x])^12 Cos[x]^3 + 5 (I Sin[x])^2 Cos[x]^13 + 5 (I Sin[x])^13 Cos[x]^2) + Exp[8 I y] (189 (I Sin[x])^7 Cos[x]^8 + 189 (I Sin[x])^8 Cos[x]^7 + 124 (I Sin[x])^6 Cos[x]^9 + 124 (I Sin[x])^9 Cos[x]^6 + 7 (I Sin[x])^4 Cos[x]^11 + 7 (I Sin[x])^11 Cos[x]^4 + 44 (I Sin[x])^5 Cos[x]^10 + 44 (I Sin[x])^10 Cos[x]^5) + Exp[10 I y] (25 (I Sin[x])^7 Cos[x]^8 + 25 (I Sin[x])^8 Cos[x]^7 + 25 (I Sin[x])^9 Cos[x]^6 + 25 (I Sin[x])^6 Cos[x]^9 + 27 (I Sin[x])^5 Cos[x]^10 + 27 (I Sin[x])^10 Cos[x]^5 + 12 (I Sin[x])^4 Cos[x]^11 + 12 (I Sin[x])^11 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^3) + Exp[12 I y] (9 (I Sin[x])^8 Cos[x]^7 + 9 (I Sin[x])^7 Cos[x]^8 + 4 (I Sin[x])^6 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^6 + 1 (I Sin[x])^5 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^5) + Exp[14 I y] (1 (I Sin[x])^6 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^6))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-14 I y] (1 (I Sin[x])^7 Cos[x]^8 + 1 (I Sin[x])^8 Cos[x]^7) + Exp[-12 I y] (6 (I Sin[x])^8 Cos[x]^7 + 6 (I Sin[x])^7 Cos[x]^8 + 4 (I Sin[x])^6 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^6 + 3 (I Sin[x])^5 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TypeSystem`NestedGrid`PackagePrivate`$outputID$$]][{\n Key[\"NumberOfSamplesForReel\"]}, 1]], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"NumberOfSamplesForReel\"]}, \"RowHeader\", False], \n \"Mouse\"], \n ImageSize -> {{220.80000000000004`, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], Background -> \n GrayLevel[0.95], Alignment -> {Left, Baseline}], \n Item[\n Pane[\n Annotation[\n RawBoxes[\"300\"], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"NumberOfSamplesForReel\"]}, \"Item\", False], \"Mouse\"], \n ImageSize -> {{34, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], \n ItemSize -> {Full, Automatic}]}, {\n Item[\n Pane[\n Annotation[\n EventHandler[\n MouseAppearance[\n Mouseover[\"NumberOfSamplesForField\", \n Style[\n \"NumberOfSamplesForField\", FontColor -> \n RGBColor[\n 0.27450980392156865`, 0.5372549019607843, \n 0.792156862745098]]], \"LinkHand\"], {\"MouseClicked\", 1} :> \n TypeSystem`NestedGrid`PackagePrivate`updateState[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`localHold[\n TypeSystem`NestedGrid`PackagePrivate`$outputID$$]][{\n Key[\"NumberOfSamplesForField\"]}, 1]], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"NumberOfSamplesForField\"]}, \"RowHeader\", False], \n \"Mouse\"], \n ImageSize -> {{220.80000000000004`, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], Background -> \n GrayLevel[0.95], Alignment -> {Left, Baseline}], \n Item[\n Pane[\n Annotation[\n RawBoxes[\"0\"], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"NumberOfSamplesForField\"]}, \"Item\", False], \"Mouse\"], \n ImageSize -> {{34, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], \n ItemSize -> {Full, Automatic}]}, {\n Item[\n Pane[\n Annotation[\n EventHandler[\n MouseAppearance[\n Mouseover[\"SamplesFormatCode\", \n Style[\n \"SamplesFormatCode\", FontColor -> \n RGBColor[\n 0.27450980392156865`, 0.5372549019607843, \n 0.792156862745098]]], \"LinkHand\"], {\"MouseClicked\", 1} :> \n TypeSystem`NestedGrid`PackagePrivate`updateState[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`localHold[\n TypeSystem`NestedGrid`PackagePrivate`$outputID$$]][{\n Key[\"SamplesFormatCode\"]}, 1]], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"SamplesFormatCode\"]}, \"RowHeader\", False], \"Mouse\"], \n ImageSize -> {{220.80000000000004`, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], Background -> \n GrayLevel[0.95], Alignment -> {Left, Baseline}], \n Item[\n Pane[\n Annotation[\n RawBoxes[\"1\"], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"SamplesFormatCode\"]}, \"Item\", False], \"Mouse\"], \n ImageSize -> {{34, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], \n ItemSize -> {Full, Automatic}]}, {\n Item[\n Pane[\n Annotation[\n EventHandler[\n MouseAppearance[\n Mouseover[\"CDPFold\", \n Style[\n \"CDPFold\", FontColor -> \n RGBColor[\n 0.27450980392156865`, 0.5372549019607843, \n 0.792156862745098]]], \"LinkHand\"], {\"MouseClicked\", 1} :> \n TypeSystem`NestedGrid`PackagePrivate`updateState[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`localHold[\n TypeSystem`NestedGrid`PackagePrivate`$outputID$$]][{\n Key[\"CDPFold\"]}, 1]], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"CDPFold\"]}, \"RowHeader\", False], \"Mouse\"], \n ImageSize -> {{220.80000000000004`, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], Background -> \n GrayLevel[0.95], Alignment -> {Left, Baseline}], \n Item[\n Pane[\n Annotation[\n RawBoxes[\"0\"], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"CDPFold\"]}, \"Item\", False], \"Mouse\"], \n ImageSize -> {{34, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], \n ItemSize -> {Full, Automatic}]}, {\n Item[\n Pane[\n Annotation[\n EventHandler[\n MouseAppearance[\n Mouseover[\"TraceSortingCode\", \n Style[\n \"TraceSortingCode\", FontColor -> \n RGBColor[\n 0.27450980392156865`, 0.5372549019607843, \n 0.792156862745098]]], \"LinkHand\"], {\"MouseClicked\", 1} :> \n TypeSystem`NestedGrid`PackagePrivate`updateState[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`localHold[\n TypeSystem`NestedGrid`PackagePrivate`$outputID$$]][{\n Key[\"TraceSortingCode\"]}, 1]], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"TraceSortingCode\"]}, \"RowHeader\", False], \"Mouse\"], \n ImageSize -> {{220.80000000000004`, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], Background -> \n GrayLevel[0.95], Alignment -> {Left, Baseline}], \n Item[\n Pane[\n Annotation[\n RawBoxes[\"0\"], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"TraceSortingCode\"]}, \"Item\", False], \"Mouse\"], \n ImageSize -> {{34, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], \n ItemSize -> {Full, Automatic}]}, {\n Item[\n Pane[\n Annotation[\n EventHandler[\n MouseAppearance[\n Mouseover[\"VerticalSumCode\", \n Style[\n \"VerticalSumCode\", FontColor -> \n RGBColor[\n 0.27450980392156865`, 0.5372549019607843, \n 0.792156862745098]]], \"LinkHand\"], {\"MouseClicked\", 1} :> \n TypeSystem`NestedGrid`PackagePrivate`updateState[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`localHold[\n TypeSystem`NestedGrid`PackagePrivate`$outputID$$]][{\n Key[\"VerticalSumCode\"]}, 1]], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"VerticalSumCode\"]}, \"RowHeader\", False], \"Mouse\"], \n ImageSize -> {{220.80000000000004`, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], Background -> \n GrayLevel[0.95], Alignment -> {Left, Baseline}], \n Item[\n Pane[\n Annotation[\n RawBoxes[\"0\"], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"VerticalSumCode\"]}, \"Item\", False], \"Mouse\"], \n ImageSize -> {{34, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], \n ItemSize -> {Full, Automatic}]}, {\n Item[\n Pane[\n Annotation[\n EventHandler[\n MouseAppearance[\n Mouseover[\"SweepFrequencyAtStart\", \n Style[\n \"SweepFrequencyAtStart\", FontColor -> \n RGBColor[\n 0.27450980392156865`, 0.5372549019607843, \n 0.792156862745098]]], \"LinkHand\"], {\"MouseClicked\", 1} :> \n TypeSystem`NestedGrid`PackagePrivate`updateState[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`localHold[\n TypeSystem`NestedGrid`PackagePrivate`$outputID$$]][{\n Key[\"SweepFrequencyAtStart\"]}, 1]], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"SweepFrequencyAtStart\"]}, \"RowHeader\", False], \"Mouse\"],\n ImageSize -> {{220.80000000000004`, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], Background -> \n GrayLevel[0.95], Alignment -> {Left, Baseline}], \n Item[\n Pane[\n Annotation[\n RawBoxes[\"0\"], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"SweepFrequencyAtStart\"]}, \"Item\", False], \"Mouse\"], \n ImageSize -> {{34, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], \n ItemSize -> {Full, Automatic}]}, {\n Item[\n Pane[\n Annotation[\n EventHandler[\n MouseAppearance[\n Mouseover[\"SweepFrequencyAtEnd\", \n Style[\n \"SweepFrequencyAtEnd\", FontColor -> \n RGBColor[\n 0.27450980392156865`, 0.5372549019607843, \n 0.792156862745098]]], \"LinkHand\"], {\"MouseClicked\", 1} :> \n TypeSystem`NestedGrid`PackagePrivate`updateState[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`localHold[\n TypeSystem`NestedGrid`PackagePrivate`$outputID$$]][{\n Key[\"SweepFrequencyAtEnd\"]}, 1]], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"SweepFrequencyAtEnd\"]}, \"RowHeader\", False], \"Mouse\"], \n ImageSize -> {{220.80000000000004`, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], Background -> \n GrayLevel[0.95], Alignment -> {Left, Baseline}], \n Item[\n Pane[\n Annotation[\n RawBoxes[\"0\"], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"SweepFrequencyAtEnd\"]}, \"Item\", False], \"Mouse\"], \n ImageSize -> {{34, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], \n ItemSize -> {Full, Automatic}]}, {\n Item[\n Pane[\n Annotation[\n EventHandler[\n MouseAppearance[\n Mouseover[\"SweepLength\", \n Style[\n \"SweepLength\", FontColor -> \n RGBColor[\n 0.27450980392156865`, 0.5372549019607843, \n 0.792156862745098]]], \"LinkHand\"], {\"MouseClicked\", 1} :> \n TypeSystem`NestedGrid`PackagePrivate`updateState[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`localHold[\n TypeSystem`NestedGrid`PackagePrivate`$outputID$$]][{\n Key[\"SweepLength\"]}, 1]], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"SweepLength\"]}, \"RowHeader\", False], \"Mouse\"], \n ImageSize -> {{220.80000000000004`, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], Background -> \n GrayLevel[0.95], Alignment -> {Left, Baseline}], \n Item[\n Pane[\n Annotation[\n RawBoxes[\"0\"], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"SweepLength\"]}, \"Item\", False], \"Mouse\"], \n ImageSize -> {{34, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], \n ItemSize -> {Full, Automatic}]}, {\n Item[\n Pane[\n Annotation[\n EventHandler[\n MouseAppearance[\n Mouseover[\"SweepTypeCode\", \n Style[\n \"SweepTypeCode\", FontColor -> \n RGBColor[\n 0.27450980392156865`, 0.5372549019607843, \n 0.792156862745098]]], \"LinkHand\"], {\"MouseClicked\", 1} :> \n TypeSystem`NestedGrid`PackagePrivate`updateState[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`localHold[\n TypeSystem`NestedGrid`PackagePrivate`$outputID$$]][{\n Key[\"SweepTypeCode\"]}, 1]], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"SweepTypeCode\"]}, \"RowHeader\", False], \"Mouse\"], \n ImageSize -> {{220.80000000000004`, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], Background -> \n GrayLevel[0.95], Alignment -> {Left, Baseline}], \n Item[\n Pane[\n Annotation[\n RawBoxes[\"0\"], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"SweepTypeCode\"]}, \"Item\", False], \"Mouse\"], \n ImageSize -> {{34, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], \n ItemSize -> {Full, Automatic}]}, {\n Item[\n Pane[\n Annotation[\n EventHandler[\n MouseAppearance[\n Mouseover[\"TraceNumberOfSweepChannel\", \n Style[\n \"TraceNumberOfSweepChannel\", FontColor -> \n RGBColor[\n 0.27450980392156865`, 0.5372549019607843, \n 0.792156862745098]]], \"LinkHand\"], {\"MouseClicked\", 1} :> \n TypeSystem`NestedGrid`PackagePrivate`updateState[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`localHold[\n TypeSystem`NestedGrid`PackagePrivate`$outputID$$]][{\n Key[\"TraceNumberOfSweepChannel\"]}, 1]], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"TraceNumberOfSweepChannel\"]}, \"RowHeader\", False], \n \"Mouse\"], \n ImageSize -> {{220.80000000000004`, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], Background -> \n GrayLevel[0.95], Alignment -> {Left, Baseline}], \n Item[\n Pane[\n Annotation[\n RawBoxes[\"0\"], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"TraceNumberOfSweepChannel\"]}, \"Item\", False], \"Mouse\"], \n ImageSize -> {{34, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], \n ItemSize -> {Full, Automatic}]}, {\n Item[\n Pane[\n Annotation[\n EventHandler[\n MouseAppearance[\n Mouseover[\"SweepTraceTaperLengthAtStart\", \n Style[\n \"SweepTraceTaperLengthAtStart\", FontColor -> \n RGBColor[\n 0.27450980392156865`, 0.5372549019607843, \n 0.792156862745098]]], \"LinkHand\"], {\"MouseClicked\", 1} :> \n TypeSystem`NestedGrid`PackagePrivate`updateState[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`localHold[\n TypeSystem`NestedGrid`PackagePrivate`$outputID$$]][{\n Key[\"SweepTraceTaperLengthAtStart\"]}, 1]], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"SweepTraceTaperLengthAtStart\"]}, \"RowHeader\", False], \n \"Mouse\"], \n ImageSize -> {{220.80000000000004`, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], Background -> \n GrayLevel[0.95], Alignment -> {Left, Baseline}], \n Item[\n Pane[\n Annotation[\n RawBoxes[\"0\"], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"SweepTraceTaperLengthAtStart\"]}, \"Item\", False], \n \"Mouse\"], ImageSize -> {{34, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], \n ItemSize -> {Full, Automatic}]}, {\n Item[\n Pane[\n Annotation[\n EventHandler[\n MouseAppearance[\n Mouseover[\"SweepTraceTaperLength\", \n Style[\n \"SweepTraceTaperLength\", FontColor -> \n RGBColor[\n 0.27450980392156865`, 0.5372549019607843, \n 0.792156862745098]]], \"LinkHand\"], {\"MouseClicked\", 1} :> \n TypeSystem`NestedGrid`PackagePrivate`updateState[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`localHold[\n TypeSystem`NestedGrid`PackagePrivate`$outputID$$]][{\n Key[\"SweepTraceTaperLength\"]}, 1]], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"SweepTraceTaperLength\"]}, \"RowHeader\", False], \"Mouse\"],\n ImageSize -> {{220.80000000000004`, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], Background -> \n GrayLevel[0.95], Alignment -> {Left, Baseline}], \n Item[\n Pane[\n Annotation[\n RawBoxes[\"0\"], \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n \"04fdea4c-58b9-4a29-b2f9-eee649a0b654\"][{\n Key[\"SweepTraceTaperLength\"]}, \"Item\", False], \"Mouse\"], \n ImageSize -> {{34, Full}, Automatic}, \n ImageMargins -> {{5, 3}, {4, 5}}], \n ItemSize -> {Full, Automatic}]}, {\n Item[\n Deploy[\n Pane[\n Row[{\n Spacer[2], \n Style[\n Row[{\n Button[\n MouseAppearance[\n Mouseover[\n Graphics[{{\n EdgeForm[None], \n FaceForm[None], \n Rectangle[{0, 0}, {18, 18}, RoundingRadius -> 2]}, \n Rotate[\n Translate[{\n CapForm[Round], \n RGBColor[\n 0.5372549019607843, 0.5372549019607843, \n 0.5372549019607843], \n Line[{{0, 0}, {4, 5}, {8, 0}}], \n Line[{{0, 5}, {8, 5}}]}, {5, 6.5}], 0, {9, 9}]}, \n ImageSize -> (1 -> 1), ImagePadding -> {{0, 1}, {1, 0}}, \n BaselinePosition -> Scaled[0.35]], \n Graphics[{{\n EdgeForm[\n RGBColor[\n 0.27450980392156865`, 0.5411764705882353, \n 0.796078431372549]], \n FaceForm[None], \n Rectangle[{0, 0}, {18, 18}, RoundingRadius -> 2]}, \n Rotate[\n Translate[{\n CapForm[Round], \n RGBColor[\n 0.27450980392156865`, 0.5411764705882353, \n 0.796078431372549], \n Line[{{0, 0}, {4, 5}, {8, 0}}], \n Line[{{0, 5}, {8, 5}}]}, {5, 6.5}], 0, {9, 9}]}, \n ImageSize -> (1 -> 1), ImagePadding -> {{0, 1}, {1, 0}}, \n BaselinePosition -> Scaled[0.35]]], \"LinkHand\"], \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$ = \n Clip[TypeSystem`NestedGrid`PackagePrivate`$vPos$$ - 20 \n If[True, 27, 1], {1, 27 - -20 + 1}]; \n TypeSystem`NestedGrid`PackagePrivate`updateState[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`localHold[\n TypeSystem`NestedGrid`PackagePrivate`$outputID$$], True][\n TypeSystem`NestedGrid`PackagePrivate`$path$$], Appearance -> \n None], \n Button[\n MouseAppearance[\n Mouseover[\n Graphics[{{\n EdgeForm[None], \n FaceForm[None], \n Rectangle[{0, 0}, {18, 18}, RoundingRadius -> 2]}, \n Rotate[\n Translate[{\n CapForm[Round], \n RGBColor[\n 0.5372549019607843, 0.5372549019607843, \n 0.5372549019607843], \n Line[{{0, 0}, {4, 5}, {8, 0}}]}, {5, 6.5}], 0, {9, 9}]}, \n ImageSize -> (1 -> 1), ImagePadding -> {{0, 1}, {1, 0}}, \n BaselinePosition -> Scaled[0.35]], \n Graphics[{{\n EdgeForm[\n RGBColor[\n 0.27450980392156865`, 0.5411764705882353, \n 0.796078431372549]], \n FaceForm[None], \n Rectangle[{0, 0}, {18, 18}, RoundingRadius -> 2]}, \n Rotate[\n Translate[{\n CapForm[Round], \n RGBColor[\n 0.27450980392156865`, 0.5411764705882353, \n 0.796078431372549], \n Line[{{0, 0}, {4, 5}, {8, 0}}]}, {5, 6.5}], 0, {9, 9}]}, \n ImageSize -> (1 -> 1), ImagePadding -> {{0, 1}, {1, 0}}, \n BaselinePosition -> Scaled[0.35]]], \"LinkHand\"], \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$ = \n Clip[TypeSystem`NestedGrid`PackagePrivate`$vPos$$ - 20 \n If[False, 27, 1], {1, 27 - -20 + 1}]; \n TypeSystem`NestedGrid`PackagePrivate`updateState[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`localHold[\n TypeSystem`NestedGrid`PackagePrivate`$outputID$$], True][\n TypeSystem`NestedGrid`PackagePrivate`$path$$], Appearance -> \n None], \" \", \n Style[\n Mouseover[\n Row[{\"rows \", 1, \"\\[Dash]\", 20, \" of \", \n Style[\n 27, FontColor -> GrayLevel[0], FontWeight -> \"Medium\"]}, \n BaseStyle -> {\n FontSize -> 8., FontColor -> \n RGBColor[\n 0.5098039215686274, 0.5098039215686274, \n 0.5098039215686274]}], \n Row[{\"rows \", 1, \"\\[Dash]\", 20, \" of \", \n Style[\n 27, FontColor -> GrayLevel[0], FontWeight -> \"Medium\"]}, \n BaseStyle -> {\n FontSize -> 8., FontColor -> \n RGBColor[\n 0.5098039215686274, 0.5098039215686274, \n 0.5098039215686274]}]], ContextMenu -> {\n MenuItem[\"Hide\", \n KernelExecute[\n \n TypeSystem`NestedGrid`PackagePrivate`adjustLimits[{\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`$outputID$$}, \"Rows\",\n 1, {}]], MenuEvaluator -> Automatic], \n MenuItem[\"Show up to 10 Rows\", \n KernelExecute[\n \n TypeSystem`NestedGrid`PackagePrivate`adjustLimits[{\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`$outputID$$}, \"Rows\",\n 10, {}]], MenuEvaluator -> Automatic], \n MenuItem[\"Show up to 30 Rows\", \n KernelExecute[\n \n TypeSystem`NestedGrid`PackagePrivate`adjustLimits[{\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`$outputID$$}, \"Rows\",\n 30, {}]], MenuEvaluator -> Automatic], \n MenuItem[\"Show up to 100 Rows\", \n KernelExecute[\n \n TypeSystem`NestedGrid`PackagePrivate`adjustLimits[{\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`$outputID$$}, \"Rows\",\n 100, {}]], MenuEvaluator -> Automatic], \n MenuItem[\"Show All\", \n KernelExecute[\n \n TypeSystem`NestedGrid`PackagePrivate`adjustLimits[{\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`$outputID$$}, \"Rows\",\n 100000000, {}]], MenuEvaluator -> Automatic]}], \" \", \n Button[\n MouseAppearance[\n Mouseover[\n Graphics[{{\n EdgeForm[None], \n FaceForm[None], \n Rectangle[{0, 0}, {18, 18}, RoundingRadius -> 2]}, \n Rotate[\n Translate[{\n CapForm[Round], \n RGBColor[\n 0.5372549019607843, 0.5372549019607843, \n 0.5372549019607843], \n Line[{{0, 0}, {4, 5}, {8, 0}}]}, {5, 6.5}], 180 Degree, {\n 9, 9}]}, ImageSize -> (1 -> 1), \n ImagePadding -> {{0, 1}, {1, 0}}, BaselinePosition -> \n Scaled[0.35]], \n Graphics[{{\n EdgeForm[\n RGBColor[\n 0.27450980392156865`, 0.5411764705882353, \n 0.796078431372549]], \n FaceForm[None], \n Rectangle[{0, 0}, {18, 18}, RoundingRadius -> 2]}, \n Rotate[\n Translate[{\n CapForm[Round], \n RGBColor[\n 0.27450980392156865`, 0.5411764705882353, \n 0.796078431372549], \n Line[{{0, 0}, {4, 5}, {8, 0}}]}, {5, 6.5}], 180 Degree, {\n 9, 9}]}, ImageSize -> (1 -> 1), \n ImagePadding -> {{0, 1}, {1, 0}}, BaselinePosition -> \n Scaled[0.35]]], \"LinkHand\"], \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$ = \n Clip[TypeSystem`NestedGrid`PackagePrivate`$vPos$$ + \n 20 If[False, 27, 1], {1, 27 - 20 + 1}]; \n TypeSystem`NestedGrid`PackagePrivate`updateState[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`localHold[\n TypeSystem`NestedGrid`PackagePrivate`$outputID$$], True][\n TypeSystem`NestedGrid`PackagePrivate`$path$$], Appearance -> \n None], \n Button[\n MouseAppearance[\n Mouseover[\n Graphics[{{\n EdgeForm[None], \n FaceForm[None], \n Rectangle[{0, 0}, {18, 18}, RoundingRadius -> 2]}, \n Rotate[\n Translate[{\n CapForm[Round], \n RGBColor[\n 0.5372549019607843, 0.5372549019607843, \n 0.5372549019607843], \n Line[{{0, 0}, {4, 5}, {8, 0}}], \n Line[{{0, 5}, {8, 5}}]}, {5, 6.5}], 180 Degree, {9, 9}]}, \n ImageSize -> (1 -> 1), ImagePadding -> {{0, 1}, {1, 0}}, \n BaselinePosition -> Scaled[0.35]], \n Graphics[{{\n EdgeForm[\n RGBColor[\n 0.27450980392156865`, 0.5411764705882353, \n 0.796078431372549]], \n FaceForm[None], \n Rectangle[{0, 0}, {18, 18}, RoundingRadius -> 2]}, \n Rotate[\n Translate[{\n CapForm[Round], \n RGBColor[\n 0.27450980392156865`, 0.5411764705882353, \n 0.796078431372549], \n Line[{{0, 0}, {4, 5}, {8, 0}}], \n Line[{{0, 5}, {8, 5}}]}, {5, 6.5}], 180 Degree, {9, 9}]}, \n ImageSize -> (1 -> 1), ImagePadding -> {{0, 1}, {1, 0}}, \n BaselinePosition -> Scaled[0.35]]], \"LinkHand\"], \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$ = \n Clip[TypeSystem`NestedGrid`PackagePrivate`$vPos$$ + \n 20 If[True, 27, 1], {1, 27 - 20 + 1}]; \n TypeSystem`NestedGrid`PackagePrivate`updateState[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`localHold[\n TypeSystem`NestedGrid`PackagePrivate`$outputID$$], True][\n TypeSystem`NestedGrid`PackagePrivate`$path$$], Appearance -> \n None]}], ContextMenu -> {}], \n Graphics[{\n RGBColor[\n 0.8196078431372549, 0.8196078431372549, \n 0.8196078431372549], \n Line[{{0, 0}, {0, 19}}]}, ImageSize -> (1 -> 1), \n ImagePadding -> {{0, 0}, {0, 0}}, BaselinePosition -> \n Scaled[0.35]]}], ImageMargins -> {{0, -1}, {-1, 1}}]], \n Background -> \n RGBColor[\n 0.9764705882352941, 0.9764705882352941, 0.9764705882352941], \n Alignment -> {Left, Top}], SpanFromLeft}}, \n BaseStyle -> {\n ContextMenu -> \n Dynamic[TypeSystem`NestedGrid`PackagePrivate`$contextMenuTrigger; \n Which[TypeSystem`NestedGrid`PackagePrivate`$lastOutputID =!= \n TypeSystem`NestedGrid`PackagePrivate`$outputID$$, {}, \n TypeSystem`NestedGrid`PackagePrivate`$contextMenuTrigger === \n TypeSystem`NestedGrid`PackagePrivate`$lastContextMenuTrigger, \n TypeSystem`NestedGrid`PackagePrivate`$lastContextMenu, True, \n TypeSystem`NestedGrid`PackagePrivate`$lastContextMenuTrigger = \n TypeSystem`NestedGrid`PackagePrivate`$contextMenuTrigger; \n TypeSystem`NestedGrid`PackagePrivate`$lastContextMenu = \n Block[{TypeSystem`NestedGrid`PackagePrivate`$globalScrollPos = \\\n{TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$}}, \n With[{\n TypeSystem`NestedGrid`PackagePrivate`lastPath$ = \n TypeSystem`NestedGrid`PackagePrivate`$lastPath, \n TypeSystem`NestedGrid`PackagePrivate`lastPathType$ = \n TypeSystem`NestedGrid`PackagePrivate`$lastPathType, \n TypeSystem`NestedGrid`PackagePrivate`isLeafHeader$ = \n TypeSystem`NestedGrid`PackagePrivate`$\\\nlastPathIsLeafHeader, TypeSystem`NestedGrid`PackagePrivate`headerHidden$ = And[\n MatchQ[TypeSystem`NestedGrid`PackagePrivate`$lastPathType, \n Alternatives[\"RowHeader\", \"ColumnHeader\"]], \n TypeSystem`NestedGrid`PackagePrivate`headerHiddenQ[\n TypeSystem`NestedGrid`PackagePrivate`$lastPath, \n TypeSystem`NestedGrid`PackagePrivate`$state$$]], \n TypeSystem`NestedGrid`PackagePrivate`allHidden$ = \n TypeSystem`NestedGrid`PackagePrivate`allHiddenQ[\n TypeSystem`NestedGrid`PackagePrivate`$lastPath, \n TypeSystem`NestedGrid`PackagePrivate`$state$$], \n TypeSystem`NestedGrid`PackagePrivate`anyHidden$ = \n TypeSystem`NestedGrid`PackagePrivate`anyHiddenQ[\n TypeSystem`NestedGrid`PackagePrivate`$lastPath, \n TypeSystem`NestedGrid`PackagePrivate`$state$$], \n TypeSystem`NestedGrid`PackagePrivate`sortDirection$ = \n TypeSystem`NestedGrid`PackagePrivate`columnSortDirection[\n TypeSystem`NestedGrid`PackagePrivate`$lastPath, \n TypeSystem`NestedGrid`PackagePrivate`$state$$[\n \"SortPaths\"], \n TypeSystem`NestedGrid`PackagePrivate`$state$$[\n \"SortDirections\"]], \n TypeSystem`NestedGrid`PackagePrivate`haveData$ = Not[\n FailureQ[\n TypeSystem`NestedGrid`PackagePrivate`datasetInitialData[\n TypeSystem`NestedGrid`PackagePrivate`$state$$]]], \n TypeSystem`NestedGrid`PackagePrivate`isKeyDummy$ = Not[\n FreeQ[\n TypeSystem`NestedGrid`PackagePrivate`$lastPath, Keys]]}, \n Join[{\n If[\n Or[\n Not[TypeSystem`NestedGrid`PackagePrivate`haveData$], \n Not[TypeSystem`NestedGrid`PackagePrivate`anyHidden$], \n TypeSystem`NestedGrid`PackagePrivate`isKeyDummy$], \n Nothing, \n MenuItem[\n StringJoin[\"Show \", \n Which[\n TypeSystem`NestedGrid`PackagePrivate`lastPathType$ == \n \"Item\", \"\", \n TypeSystem`NestedGrid`PackagePrivate`lastPathType$ == \n \"RowHeader\", \"Row\", \n TypeSystem`NestedGrid`PackagePrivate`lastPathType$ == \n \"ColumnHeader\", \"Column\", True, \"\"]], \n KernelExecute[\n TypeSystem`NestedGrid`PackagePrivate`updateHiddenItems[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`localHold[\n TypeSystem`NestedGrid`PackagePrivate`$outputID$$]][\n TypeSystem`NestedGrid`PackagePrivate`lastPath$, \n \"remove\"]], MenuEvaluator -> Automatic]], \n If[\n Or[\n Not[TypeSystem`NestedGrid`PackagePrivate`haveData$], \n TypeSystem`NestedGrid`PackagePrivate`pathEmptyQ[\n TypeSystem`NestedGrid`PackagePrivate`$lastPath, \n TypeSystem`NestedGrid`PackagePrivate`$state$$], \n TypeSystem`NestedGrid`PackagePrivate`isKeyDummy$, \n And[\n TypeSystem`NestedGrid`PackagePrivate`allHidden$, \n TypeSystem`NestedGrid`PackagePrivate`headerHidden$]], \n Nothing, \n MenuItem[\n StringJoin[\"Hide \", \n Which[\n TypeSystem`NestedGrid`PackagePrivate`lastPathType$ == \n \"Item\", \"\", \n TypeSystem`NestedGrid`PackagePrivate`lastPathType$ == \n \"RowHeader\", \"Row\", \n TypeSystem`NestedGrid`PackagePrivate`lastPathType$ == \n \"ColumnHeader\", \"Column\", True, \"\"]], \n KernelExecute[\n TypeSystem`NestedGrid`PackagePrivate`updateHiddenItems[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`localHold[\n TypeSystem`NestedGrid`PackagePrivate`$outputID$$]][\n TypeSystem`NestedGrid`PackagePrivate`lastPath$, \"add\"]], \n MenuEvaluator -> Automatic]], Delimiter}, \n If[\n And[TypeSystem`NestedGrid`PackagePrivate`haveData$, \n MatchQ[TypeSystem`NestedGrid`PackagePrivate`lastPathType$, \n Alternatives[\"ColumnHeader\", \"KeyDummy\"]], \n TypeSystem`NestedGrid`PackagePrivate`isLeafHeader$, \n Not[TypeSystem`NestedGrid`PackagePrivate`allHidden$]], {\n If[\n TypeSystem`NestedGrid`PackagePrivate`sortDirection$ =!= \n \"Ascending\", \n MenuItem[\"Sort\", \n KernelExecute[\n TypeSystem`NestedGrid`PackagePrivate`updateSort[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`$outputID$$][\n TypeSystem`NestedGrid`PackagePrivate`lastPath$, \n \"Ascending\"]], MenuEvaluator -> Automatic], Nothing], \n If[\n TypeSystem`NestedGrid`PackagePrivate`sortDirection$ =!= \n \"Descending\", \n MenuItem[\"Reverse Sort\", \n KernelExecute[\n TypeSystem`NestedGrid`PackagePrivate`updateSort[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`$outputID$$][\n TypeSystem`NestedGrid`PackagePrivate`lastPath$, \n \"Descending\"]], MenuEvaluator -> Automatic], Nothing], \n If[\n TypeSystem`NestedGrid`PackagePrivate`sortDirection$ =!= \n None, \n MenuItem[\"Unsort\", \n KernelExecute[\n TypeSystem`NestedGrid`PackagePrivate`updateSort[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`$outputID$$][\n TypeSystem`NestedGrid`PackagePrivate`lastPath$, None]], \n MenuEvaluator -> Automatic], Nothing], Delimiter}, {}], {\n MenuItem[\"Copy Position to Clipboard\", \n KernelExecute[\n TypeSystem`NestedGrid`PackagePrivate`toCurrentPosition[\n TypeSystem`NestedGrid`PackagePrivate`copyClip]], \n MenuEvaluator -> Automatic], \n MenuItem[\"Copy Data to Clipboard\", \n KernelExecute[\n TypeSystem`NestedGrid`PackagePrivate`toCurrentData[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`copyClip]], \n MenuEvaluator -> Automatic], Delimiter, \n MenuItem[\"Paste Position in New Cell\", \n KernelExecute[\n TypeSystem`NestedGrid`PackagePrivate`toCurrentPosition[\n TypeSystem`NestedGrid`PackagePrivate`cellPaste]], \n MenuEvaluator -> Automatic], \n MenuItem[\"Paste Data in New Cell\", \n KernelExecute[\n TypeSystem`NestedGrid`PackagePrivate`toCurrentData[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`cellPaste]], \n MenuEvaluator -> Automatic]}]]]]], FontFamily -> \n \"Verdana\", FontSize -> 12}, Spacings -> {0, 0}, Alignment -> Left,\n Dividers -> All, FrameStyle -> GrayLevel[0.7490196078431373], \n BaseStyle -> {FontFamily -> \"Verdana\", FontSize -> 12}], \n LineBreakWithin -> False, ContextMenu -> {}, NumberMarks -> False, \n ShowAutoStyles -> False]], \n TypeSystem`NestedGrid`PackagePrivate`initialQ = True}, \n Dynamic[\n TypeSystem`NestedGrid`PackagePrivate`setupViewPath[\n TypeSystem`NestedGrid`PackagePrivate`$path$$, If[\n Not[TypeSystem`NestedGrid`PackagePrivate`initialQ], \n Module[{\n TypeSystem`NestedGrid`PackagePrivate`tmpGrid$ = $Failed, \n TypeSystem`NestedGrid`PackagePrivate`tmpData$ = \n TypeSystem`NestedGrid`PackagePrivate`datasetData[\n TypeSystem`NestedGrid`PackagePrivate`$state$$]}, \n TypeSystem`NestedGrid`PackagePrivate`tmpGrid$ = If[\n FailureQ[TypeSystem`NestedGrid`PackagePrivate`tmpData$], \n TypeSystem`NestedGrid`PackagePrivate`renderedGrid, \n TypeSystem`NestedGrid`PackagePrivate`renderGrid[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`localHold[\n TypeSystem`NestedGrid`PackagePrivate`$outputID$$]][\n TypeSystem`NestedGrid`PackagePrivate`tmpData$]]; If[\n Not[\n FailureQ[TypeSystem`NestedGrid`PackagePrivate`tmpGrid$]], \n TypeSystem`NestedGrid`PackagePrivate`renderedGrid = \n TypeSystem`NestedGrid`PackagePrivate`tmpGrid$]; Null]]; \n TypeSystem`NestedGrid`PackagePrivate`initialQ = False; \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$; \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$; If[\n FailureQ[TypeSystem`NestedGrid`PackagePrivate`renderedGrid], \n TypeSystem`SparseGrid[\n TypeSystem`H[\"(data no longer present)\"]], \n If[GeneralUtilities`$DebugMode, \n Row[{TypeSystem`NestedGrid`PackagePrivate`renderedGrid, \" \", \n TypeSystem`NestedGrid`PackagePrivate`formatState[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$]}], \n TypeSystem`NestedGrid`PackagePrivate`renderedGrid]]], \n TrackedSymbols :> {\n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$}], \n DynamicModuleValues :> {}], \n TypeSystem`NestedGrid`PackagePrivate`$topBar$$ = Dynamic[\n TypeSystem`NestedGrid`PackagePrivate`makeFramedBar[\n TypeSystem`PackageScope`SubViewPathbar[\n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`updateState[\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$path$$, \n TypeSystem`NestedGrid`PackagePrivate`$vPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$hPos$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$, \n TypeSystem`NestedGrid`PackagePrivate`localHold[\n TypeSystem`NestedGrid`PackagePrivate`$outputID$$]]]], \n TrackedSymbols :> {TypeSystem`NestedGrid`PackagePrivate`$path$$}], \n TypeSystem`NestedGrid`PackagePrivate`$bottomBar$$ = Style[\n Framed[\n Dynamic[\n Replace[\n TypeSystem`NestedGrid`PackagePrivate`mouseAnnotation$$, {\n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n TypeSystem`NestedGrid`PackagePrivate`$outputID$$][Null, \n Blank[]] -> \"\", \n TypeSystem`NestedGrid`PackagePrivate`$SliceMarker[\n TypeSystem`NestedGrid`PackagePrivate`$outputID$$][\n Pattern[TypeSystem`NestedGrid`PackagePrivate`path$, \n Blank[]], \n Pattern[TypeSystem`NestedGrid`PackagePrivate`pathType$, \n Blank[]], \n Pattern[TypeSystem`NestedGrid`PackagePrivate`isLeafHeader$, \n Blank[]]] :> (\n Increment[TypeSystem`NestedGrid`PackagePrivate`$contextMenuTrigger]; \n TypeSystem`NestedGrid`PackagePrivate`$lastPath = \n TypeSystem`NestedGrid`PackagePrivate`path$; \n TypeSystem`NestedGrid`PackagePrivate`$lastPathType = \n TypeSystem`NestedGrid`PackagePrivate`pathType$; \n TypeSystem`NestedGrid`PackagePrivate`$lastPathIsLeafHeader = \n TypeSystem`NestedGrid`PackagePrivate`isLeafHeader$; \n TypeSystem`NestedGrid`PackagePrivate`$lastOutputID = \n TypeSystem`NestedGrid`PackagePrivate`$outputID$$; \n TypeSystem`NestedGrid`PackagePrivate`makePathTrail[\n TypeSystem`NestedGrid`PackagePrivate`path$, \n TypeSystem`NestedGrid`PackagePrivate`makePathElements]), Null :> \n Spacer[10], Blank[] :> Spacer[10]}], \n TrackedSymbols :> {\n TypeSystem`NestedGrid`PackagePrivate`mouseAnnotation$$}], FrameStyle -> \n None, ImageMargins -> 0, FrameMargins -> 0, Alignment -> Top, \n ImageSize -> {Automatic, 15}], FontSize -> 1], \n TypeSystem`NestedGrid`PackagePrivate`mouseAnnotation$$ = Null}, \n DynamicWrapperBox[\n DynamicBox[ToBoxes[\n Dataset`DatasetContent[\n 2, \"Path\" -> Hold[TypeSystem`NestedGrid`PackagePrivate`$path$$], \n \"Grid\" -> Hold[TypeSystem`NestedGrid`PackagePrivate`$grid$$], \"State\" -> \n Hold[TypeSystem`NestedGrid`PackagePrivate`$state$$], \"VPos\" -> \n Hold[TypeSystem`NestedGrid`PackagePrivate`$vPos$$], \"HPos\" -> \n Hold[TypeSystem`NestedGrid`PackagePrivate`$hPos$$], \"TopBar\" -> \n Hold[TypeSystem`NestedGrid`PackagePrivate`$topBar$$], \"BottomBar\" -> \n Hold[TypeSystem`NestedGrid`PackagePrivate`$bottomBar$$], \"OutputID\" -> \n Hold[\n TypeSystem`NestedGrid`PackagePrivate`localHold[\n TypeSystem`NestedGrid`PackagePrivate`$outputID$$]]], StandardForm],\n ImageSizeCache->{308., {255., 261.}},\n TrackedSymbols:>{\n TypeSystem`NestedGrid`PackagePrivate`$state$$, \n TypeSystem`NestedGrid`PackagePrivate`$grid$$}], \n TypeSystem`NestedGrid`PackagePrivate`mouseAnnotation$$ = \n MouseAnnotation[],\n ImageSizeCache->{308., {255., 261.}}],\n BaseStyle->{LineBreakWithin -> False},\n DynamicModuleValues:>{},\n Initialization:>\n Block[{$ContextPath = $ContextPath}, Needs[\"TypeSystem`\"]; \n Needs[\"Dataset`\"]; \n TypeSystem`NestedGrid`PackagePrivate`$outputID$$ = CreateUUID[]],\n UnsavedVariables:>{TypeSystem`NestedGrid`PackagePrivate`$outputID$$}],\n Deploy,\n DefaultBaseStyle->\"Deploy\"],\n Dataset`InterpretDataset[1],\n Editable->False,\n SelectWithContents->True,\n Selectable->False]], \"Output\",\n CellLabel->\"Out[10]=\",ExpressionUUID->\"702da599-783c-4e7c-9721-85b23af62fbe\"]\n}, Open ]],\n\nCell[CellGroupData[{\n\nCell[BoxData[\n RowBox[{\"ArrayPlot\", \"[\", \n RowBox[{\n RowBox[{\"marmousi\", \"[\", \n RowBox[{\"[\", \"1\", \"]\"}], \"]\"}], \"[\", \n RowBox[{\"[\", \n RowBox[{\"\\\"\\\\\"\", \",\", \" \", \"All\", \",\", \" \", \"\\\"\\\\\"\"}], \n \"]\"}], \"]\"}], \"]\"}]], \"Code\",\n CellLabel->\"In[21]:=\",ExpressionUUID->\"d867bc86-53ef-493d-af8a-6305482f2325\"],\n\nCell[BoxData[\n 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XcVXwqxk6NetDtg+Opb4oONT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\neX7EV\/ym8ThO9IsbXwmtcH\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ngEfCXNhi6AMM0yX\/FfemB\/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\nCE7ZkBt5TakPY\/+1WBb5ijfexHH9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McUn4W9xO+0g8ocj9FP6D4RJ+11vcN2hdlPMrB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\nbDfHK9xF4m4M81h+e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l14k54+j++ihZf6Y+u8D1PMP8RfKW9DF9pPSsT99afCqkP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\nnM56QjXPOQcf2G9SVzNvMifRup+B6z6Wkusun1k4NT\/Hy+nkKyUiqfjMSzS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8N7ic8FZc5t0hNrzUtijzatyJwlvt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\nfoLKVyV4zsudfGV73pNxGHWxcwkZZx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Hdpk5nHorN9W1z7z+oNLnK+yi9g+Irf\/29nRjfUftXuc5TTeX+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\nr963hvqrlow6uZlADcm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TiK2ScQ+p4a8hf7W4Dn2etI\/p3+kgbQ1vDWR3vwtE1fuC6W4xW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\nPAnz8T78SbWkb\/B9HE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v85f8lXegxK98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\nAv4tY98qyb\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6+YA3wlQqCboDzy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\n36nMn17pa\/GJ18Bd+9qEYT+3+sMbtV2W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(I Sin[x])^13 Cos[x]^3 + 8 (I Sin[x])^4 Cos[x]^12 + 8 (I Sin[x])^12 Cos[x]^4 + 23 (I Sin[x])^6 Cos[x]^10 + 23 (I Sin[x])^10 Cos[x]^6 + 36 (I Sin[x])^8 Cos[x]^8) + Exp[13 I y] (4 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^7 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^7 + 1 (I Sin[x])^12 Cos[x]^4 + 1 (I Sin[x])^4 Cos[x]^12 + 5 (I Sin[x])^6 Cos[x]^10 + 5 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^8 Cos[x]^8) + Exp[15 I y] (1 (I Sin[x])^10 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^10))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^6 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^6) + Exp[-13 I y] (1 (I Sin[x])^5 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^5 + 7 (I Sin[x])^9 Cos[x]^7 + 7 (I Sin[x])^7 Cos[x]^9 + 3 (I Sin[x])^6 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^6 + 8 (I Sin[x])^8 Cos[x]^8) + Exp[-11 I y] (45 (I Sin[x])^7 Cos[x]^9 + 45 (I Sin[x])^9 Cos[x]^7 + 11 (I Sin[x])^5 Cos[x]^11 + 11 (I Sin[x])^11 Cos[x]^5 + 46 (I Sin[x])^8 Cos[x]^8 + 25 (I Sin[x])^6 Cos[x]^10 + 25 (I Sin[x])^10 Cos[x]^6 + 1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4) + Exp[-9 I y] (109 (I Sin[x])^6 Cos[x]^10 + 109 (I Sin[x])^10 Cos[x]^6 + 12 (I Sin[x])^4 Cos[x]^12 + 12 (I Sin[x])^12 Cos[x]^4 + 44 (I Sin[x])^5 Cos[x]^11 + 44 (I Sin[x])^11 Cos[x]^5 + 179 (I Sin[x])^9 Cos[x]^7 + 179 (I Sin[x])^7 Cos[x]^9 + 220 (I Sin[x])^8 Cos[x]^8 + 1 (I Sin[x])^3 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^3) + Exp[-7 I y] (319 (I Sin[x])^6 Cos[x]^10 + 319 (I Sin[x])^10 Cos[x]^6 + 676 (I Sin[x])^8 Cos[x]^8 + 543 (I Sin[x])^9 Cos[x]^7 + 543 (I Sin[x])^7 Cos[x]^9 + 125 (I Sin[x])^5 Cos[x]^11 + 125 (I Sin[x])^11 Cos[x]^5 + 36 (I Sin[x])^4 Cos[x]^12 + 36 (I Sin[x])^12 Cos[x]^4 + 4 (I Sin[x])^3 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^3) + Exp[-5 I y] (1074 (I Sin[x])^7 Cos[x]^9 + 1074 (I Sin[x])^9 Cos[x]^7 + 400 (I Sin[x])^5 Cos[x]^11 + 400 (I Sin[x])^11 Cos[x]^5 + 749 (I Sin[x])^6 Cos[x]^10 + 749 (I Sin[x])^10 Cos[x]^6 + 1176 (I Sin[x])^8 Cos[x]^8 + 150 (I Sin[x])^12 Cos[x]^4 + 150 (I Sin[x])^4 Cos[x]^12 + 38 (I Sin[x])^3 Cos[x]^13 + 38 (I Sin[x])^13 Cos[x]^3 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2) + Exp[-3 I y] (1894 (I Sin[x])^7 Cos[x]^9 + 1894 (I Sin[x])^9 Cos[x]^7 + 586 (I Sin[x])^5 Cos[x]^11 + 586 (I Sin[x])^11 Cos[x]^5 + 1231 (I Sin[x])^10 Cos[x]^6 + 1231 (I Sin[x])^6 Cos[x]^10 + 2130 (I Sin[x])^8 Cos[x]^8 + 185 (I Sin[x])^4 Cos[x]^12 + 185 (I Sin[x])^12 Cos[x]^4 + 40 (I Sin[x])^3 Cos[x]^13 + 40 (I Sin[x])^13 Cos[x]^3 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2) + Exp[-1 I y] (2296 (I Sin[x])^8 Cos[x]^8 + 1586 (I Sin[x])^10 Cos[x]^6 + 1586 (I Sin[x])^6 Cos[x]^10 + 464 (I Sin[x])^4 Cos[x]^12 + 464 (I Sin[x])^12 Cos[x]^4 + 972 (I Sin[x])^5 Cos[x]^11 + 972 (I Sin[x])^11 Cos[x]^5 + 2066 (I Sin[x])^7 Cos[x]^9 + 2066 (I Sin[x])^9 Cos[x]^7 + 158 (I Sin[x])^13 Cos[x]^3 + 158 (I Sin[x])^3 Cos[x]^13 + 37 (I Sin[x])^2 Cos[x]^14 + 37 (I Sin[x])^14 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[1 I y] (1570 (I Sin[x])^6 Cos[x]^10 + 1570 (I Sin[x])^10 Cos[x]^6 + 2688 (I Sin[x])^8 Cos[x]^8 + 308 (I Sin[x])^4 Cos[x]^12 + 308 (I Sin[x])^12 Cos[x]^4 + 799 (I Sin[x])^11 Cos[x]^5 + 799 (I Sin[x])^5 Cos[x]^11 + 2321 (I Sin[x])^9 Cos[x]^7 + 2321 (I Sin[x])^7 Cos[x]^9 + 79 (I Sin[x])^3 Cos[x]^13 + 79 (I Sin[x])^13 Cos[x]^3 + 13 (I Sin[x])^14 Cos[x]^2 + 13 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[3 I y] (1622 (I Sin[x])^9 Cos[x]^7 + 1622 (I Sin[x])^7 Cos[x]^9 + 742 (I Sin[x])^11 Cos[x]^5 + 742 (I Sin[x])^5 Cos[x]^11 + 147 (I Sin[x])^3 Cos[x]^13 + 147 (I Sin[x])^13 Cos[x]^3 + 370 (I Sin[x])^4 Cos[x]^12 + 370 (I Sin[x])^12 Cos[x]^4 + 1195 (I Sin[x])^6 Cos[x]^10 + 1195 (I Sin[x])^10 Cos[x]^6 + 1754 (I Sin[x])^8 Cos[x]^8 + 42 (I Sin[x])^14 Cos[x]^2 + 42 (I Sin[x])^2 Cos[x]^14 + 9 (I Sin[x])^1 Cos[x]^15 + 9 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[5 I y] (416 (I Sin[x])^5 Cos[x]^11 + 416 (I Sin[x])^11 Cos[x]^5 + 1044 (I Sin[x])^9 Cos[x]^7 + 1044 (I Sin[x])^7 Cos[x]^9 + 169 (I Sin[x])^12 Cos[x]^4 + 169 (I Sin[x])^4 Cos[x]^12 + 741 (I Sin[x])^6 Cos[x]^10 + 741 (I Sin[x])^10 Cos[x]^6 + 1142 (I Sin[x])^8 Cos[x]^8 + 51 (I Sin[x])^13 Cos[x]^3 + 51 (I Sin[x])^3 Cos[x]^13 + 10 (I Sin[x])^2 Cos[x]^14 + 10 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^15 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^15) + Exp[7 I y] (338 (I Sin[x])^10 Cos[x]^6 + 338 (I Sin[x])^6 Cos[x]^10 + 516 (I Sin[x])^8 Cos[x]^8 + 88 (I Sin[x])^4 Cos[x]^12 + 88 (I Sin[x])^12 Cos[x]^4 + 189 (I Sin[x])^5 Cos[x]^11 + 189 (I Sin[x])^11 Cos[x]^5 + 450 (I Sin[x])^7 Cos[x]^9 + 450 (I Sin[x])^9 Cos[x]^7 + 9 (I Sin[x])^2 Cos[x]^14 + 9 (I Sin[x])^14 Cos[x]^2 + 32 (I Sin[x])^3 Cos[x]^13 + 32 (I Sin[x])^13 Cos[x]^3 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[9 I y] (112 (I Sin[x])^6 Cos[x]^10 + 112 (I Sin[x])^10 Cos[x]^6 + 28 (I Sin[x])^4 Cos[x]^12 + 28 (I Sin[x])^12 Cos[x]^4 + 180 (I Sin[x])^8 Cos[x]^8 + 61 (I Sin[x])^11 Cos[x]^5 + 61 (I Sin[x])^5 Cos[x]^11 + 155 (I Sin[x])^9 Cos[x]^7 + 155 (I Sin[x])^7 Cos[x]^9 + 8 (I Sin[x])^13 Cos[x]^3 + 8 (I Sin[x])^3 Cos[x]^13 + 1 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^2 Cos[x]^14) + Exp[11 I y] (36 (I Sin[x])^9 Cos[x]^7 + 36 (I Sin[x])^7 Cos[x]^9 + 18 (I Sin[x])^11 Cos[x]^5 + 18 (I Sin[x])^5 Cos[x]^11 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3 + 8 (I Sin[x])^4 Cos[x]^12 + 8 (I Sin[x])^12 Cos[x]^4 + 23 (I Sin[x])^6 Cos[x]^10 + 23 (I Sin[x])^10 Cos[x]^6 + 36 (I Sin[x])^8 Cos[x]^8) + Exp[13 I y] (4 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^7 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^7 + 1 (I Sin[x])^12 Cos[x]^4 + 1 (I Sin[x])^4 Cos[x]^12 + 5 (I Sin[x])^6 Cos[x]^10 + 5 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^8 Cos[x]^8) + Exp[15 I y] (1 (I Sin[x])^10 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^10));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":727.8,"max_line_length":5234,"alphanum_fraction":0.5042594119} {"size":394,"ext":"cdf","lang":"Mathematica","max_stars_count":null,"content":"\/* Quartus Prime Version 17.1.0 Build 590 10\/25\/2017 SJ Lite Edition *\/\nJedecChain;\n\tFileRevision(JESD32A);\n\tDefaultMfr(6E);\n\n\tP ActionCode(Cfg)\n\t\tDevice PartName(EP4CE15) Path(\"C:\/FPGA_source\/FPGA_MP801\/MP801_example_project\/mdyOsc_v1.1\/Oscill_main_top\/\") File(\"output_file11.jic\") MfrSpec(OpMask(1) SEC_Device(EPCS64) Child_OpMask(1 1));\n\nChainEnd;\n\nAlteraBegin;\n\tChainType(JTAG);\nAlteraEnd;\n","avg_line_length":28.1428571429,"max_line_length":194,"alphanum_fraction":0.7741116751} {"size":9135,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 15;\nname = \"15v1 2 2 1 2 2 1 3 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-14 I y] (1 (I Sin[x])^8 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^8) + Exp[-12 I y] (6 (I Sin[x])^9 Cos[x]^6 + 6 (I Sin[x])^6 Cos[x]^9 + 7 (I Sin[x])^8 Cos[x]^7 + 7 (I Sin[x])^7 Cos[x]^8 + 1 (I Sin[x])^5 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^5) + Exp[-10 I y] (44 (I Sin[x])^7 Cos[x]^8 + 44 (I Sin[x])^8 Cos[x]^7 + 32 (I Sin[x])^6 Cos[x]^9 + 32 (I Sin[x])^9 Cos[x]^6 + 13 (I Sin[x])^5 Cos[x]^10 + 13 (I Sin[x])^10 Cos[x]^5 + 2 (I Sin[x])^4 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^4) + Exp[-8 I y] (170 (I Sin[x])^8 Cos[x]^7 + 170 (I Sin[x])^7 Cos[x]^8 + 62 (I Sin[x])^5 Cos[x]^10 + 62 (I Sin[x])^10 Cos[x]^5 + 112 (I Sin[x])^6 Cos[x]^9 + 112 (I Sin[x])^9 Cos[x]^6 + 18 (I Sin[x])^4 Cos[x]^11 + 18 (I Sin[x])^11 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^3) + Exp[-6 I y] (316 (I Sin[x])^6 Cos[x]^9 + 316 (I Sin[x])^9 Cos[x]^6 + 449 (I Sin[x])^8 Cos[x]^7 + 449 (I Sin[x])^7 Cos[x]^8 + 161 (I Sin[x])^5 Cos[x]^10 + 161 (I Sin[x])^10 Cos[x]^5 + 61 (I Sin[x])^4 Cos[x]^11 + 61 (I Sin[x])^11 Cos[x]^4 + 13 (I Sin[x])^3 Cos[x]^12 + 13 (I Sin[x])^12 Cos[x]^3 + 1 (I Sin[x])^2 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^2) + Exp[-4 I y] (650 (I Sin[x])^9 Cos[x]^6 + 650 (I Sin[x])^6 Cos[x]^9 + 839 (I Sin[x])^7 Cos[x]^8 + 839 (I Sin[x])^8 Cos[x]^7 + 135 (I Sin[x])^4 Cos[x]^11 + 135 (I Sin[x])^11 Cos[x]^4 + 339 (I Sin[x])^5 Cos[x]^10 + 339 (I Sin[x])^10 Cos[x]^5 + 35 (I Sin[x])^3 Cos[x]^12 + 35 (I Sin[x])^12 Cos[x]^3 + 4 (I Sin[x])^2 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^2) + Exp[-2 I y] (592 (I Sin[x])^5 Cos[x]^10 + 592 (I Sin[x])^10 Cos[x]^5 + 1106 (I Sin[x])^7 Cos[x]^8 + 1106 (I Sin[x])^8 Cos[x]^7 + 912 (I Sin[x])^9 Cos[x]^6 + 912 (I Sin[x])^6 Cos[x]^9 + 275 (I Sin[x])^4 Cos[x]^11 + 275 (I Sin[x])^11 Cos[x]^4 + 95 (I Sin[x])^3 Cos[x]^12 + 95 (I Sin[x])^12 Cos[x]^3 + 21 (I Sin[x])^2 Cos[x]^13 + 21 (I Sin[x])^13 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^1) + Exp[0 I y] (1414 (I Sin[x])^8 Cos[x]^7 + 1414 (I Sin[x])^7 Cos[x]^8 + 618 (I Sin[x])^5 Cos[x]^10 + 618 (I Sin[x])^10 Cos[x]^5 + 1038 (I Sin[x])^6 Cos[x]^9 + 1038 (I Sin[x])^9 Cos[x]^6 + 261 (I Sin[x])^4 Cos[x]^11 + 261 (I Sin[x])^11 Cos[x]^4 + 81 (I Sin[x])^3 Cos[x]^12 + 81 (I Sin[x])^12 Cos[x]^3 + 18 (I Sin[x])^2 Cos[x]^13 + 18 (I Sin[x])^13 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^1) + Exp[2 I y] (848 (I Sin[x])^6 Cos[x]^9 + 848 (I Sin[x])^9 Cos[x]^6 + 1012 (I Sin[x])^8 Cos[x]^7 + 1012 (I Sin[x])^7 Cos[x]^8 + 587 (I Sin[x])^5 Cos[x]^10 + 587 (I Sin[x])^10 Cos[x]^5 + 348 (I Sin[x])^4 Cos[x]^11 + 348 (I Sin[x])^11 Cos[x]^4 + 150 (I Sin[x])^3 Cos[x]^12 + 150 (I Sin[x])^12 Cos[x]^3 + 47 (I Sin[x])^2 Cos[x]^13 + 47 (I Sin[x])^13 Cos[x]^2 + 10 (I Sin[x])^1 Cos[x]^14 + 10 (I Sin[x])^14 Cos[x]^1 + 1 Cos[x]^15 + 1 (I Sin[x])^15) + Exp[4 I y] (650 (I Sin[x])^9 Cos[x]^6 + 650 (I Sin[x])^6 Cos[x]^9 + 811 (I Sin[x])^7 Cos[x]^8 + 811 (I Sin[x])^8 Cos[x]^7 + 355 (I Sin[x])^5 Cos[x]^10 + 355 (I Sin[x])^10 Cos[x]^5 + 145 (I Sin[x])^4 Cos[x]^11 + 145 (I Sin[x])^11 Cos[x]^4 + 37 (I Sin[x])^3 Cos[x]^12 + 37 (I Sin[x])^12 Cos[x]^3 + 4 (I Sin[x])^13 Cos[x]^2 + 4 (I Sin[x])^2 Cos[x]^13) + Exp[6 I y] (203 (I Sin[x])^5 Cos[x]^10 + 203 (I Sin[x])^10 Cos[x]^5 + 358 (I Sin[x])^7 Cos[x]^8 + 358 (I Sin[x])^8 Cos[x]^7 + 293 (I Sin[x])^9 Cos[x]^6 + 293 (I Sin[x])^6 Cos[x]^9 + 97 (I Sin[x])^4 Cos[x]^11 + 97 (I Sin[x])^11 Cos[x]^4 + 39 (I Sin[x])^3 Cos[x]^12 + 39 (I Sin[x])^12 Cos[x]^3 + 10 (I Sin[x])^2 Cos[x]^13 + 10 (I Sin[x])^13 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^1) + Exp[8 I y] (54 (I Sin[x])^10 Cos[x]^5 + 54 (I Sin[x])^5 Cos[x]^10 + 184 (I Sin[x])^7 Cos[x]^8 + 184 (I Sin[x])^8 Cos[x]^7 + 112 (I Sin[x])^9 Cos[x]^6 + 112 (I Sin[x])^6 Cos[x]^9 + 13 (I Sin[x])^11 Cos[x]^4 + 13 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^12 Cos[x]^3 + 1 (I Sin[x])^3 Cos[x]^12) + Exp[10 I y] (30 (I Sin[x])^6 Cos[x]^9 + 30 (I Sin[x])^9 Cos[x]^6 + 10 (I Sin[x])^4 Cos[x]^11 + 10 (I Sin[x])^11 Cos[x]^4 + 33 (I Sin[x])^8 Cos[x]^7 + 33 (I Sin[x])^7 Cos[x]^8 + 16 (I Sin[x])^5 Cos[x]^10 + 16 (I Sin[x])^10 Cos[x]^5 + 2 (I Sin[x])^3 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^3) + Exp[12 I y] (6 (I Sin[x])^9 Cos[x]^6 + 6 (I Sin[x])^6 Cos[x]^9 + 7 (I Sin[x])^8 Cos[x]^7 + 7 (I Sin[x])^7 Cos[x]^8 + 1 (I Sin[x])^10 Cos[x]^5 + 1 (I Sin[x])^5 Cos[x]^10) + Exp[14 I y] (1 (I Sin[x])^5 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^5))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-14 I y] (1 (I Sin[x])^8 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^8) + Exp[-12 I y] (6 (I Sin[x])^9 Cos[x]^6 + 6 (I Sin[x])^6 Cos[x]^9 + 7 (I Sin[x])^8 Cos[x]^7 + 7 (I Sin[x])^7 Cos[x]^8 + 1 (I Sin[x])^5 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^5) + Exp[-10 I y] (44 (I Sin[x])^7 Cos[x]^8 + 44 (I Sin[x])^8 Cos[x]^7 + 32 (I Sin[x])^6 Cos[x]^9 + 32 (I Sin[x])^9 Cos[x]^6 + 13 (I Sin[x])^5 Cos[x]^10 + 13 (I Sin[x])^10 Cos[x]^5 + 2 (I Sin[x])^4 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^4) + Exp[-8 I y] (170 (I Sin[x])^8 Cos[x]^7 + 170 (I Sin[x])^7 Cos[x]^8 + 62 (I Sin[x])^5 Cos[x]^10 + 62 (I Sin[x])^10 Cos[x]^5 + 112 (I Sin[x])^6 Cos[x]^9 + 112 (I Sin[x])^9 Cos[x]^6 + 18 (I Sin[x])^4 Cos[x]^11 + 18 (I Sin[x])^11 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^3) + Exp[-6 I y] (316 (I Sin[x])^6 Cos[x]^9 + 316 (I Sin[x])^9 Cos[x]^6 + 449 (I Sin[x])^8 Cos[x]^7 + 449 (I Sin[x])^7 Cos[x]^8 + 161 (I Sin[x])^5 Cos[x]^10 + 161 (I Sin[x])^10 Cos[x]^5 + 61 (I Sin[x])^4 Cos[x]^11 + 61 (I Sin[x])^11 Cos[x]^4 + 13 (I Sin[x])^3 Cos[x]^12 + 13 (I Sin[x])^12 Cos[x]^3 + 1 (I Sin[x])^2 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^2) + Exp[-4 I y] (650 (I Sin[x])^9 Cos[x]^6 + 650 (I Sin[x])^6 Cos[x]^9 + 839 (I Sin[x])^7 Cos[x]^8 + 839 (I Sin[x])^8 Cos[x]^7 + 135 (I Sin[x])^4 Cos[x]^11 + 135 (I Sin[x])^11 Cos[x]^4 + 339 (I Sin[x])^5 Cos[x]^10 + 339 (I Sin[x])^10 Cos[x]^5 + 35 (I Sin[x])^3 Cos[x]^12 + 35 (I Sin[x])^12 Cos[x]^3 + 4 (I Sin[x])^2 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^2) + Exp[-2 I y] (592 (I Sin[x])^5 Cos[x]^10 + 592 (I Sin[x])^10 Cos[x]^5 + 1106 (I Sin[x])^7 Cos[x]^8 + 1106 (I Sin[x])^8 Cos[x]^7 + 912 (I Sin[x])^9 Cos[x]^6 + 912 (I Sin[x])^6 Cos[x]^9 + 275 (I Sin[x])^4 Cos[x]^11 + 275 (I Sin[x])^11 Cos[x]^4 + 95 (I Sin[x])^3 Cos[x]^12 + 95 (I Sin[x])^12 Cos[x]^3 + 21 (I Sin[x])^2 Cos[x]^13 + 21 (I Sin[x])^13 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^1) + Exp[0 I y] (1414 (I Sin[x])^8 Cos[x]^7 + 1414 (I Sin[x])^7 Cos[x]^8 + 618 (I Sin[x])^5 Cos[x]^10 + 618 (I Sin[x])^10 Cos[x]^5 + 1038 (I Sin[x])^6 Cos[x]^9 + 1038 (I Sin[x])^9 Cos[x]^6 + 261 (I Sin[x])^4 Cos[x]^11 + 261 (I Sin[x])^11 Cos[x]^4 + 81 (I Sin[x])^3 Cos[x]^12 + 81 (I Sin[x])^12 Cos[x]^3 + 18 (I Sin[x])^2 Cos[x]^13 + 18 (I Sin[x])^13 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^1) + Exp[2 I y] (848 (I Sin[x])^6 Cos[x]^9 + 848 (I Sin[x])^9 Cos[x]^6 + 1012 (I Sin[x])^8 Cos[x]^7 + 1012 (I Sin[x])^7 Cos[x]^8 + 587 (I Sin[x])^5 Cos[x]^10 + 587 (I Sin[x])^10 Cos[x]^5 + 348 (I Sin[x])^4 Cos[x]^11 + 348 (I Sin[x])^11 Cos[x]^4 + 150 (I Sin[x])^3 Cos[x]^12 + 150 (I Sin[x])^12 Cos[x]^3 + 47 (I Sin[x])^2 Cos[x]^13 + 47 (I Sin[x])^13 Cos[x]^2 + 10 (I Sin[x])^1 Cos[x]^14 + 10 (I Sin[x])^14 Cos[x]^1 + 1 Cos[x]^15 + 1 (I Sin[x])^15) + Exp[4 I y] (650 (I Sin[x])^9 Cos[x]^6 + 650 (I Sin[x])^6 Cos[x]^9 + 811 (I Sin[x])^7 Cos[x]^8 + 811 (I Sin[x])^8 Cos[x]^7 + 355 (I Sin[x])^5 Cos[x]^10 + 355 (I Sin[x])^10 Cos[x]^5 + 145 (I Sin[x])^4 Cos[x]^11 + 145 (I Sin[x])^11 Cos[x]^4 + 37 (I Sin[x])^3 Cos[x]^12 + 37 (I Sin[x])^12 Cos[x]^3 + 4 (I Sin[x])^13 Cos[x]^2 + 4 (I Sin[x])^2 Cos[x]^13) + Exp[6 I y] (203 (I Sin[x])^5 Cos[x]^10 + 203 (I Sin[x])^10 Cos[x]^5 + 358 (I Sin[x])^7 Cos[x]^8 + 358 (I Sin[x])^8 Cos[x]^7 + 293 (I Sin[x])^9 Cos[x]^6 + 293 (I Sin[x])^6 Cos[x]^9 + 97 (I Sin[x])^4 Cos[x]^11 + 97 (I Sin[x])^11 Cos[x]^4 + 39 (I Sin[x])^3 Cos[x]^12 + 39 (I Sin[x])^12 Cos[x]^3 + 10 (I Sin[x])^2 Cos[x]^13 + 10 (I Sin[x])^13 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^1) + Exp[8 I y] (54 (I Sin[x])^10 Cos[x]^5 + 54 (I Sin[x])^5 Cos[x]^10 + 184 (I Sin[x])^7 Cos[x]^8 + 184 (I Sin[x])^8 Cos[x]^7 + 112 (I Sin[x])^9 Cos[x]^6 + 112 (I Sin[x])^6 Cos[x]^9 + 13 (I Sin[x])^11 Cos[x]^4 + 13 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^12 Cos[x]^3 + 1 (I Sin[x])^3 Cos[x]^12) + Exp[10 I y] (30 (I Sin[x])^6 Cos[x]^9 + 30 (I Sin[x])^9 Cos[x]^6 + 10 (I Sin[x])^4 Cos[x]^11 + 10 (I Sin[x])^11 Cos[x]^4 + 33 (I Sin[x])^8 Cos[x]^7 + 33 (I Sin[x])^7 Cos[x]^8 + 16 (I Sin[x])^5 Cos[x]^10 + 16 (I Sin[x])^10 Cos[x]^5 + 2 (I Sin[x])^3 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^3) + Exp[12 I y] (6 (I Sin[x])^9 Cos[x]^6 + 6 (I Sin[x])^6 Cos[x]^9 + 7 (I Sin[x])^8 Cos[x]^7 + 7 (I Sin[x])^7 Cos[x]^8 + 1 (I Sin[x])^10 Cos[x]^5 + 1 (I Sin[x])^5 Cos[x]^10) + Exp[14 I y] (1 (I Sin[x])^5 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^5));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":609.0,"max_line_length":4344,"alphanum_fraction":0.5013683634} {"size":4503,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 10;\nname = \"10v2 1 1 4 1 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-9 I y] (1 (I Sin[x])^6 Cos[x]^4 + 1 (I Sin[x])^4 Cos[x]^6) + Exp[-8 I y] (4 (I Sin[x])^5 Cos[x]^5 + 3 (I Sin[x])^3 Cos[x]^7 + 3 (I Sin[x])^7 Cos[x]^3 + 2 (I Sin[x])^6 Cos[x]^4 + 2 (I Sin[x])^4 Cos[x]^6 + 2 (I Sin[x])^2 Cos[x]^8 + 2 (I Sin[x])^8 Cos[x]^2) + Exp[-7 I y] (11 (I Sin[x])^7 Cos[x]^3 + 11 (I Sin[x])^3 Cos[x]^7 + 18 (I Sin[x])^5 Cos[x]^5 + 14 (I Sin[x])^6 Cos[x]^4 + 14 (I Sin[x])^4 Cos[x]^6 + 2 (I Sin[x])^2 Cos[x]^8 + 2 (I Sin[x])^8 Cos[x]^2) + Exp[-6 I y] (37 (I Sin[x])^4 Cos[x]^6 + 37 (I Sin[x])^6 Cos[x]^4 + 7 (I Sin[x])^2 Cos[x]^8 + 7 (I Sin[x])^8 Cos[x]^2 + 36 (I Sin[x])^5 Cos[x]^5 + 3 (I Sin[x])^1 Cos[x]^9 + 3 (I Sin[x])^9 Cos[x]^1 + 19 (I Sin[x])^3 Cos[x]^7 + 19 (I Sin[x])^7 Cos[x]^3) + Exp[-5 I y] (58 (I Sin[x])^6 Cos[x]^4 + 58 (I Sin[x])^4 Cos[x]^6 + 8 (I Sin[x])^8 Cos[x]^2 + 8 (I Sin[x])^2 Cos[x]^8 + 76 (I Sin[x])^5 Cos[x]^5 + 21 (I Sin[x])^7 Cos[x]^3 + 21 (I Sin[x])^3 Cos[x]^7 + 1 (I Sin[x])^1 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^1) + Exp[-4 I y] (33 (I Sin[x])^3 Cos[x]^7 + 33 (I Sin[x])^7 Cos[x]^3 + 60 (I Sin[x])^5 Cos[x]^5 + 44 (I Sin[x])^4 Cos[x]^6 + 44 (I Sin[x])^6 Cos[x]^4 + 15 (I Sin[x])^2 Cos[x]^8 + 15 (I Sin[x])^8 Cos[x]^2 + 3 (I Sin[x])^1 Cos[x]^9 + 3 (I Sin[x])^9 Cos[x]^1 + 1 Cos[x]^10 + 1 (I Sin[x])^10) + Exp[-3 I y] (44 (I Sin[x])^5 Cos[x]^5 + 21 (I Sin[x])^7 Cos[x]^3 + 21 (I Sin[x])^3 Cos[x]^7 + 36 (I Sin[x])^6 Cos[x]^4 + 36 (I Sin[x])^4 Cos[x]^6 + 4 (I Sin[x])^2 Cos[x]^8 + 4 (I Sin[x])^8 Cos[x]^2 + 1 (I Sin[x])^9 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^9) + Exp[-2 I y] (15 (I Sin[x])^4 Cos[x]^6 + 15 (I Sin[x])^6 Cos[x]^4 + 5 (I Sin[x])^2 Cos[x]^8 + 5 (I Sin[x])^8 Cos[x]^2 + 9 (I Sin[x])^3 Cos[x]^7 + 9 (I Sin[x])^7 Cos[x]^3 + 2 (I Sin[x])^1 Cos[x]^9 + 2 (I Sin[x])^9 Cos[x]^1 + 10 (I Sin[x])^5 Cos[x]^5) + Exp[-1 I y] (3 (I Sin[x])^4 Cos[x]^6 + 3 (I Sin[x])^6 Cos[x]^4 + 2 (I Sin[x])^8 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^8 + 3 (I Sin[x])^7 Cos[x]^3 + 3 (I Sin[x])^3 Cos[x]^7 + 2 (I Sin[x])^5 Cos[x]^5) + Exp[0 I y] (2 (I Sin[x])^5 Cos[x]^5))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-9 I y] (1 (I Sin[x])^6 Cos[x]^4 + 1 (I Sin[x])^4 Cos[x]^6) + Exp[-8 I y] (4 (I Sin[x])^5 Cos[x]^5 + 3 (I Sin[x])^3 Cos[x]^7 + 3 (I Sin[x])^7 Cos[x]^3 + 2 (I Sin[x])^6 Cos[x]^4 + 2 (I Sin[x])^4 Cos[x]^6 + 2 (I Sin[x])^2 Cos[x]^8 + 2 (I Sin[x])^8 Cos[x]^2) + Exp[-7 I y] (11 (I Sin[x])^7 Cos[x]^3 + 11 (I Sin[x])^3 Cos[x]^7 + 18 (I Sin[x])^5 Cos[x]^5 + 14 (I Sin[x])^6 Cos[x]^4 + 14 (I Sin[x])^4 Cos[x]^6 + 2 (I Sin[x])^2 Cos[x]^8 + 2 (I Sin[x])^8 Cos[x]^2) + Exp[-6 I y] (37 (I Sin[x])^4 Cos[x]^6 + 37 (I Sin[x])^6 Cos[x]^4 + 7 (I Sin[x])^2 Cos[x]^8 + 7 (I Sin[x])^8 Cos[x]^2 + 36 (I Sin[x])^5 Cos[x]^5 + 3 (I Sin[x])^1 Cos[x]^9 + 3 (I Sin[x])^9 Cos[x]^1 + 19 (I Sin[x])^3 Cos[x]^7 + 19 (I Sin[x])^7 Cos[x]^3) + Exp[-5 I y] (58 (I Sin[x])^6 Cos[x]^4 + 58 (I Sin[x])^4 Cos[x]^6 + 8 (I Sin[x])^8 Cos[x]^2 + 8 (I Sin[x])^2 Cos[x]^8 + 76 (I Sin[x])^5 Cos[x]^5 + 21 (I Sin[x])^7 Cos[x]^3 + 21 (I Sin[x])^3 Cos[x]^7 + 1 (I Sin[x])^1 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^1) + Exp[-4 I y] (33 (I Sin[x])^3 Cos[x]^7 + 33 (I Sin[x])^7 Cos[x]^3 + 60 (I Sin[x])^5 Cos[x]^5 + 44 (I Sin[x])^4 Cos[x]^6 + 44 (I Sin[x])^6 Cos[x]^4 + 15 (I Sin[x])^2 Cos[x]^8 + 15 (I Sin[x])^8 Cos[x]^2 + 3 (I Sin[x])^1 Cos[x]^9 + 3 (I Sin[x])^9 Cos[x]^1 + 1 Cos[x]^10 + 1 (I Sin[x])^10) + Exp[-3 I y] (44 (I Sin[x])^5 Cos[x]^5 + 21 (I Sin[x])^7 Cos[x]^3 + 21 (I Sin[x])^3 Cos[x]^7 + 36 (I Sin[x])^6 Cos[x]^4 + 36 (I Sin[x])^4 Cos[x]^6 + 4 (I Sin[x])^2 Cos[x]^8 + 4 (I Sin[x])^8 Cos[x]^2 + 1 (I Sin[x])^9 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^9) + Exp[-2 I y] (15 (I Sin[x])^4 Cos[x]^6 + 15 (I Sin[x])^6 Cos[x]^4 + 5 (I Sin[x])^2 Cos[x]^8 + 5 (I Sin[x])^8 Cos[x]^2 + 9 (I Sin[x])^3 Cos[x]^7 + 9 (I Sin[x])^7 Cos[x]^3 + 2 (I Sin[x])^1 Cos[x]^9 + 2 (I Sin[x])^9 Cos[x]^1 + 10 (I Sin[x])^5 Cos[x]^5) + Exp[-1 I y] (3 (I Sin[x])^4 Cos[x]^6 + 3 (I Sin[x])^6 Cos[x]^4 + 2 (I Sin[x])^8 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^8 + 3 (I Sin[x])^7 Cos[x]^3 + 3 (I Sin[x])^3 Cos[x]^7 + 2 (I Sin[x])^5 Cos[x]^5) + Exp[0 I y] (2 (I Sin[x])^5 Cos[x]^5));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":300.2,"max_line_length":2031,"alphanum_fraction":0.4825671774} {"size":20349,"ext":"wlt","lang":"Mathematica","max_stars_count":null,"content":"%YAML 1.1\r\n%TAG !u! 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True}}}},ExpressionUUID->\"21895f5f-4181-4ef3-b603-3ab667df5cb0\"]\n}, Open ]],\n\nCell[CellGroupData[{\n\nCell[\" \", \"FooterCell\",ExpressionUUID->\"56615957-4f32-439d-b6b0-bfb37609d941\"],\n\nCell[BoxData[\"\"],ExpressionUUID->\"f12ec33d-3cf6-4649-a233-0920a0601d6f\"]\n}, Open ]]\n},\nSaveable->False,\nScreenStyleEnvironment->\"Working\",\nWindowSize->{725, 750},\nWindowMargins->{{0, Automatic}, {Automatic, 0}},\nWindowTitle->\"HrrAmplitude\",\nVisible->True,\nPrivateNotebookOptions->{\"FileOutlineCache\"->False},\nTaggingRules->{\n \"ModificationHighlight\" -> False, \n \"Metadata\" -> {\n \"context\" -> \"BlackHoleAnalysis`\", \n \"keywords\" -> {\"HrrAmplitude\", \"HRRAMPLITUDE\", \"hrramplitude\"}, \"index\" -> \n True, \"label\" -> \"BlackHoleAnalysis\/BlackHoleAnalysis`Fields Symbol\", \n \"language\" -> \"en\", \"paclet\" -> \"BlackHoleAnalysis`Fields\", \"status\" -> \n \"None\", \"summary\" -> \n \"HrrAmplitude[] returns the metric perturbation amplitude h_rr in \\\nsymbolic form.\", \n \"synonyms\" -> {\"HrrAmplitude\", \"HRRAMPLITUDE\", \"hrramplitude\"}, \"title\" -> \n \"HrrAmplitude\", \"windowTitle\" -> \"HrrAmplitude\", \"type\" -> \"Symbol\", \n \"uri\" -> \"BlackHoleAnalysis\/ref\/HrrAmplitude\", \"WorkflowDockedCell\" -> \n \"\"}, \"SearchTextTranslated\" -> \"\", \"LinkTrails\" -> \"\", \"NewStyles\" -> \n False},\nTrackCellChangeTimes->False,\nFrontEndVersion->\"11.3 for Mac OS X x86 (32-bit, 64-bit Kernel) (March 5, \\\n2018)\",\nStyleDefinitions->FrontEnd`FileName[{\"Wolfram\"}, \"Reference.nb\", \n CharacterEncoding -> \"UTF-8\"]\n]\n\n","avg_line_length":42.4919786096,"max_line_length":81,"alphanum_fraction":0.6594512962} {"size":9151,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 15;\nname = \"15v1 1 2 1 2 3 1 1 1 1 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-14 I y] (1 (I Sin[x])^7 Cos[x]^8 + 1 (I Sin[x])^8 Cos[x]^7) + Exp[-12 I y] (10 (I Sin[x])^8 Cos[x]^7 + 10 (I Sin[x])^7 Cos[x]^8 + 3 (I Sin[x])^6 Cos[x]^9 + 3 (I Sin[x])^9 Cos[x]^6 + 1 (I Sin[x])^5 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^5) + Exp[-10 I y] (33 (I Sin[x])^6 Cos[x]^9 + 33 (I Sin[x])^9 Cos[x]^6 + 42 (I Sin[x])^8 Cos[x]^7 + 42 (I Sin[x])^7 Cos[x]^8 + 13 (I Sin[x])^5 Cos[x]^10 + 13 (I Sin[x])^10 Cos[x]^5 + 3 (I Sin[x])^4 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^4) + Exp[-8 I y] (129 (I Sin[x])^9 Cos[x]^6 + 129 (I Sin[x])^6 Cos[x]^9 + 182 (I Sin[x])^7 Cos[x]^8 + 182 (I Sin[x])^8 Cos[x]^7 + 45 (I Sin[x])^5 Cos[x]^10 + 45 (I Sin[x])^10 Cos[x]^5 + 8 (I Sin[x])^4 Cos[x]^11 + 8 (I Sin[x])^11 Cos[x]^4) + Exp[-6 I y] (170 (I Sin[x])^5 Cos[x]^10 + 170 (I Sin[x])^10 Cos[x]^5 + 450 (I Sin[x])^7 Cos[x]^8 + 450 (I Sin[x])^8 Cos[x]^7 + 316 (I Sin[x])^9 Cos[x]^6 + 316 (I Sin[x])^6 Cos[x]^9 + 55 (I Sin[x])^4 Cos[x]^11 + 55 (I Sin[x])^11 Cos[x]^4 + 10 (I Sin[x])^3 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^3) + Exp[-4 I y] (327 (I Sin[x])^10 Cos[x]^5 + 327 (I Sin[x])^5 Cos[x]^10 + 925 (I Sin[x])^7 Cos[x]^8 + 925 (I Sin[x])^8 Cos[x]^7 + 635 (I Sin[x])^6 Cos[x]^9 + 635 (I Sin[x])^9 Cos[x]^6 + 100 (I Sin[x])^4 Cos[x]^11 + 100 (I Sin[x])^11 Cos[x]^4 + 15 (I Sin[x])^3 Cos[x]^12 + 15 (I Sin[x])^12 Cos[x]^3) + Exp[-2 I y] (253 (I Sin[x])^4 Cos[x]^11 + 253 (I Sin[x])^11 Cos[x]^4 + 1176 (I Sin[x])^8 Cos[x]^7 + 1176 (I Sin[x])^7 Cos[x]^8 + 938 (I Sin[x])^6 Cos[x]^9 + 938 (I Sin[x])^9 Cos[x]^6 + 550 (I Sin[x])^5 Cos[x]^10 + 550 (I Sin[x])^10 Cos[x]^5 + 74 (I Sin[x])^3 Cos[x]^12 + 74 (I Sin[x])^12 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^13 + 12 (I Sin[x])^13 Cos[x]^2) + Exp[0 I y] (1090 (I Sin[x])^9 Cos[x]^6 + 1090 (I Sin[x])^6 Cos[x]^9 + 1406 (I Sin[x])^8 Cos[x]^7 + 1406 (I Sin[x])^7 Cos[x]^8 + 600 (I Sin[x])^5 Cos[x]^10 + 600 (I Sin[x])^10 Cos[x]^5 + 255 (I Sin[x])^4 Cos[x]^11 + 255 (I Sin[x])^11 Cos[x]^4 + 71 (I Sin[x])^12 Cos[x]^3 + 71 (I Sin[x])^3 Cos[x]^12 + 10 (I Sin[x])^2 Cos[x]^13 + 10 (I Sin[x])^13 Cos[x]^2) + Exp[2 I y] (136 (I Sin[x])^3 Cos[x]^12 + 136 (I Sin[x])^12 Cos[x]^3 + 1029 (I Sin[x])^7 Cos[x]^8 + 1029 (I Sin[x])^8 Cos[x]^7 + 614 (I Sin[x])^5 Cos[x]^10 + 614 (I Sin[x])^10 Cos[x]^5 + 858 (I Sin[x])^9 Cos[x]^6 + 858 (I Sin[x])^6 Cos[x]^9 + 322 (I Sin[x])^4 Cos[x]^11 + 322 (I Sin[x])^11 Cos[x]^4 + 38 (I Sin[x])^2 Cos[x]^13 + 38 (I Sin[x])^13 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^14 + 6 (I Sin[x])^14 Cos[x]^1) + Exp[4 I y] (389 (I Sin[x])^10 Cos[x]^5 + 389 (I Sin[x])^5 Cos[x]^10 + 766 (I Sin[x])^7 Cos[x]^8 + 766 (I Sin[x])^8 Cos[x]^7 + 603 (I Sin[x])^9 Cos[x]^6 + 603 (I Sin[x])^6 Cos[x]^9 + 171 (I Sin[x])^11 Cos[x]^4 + 171 (I Sin[x])^4 Cos[x]^11 + 57 (I Sin[x])^3 Cos[x]^12 + 57 (I Sin[x])^12 Cos[x]^3 + 14 (I Sin[x])^13 Cos[x]^2 + 14 (I Sin[x])^2 Cos[x]^13 + 2 (I Sin[x])^1 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^1) + Exp[6 I y] (146 (I Sin[x])^4 Cos[x]^11 + 146 (I Sin[x])^11 Cos[x]^4 + 267 (I Sin[x])^6 Cos[x]^9 + 267 (I Sin[x])^9 Cos[x]^6 + 24 (I Sin[x])^2 Cos[x]^13 + 24 (I Sin[x])^13 Cos[x]^2 + 285 (I Sin[x])^8 Cos[x]^7 + 285 (I Sin[x])^7 Cos[x]^8 + 205 (I Sin[x])^5 Cos[x]^10 + 205 (I Sin[x])^10 Cos[x]^5 + 67 (I Sin[x])^3 Cos[x]^12 + 67 (I Sin[x])^12 Cos[x]^3 + 6 (I Sin[x])^1 Cos[x]^14 + 6 (I Sin[x])^14 Cos[x]^1 + 1 Cos[x]^15 + 1 (I Sin[x])^15) + Exp[8 I y] (109 (I Sin[x])^9 Cos[x]^6 + 109 (I Sin[x])^6 Cos[x]^9 + 37 (I Sin[x])^11 Cos[x]^4 + 37 (I Sin[x])^4 Cos[x]^11 + 140 (I Sin[x])^8 Cos[x]^7 + 140 (I Sin[x])^7 Cos[x]^8 + 63 (I Sin[x])^10 Cos[x]^5 + 63 (I Sin[x])^5 Cos[x]^10 + 13 (I Sin[x])^12 Cos[x]^3 + 13 (I Sin[x])^3 Cos[x]^12 + 2 (I Sin[x])^2 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^2) + Exp[10 I y] (21 (I Sin[x])^5 Cos[x]^10 + 21 (I Sin[x])^10 Cos[x]^5 + 20 (I Sin[x])^7 Cos[x]^8 + 20 (I Sin[x])^8 Cos[x]^7 + 12 (I Sin[x])^3 Cos[x]^12 + 12 (I Sin[x])^12 Cos[x]^3 + 19 (I Sin[x])^9 Cos[x]^6 + 19 (I Sin[x])^6 Cos[x]^9 + 13 (I Sin[x])^4 Cos[x]^11 + 13 (I Sin[x])^11 Cos[x]^4 + 1 (I Sin[x])^1 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^1 + 5 (I Sin[x])^2 Cos[x]^13 + 5 (I Sin[x])^13 Cos[x]^2) + Exp[12 I y] (5 (I Sin[x])^10 Cos[x]^5 + 5 (I Sin[x])^5 Cos[x]^10 + 3 (I Sin[x])^8 Cos[x]^7 + 3 (I Sin[x])^7 Cos[x]^8 + 5 (I Sin[x])^9 Cos[x]^6 + 5 (I Sin[x])^6 Cos[x]^9 + 1 (I Sin[x])^11 Cos[x]^4 + 1 (I Sin[x])^4 Cos[x]^11) + Exp[14 I y] (1 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^4))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-14 I y] (1 (I Sin[x])^7 Cos[x]^8 + 1 (I Sin[x])^8 Cos[x]^7) + Exp[-12 I y] (10 (I Sin[x])^8 Cos[x]^7 + 10 (I Sin[x])^7 Cos[x]^8 + 3 (I Sin[x])^6 Cos[x]^9 + 3 (I Sin[x])^9 Cos[x]^6 + 1 (I Sin[x])^5 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^5) + Exp[-10 I y] (33 (I Sin[x])^6 Cos[x]^9 + 33 (I Sin[x])^9 Cos[x]^6 + 42 (I Sin[x])^8 Cos[x]^7 + 42 (I Sin[x])^7 Cos[x]^8 + 13 (I Sin[x])^5 Cos[x]^10 + 13 (I Sin[x])^10 Cos[x]^5 + 3 (I Sin[x])^4 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^4) + Exp[-8 I y] (129 (I Sin[x])^9 Cos[x]^6 + 129 (I Sin[x])^6 Cos[x]^9 + 182 (I Sin[x])^7 Cos[x]^8 + 182 (I Sin[x])^8 Cos[x]^7 + 45 (I Sin[x])^5 Cos[x]^10 + 45 (I Sin[x])^10 Cos[x]^5 + 8 (I Sin[x])^4 Cos[x]^11 + 8 (I Sin[x])^11 Cos[x]^4) + Exp[-6 I y] (170 (I Sin[x])^5 Cos[x]^10 + 170 (I Sin[x])^10 Cos[x]^5 + 450 (I Sin[x])^7 Cos[x]^8 + 450 (I Sin[x])^8 Cos[x]^7 + 316 (I Sin[x])^9 Cos[x]^6 + 316 (I Sin[x])^6 Cos[x]^9 + 55 (I Sin[x])^4 Cos[x]^11 + 55 (I Sin[x])^11 Cos[x]^4 + 10 (I Sin[x])^3 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^3) + Exp[-4 I y] (327 (I Sin[x])^10 Cos[x]^5 + 327 (I Sin[x])^5 Cos[x]^10 + 925 (I Sin[x])^7 Cos[x]^8 + 925 (I Sin[x])^8 Cos[x]^7 + 635 (I Sin[x])^6 Cos[x]^9 + 635 (I Sin[x])^9 Cos[x]^6 + 100 (I Sin[x])^4 Cos[x]^11 + 100 (I Sin[x])^11 Cos[x]^4 + 15 (I Sin[x])^3 Cos[x]^12 + 15 (I Sin[x])^12 Cos[x]^3) + Exp[-2 I y] (253 (I Sin[x])^4 Cos[x]^11 + 253 (I Sin[x])^11 Cos[x]^4 + 1176 (I Sin[x])^8 Cos[x]^7 + 1176 (I Sin[x])^7 Cos[x]^8 + 938 (I Sin[x])^6 Cos[x]^9 + 938 (I Sin[x])^9 Cos[x]^6 + 550 (I Sin[x])^5 Cos[x]^10 + 550 (I Sin[x])^10 Cos[x]^5 + 74 (I Sin[x])^3 Cos[x]^12 + 74 (I Sin[x])^12 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^13 + 12 (I Sin[x])^13 Cos[x]^2) + Exp[0 I y] (1090 (I Sin[x])^9 Cos[x]^6 + 1090 (I Sin[x])^6 Cos[x]^9 + 1406 (I Sin[x])^8 Cos[x]^7 + 1406 (I Sin[x])^7 Cos[x]^8 + 600 (I Sin[x])^5 Cos[x]^10 + 600 (I Sin[x])^10 Cos[x]^5 + 255 (I Sin[x])^4 Cos[x]^11 + 255 (I Sin[x])^11 Cos[x]^4 + 71 (I Sin[x])^12 Cos[x]^3 + 71 (I Sin[x])^3 Cos[x]^12 + 10 (I Sin[x])^2 Cos[x]^13 + 10 (I Sin[x])^13 Cos[x]^2) + Exp[2 I y] (136 (I Sin[x])^3 Cos[x]^12 + 136 (I Sin[x])^12 Cos[x]^3 + 1029 (I Sin[x])^7 Cos[x]^8 + 1029 (I Sin[x])^8 Cos[x]^7 + 614 (I Sin[x])^5 Cos[x]^10 + 614 (I Sin[x])^10 Cos[x]^5 + 858 (I Sin[x])^9 Cos[x]^6 + 858 (I Sin[x])^6 Cos[x]^9 + 322 (I Sin[x])^4 Cos[x]^11 + 322 (I Sin[x])^11 Cos[x]^4 + 38 (I Sin[x])^2 Cos[x]^13 + 38 (I Sin[x])^13 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^14 + 6 (I Sin[x])^14 Cos[x]^1) + Exp[4 I y] (389 (I Sin[x])^10 Cos[x]^5 + 389 (I Sin[x])^5 Cos[x]^10 + 766 (I Sin[x])^7 Cos[x]^8 + 766 (I Sin[x])^8 Cos[x]^7 + 603 (I Sin[x])^9 Cos[x]^6 + 603 (I Sin[x])^6 Cos[x]^9 + 171 (I Sin[x])^11 Cos[x]^4 + 171 (I Sin[x])^4 Cos[x]^11 + 57 (I Sin[x])^3 Cos[x]^12 + 57 (I Sin[x])^12 Cos[x]^3 + 14 (I Sin[x])^13 Cos[x]^2 + 14 (I Sin[x])^2 Cos[x]^13 + 2 (I Sin[x])^1 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^1) + Exp[6 I y] (146 (I Sin[x])^4 Cos[x]^11 + 146 (I Sin[x])^11 Cos[x]^4 + 267 (I Sin[x])^6 Cos[x]^9 + 267 (I Sin[x])^9 Cos[x]^6 + 24 (I Sin[x])^2 Cos[x]^13 + 24 (I Sin[x])^13 Cos[x]^2 + 285 (I Sin[x])^8 Cos[x]^7 + 285 (I Sin[x])^7 Cos[x]^8 + 205 (I Sin[x])^5 Cos[x]^10 + 205 (I Sin[x])^10 Cos[x]^5 + 67 (I Sin[x])^3 Cos[x]^12 + 67 (I Sin[x])^12 Cos[x]^3 + 6 (I Sin[x])^1 Cos[x]^14 + 6 (I Sin[x])^14 Cos[x]^1 + 1 Cos[x]^15 + 1 (I Sin[x])^15) + Exp[8 I y] (109 (I Sin[x])^9 Cos[x]^6 + 109 (I Sin[x])^6 Cos[x]^9 + 37 (I Sin[x])^11 Cos[x]^4 + 37 (I Sin[x])^4 Cos[x]^11 + 140 (I Sin[x])^8 Cos[x]^7 + 140 (I Sin[x])^7 Cos[x]^8 + 63 (I Sin[x])^10 Cos[x]^5 + 63 (I Sin[x])^5 Cos[x]^10 + 13 (I Sin[x])^12 Cos[x]^3 + 13 (I Sin[x])^3 Cos[x]^12 + 2 (I Sin[x])^2 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^2) + Exp[10 I y] (21 (I Sin[x])^5 Cos[x]^10 + 21 (I Sin[x])^10 Cos[x]^5 + 20 (I Sin[x])^7 Cos[x]^8 + 20 (I Sin[x])^8 Cos[x]^7 + 12 (I Sin[x])^3 Cos[x]^12 + 12 (I Sin[x])^12 Cos[x]^3 + 19 (I Sin[x])^9 Cos[x]^6 + 19 (I Sin[x])^6 Cos[x]^9 + 13 (I Sin[x])^4 Cos[x]^11 + 13 (I Sin[x])^11 Cos[x]^4 + 1 (I Sin[x])^1 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^1 + 5 (I Sin[x])^2 Cos[x]^13 + 5 (I Sin[x])^13 Cos[x]^2) + Exp[12 I y] (5 (I Sin[x])^10 Cos[x]^5 + 5 (I Sin[x])^5 Cos[x]^10 + 3 (I Sin[x])^8 Cos[x]^7 + 3 (I Sin[x])^7 Cos[x]^8 + 5 (I Sin[x])^9 Cos[x]^6 + 5 (I Sin[x])^6 Cos[x]^9 + 1 (I Sin[x])^11 Cos[x]^4 + 1 (I Sin[x])^4 Cos[x]^11) + Exp[14 I y] (1 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^4));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":610.0666666667,"max_line_length":4350,"alphanum_fraction":0.502021637} {"size":8177,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 14;\nname = \"14v2 3 1 1 2 2 1 1 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-13 I y] (2 (I Sin[x])^7 Cos[x]^7) + Exp[-11 I y] (7 (I Sin[x])^8 Cos[x]^6 + 7 (I Sin[x])^6 Cos[x]^8 + 10 (I Sin[x])^7 Cos[x]^7 + 1 (I Sin[x])^5 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^5) + Exp[-9 I y] (38 (I Sin[x])^6 Cos[x]^8 + 38 (I Sin[x])^8 Cos[x]^6 + 38 (I Sin[x])^7 Cos[x]^7 + 17 (I Sin[x])^5 Cos[x]^9 + 17 (I Sin[x])^9 Cos[x]^5 + 4 (I Sin[x])^4 Cos[x]^10 + 4 (I Sin[x])^10 Cos[x]^4) + Exp[-7 I y] (71 (I Sin[x])^9 Cos[x]^5 + 71 (I Sin[x])^5 Cos[x]^9 + 146 (I Sin[x])^7 Cos[x]^7 + 121 (I Sin[x])^6 Cos[x]^8 + 121 (I Sin[x])^8 Cos[x]^6 + 19 (I Sin[x])^4 Cos[x]^10 + 19 (I Sin[x])^10 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^3) + Exp[-5 I y] (187 (I Sin[x])^5 Cos[x]^9 + 187 (I Sin[x])^9 Cos[x]^5 + 292 (I Sin[x])^7 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\"ExampleSection\",\n CellID->2123667759],\nCell[5284, 249, 135, 3, 21, \"ExampleSection\",\n CellID->1305812373],\nCell[5422, 254, 140, 3, 21, \"ExampleSection\",\n CellID->1653164318],\nCell[5565, 259, 132, 3, 21, \"ExampleSection\",\n CellID->589267740]\n}, Open ]]\n}\n]\n*)\n\n(* End of internal cache information *)\n\n","avg_line_length":23.7177033493,"max_line_length":77,"alphanum_fraction":0.6832761751} {"size":7147,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 13;\nname = \"13v3 2 1 4 2 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-12 I y] (1 (I Sin[x])^7 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^7) + Exp[-10 I y] (4 (I Sin[x])^6 Cos[x]^7 + 4 (I Sin[x])^7 Cos[x]^6 + 4 (I Sin[x])^5 Cos[x]^8 + 4 (I Sin[x])^8 Cos[x]^5 + 3 (I Sin[x])^4 Cos[x]^9 + 3 (I Sin[x])^9 Cos[x]^4 + 1 (I Sin[x])^3 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^3) + Exp[-8 I y] (23 (I Sin[x])^8 Cos[x]^5 + 23 (I Sin[x])^5 Cos[x]^8 + 13 (I Sin[x])^9 Cos[x]^4 + 13 (I Sin[x])^4 Cos[x]^9 + 24 (I Sin[x])^6 Cos[x]^7 + 24 (I Sin[x])^7 Cos[x]^6 + 5 (I Sin[x])^3 Cos[x]^10 + 5 (I Sin[x])^10 Cos[x]^3 + 1 (I Sin[x])^2 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^2) + Exp[-6 I y] (89 (I Sin[x])^7 Cos[x]^6 + 89 (I Sin[x])^6 Cos[x]^7 + 38 (I Sin[x])^4 Cos[x]^9 + 38 (I Sin[x])^9 Cos[x]^4 + 66 (I Sin[x])^5 Cos[x]^8 + 66 (I Sin[x])^8 Cos[x]^5 + 19 (I Sin[x])^3 Cos[x]^10 + 19 (I Sin[x])^10 Cos[x]^3 + 7 (I Sin[x])^2 Cos[x]^11 + 7 (I Sin[x])^11 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^1) + Exp[-4 I y] (217 (I Sin[x])^7 Cos[x]^6 + 217 (I Sin[x])^6 Cos[x]^7 + 154 (I Sin[x])^8 Cos[x]^5 + 154 (I Sin[x])^5 Cos[x]^8 + 85 (I Sin[x])^9 Cos[x]^4 + 85 (I Sin[x])^4 Cos[x]^9 + 31 (I Sin[x])^10 Cos[x]^3 + 31 (I Sin[x])^3 Cos[x]^10 + 7 (I Sin[x])^2 Cos[x]^11 + 7 (I Sin[x])^11 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^1) + Exp[-2 I y] (284 (I Sin[x])^6 Cos[x]^7 + 284 (I Sin[x])^7 Cos[x]^6 + 239 (I Sin[x])^5 Cos[x]^8 + 239 (I Sin[x])^8 Cos[x]^5 + 76 (I Sin[x])^3 Cos[x]^10 + 76 (I Sin[x])^10 Cos[x]^3 + 159 (I Sin[x])^4 Cos[x]^9 + 159 (I Sin[x])^9 Cos[x]^4 + 26 (I Sin[x])^2 Cos[x]^11 + 26 (I Sin[x])^11 Cos[x]^2 + 7 (I Sin[x])^1 Cos[x]^12 + 7 (I Sin[x])^12 Cos[x]^1 + 1 Cos[x]^13 + 1 (I Sin[x])^13) + Exp[0 I y] (412 (I Sin[x])^6 Cos[x]^7 + 412 (I Sin[x])^7 Cos[x]^6 + 300 (I Sin[x])^8 Cos[x]^5 + 300 (I Sin[x])^5 Cos[x]^8 + 147 (I Sin[x])^9 Cos[x]^4 + 147 (I Sin[x])^4 Cos[x]^9 + 52 (I Sin[x])^3 Cos[x]^10 + 52 (I Sin[x])^10 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^11 + 12 (I Sin[x])^11 Cos[x]^2 + 1 (I Sin[x])^12 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^12) + Exp[2 I y] (242 (I Sin[x])^5 Cos[x]^8 + 242 (I Sin[x])^8 Cos[x]^5 + 320 (I Sin[x])^6 Cos[x]^7 + 320 (I Sin[x])^7 Cos[x]^6 + 141 (I Sin[x])^4 Cos[x]^9 + 141 (I Sin[x])^9 Cos[x]^4 + 65 (I Sin[x])^3 Cos[x]^10 + 65 (I Sin[x])^10 Cos[x]^3 + 21 (I Sin[x])^2 Cos[x]^11 + 21 (I Sin[x])^11 Cos[x]^2 + 3 (I Sin[x])^1 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^1) + Exp[4 I y] (231 (I Sin[x])^7 Cos[x]^6 + 231 (I Sin[x])^6 Cos[x]^7 + 160 (I Sin[x])^5 Cos[x]^8 + 160 (I Sin[x])^8 Cos[x]^5 + 80 (I Sin[x])^4 Cos[x]^9 + 80 (I Sin[x])^9 Cos[x]^4 + 22 (I Sin[x])^3 Cos[x]^10 + 22 (I Sin[x])^10 Cos[x]^3 + 2 (I Sin[x])^11 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^11) + Exp[6 I y] (43 (I Sin[x])^4 Cos[x]^9 + 43 (I Sin[x])^9 Cos[x]^4 + 88 (I Sin[x])^7 Cos[x]^6 + 88 (I Sin[x])^6 Cos[x]^7 + 72 (I Sin[x])^5 Cos[x]^8 + 72 (I Sin[x])^8 Cos[x]^5 + 15 (I Sin[x])^3 Cos[x]^10 + 15 (I Sin[x])^10 Cos[x]^3 + 2 (I Sin[x])^2 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^2) + Exp[8 I y] (38 (I Sin[x])^6 Cos[x]^7 + 38 (I Sin[x])^7 Cos[x]^6 + 23 (I Sin[x])^8 Cos[x]^5 + 23 (I Sin[x])^5 Cos[x]^8 + 5 (I Sin[x])^9 Cos[x]^4 + 5 (I Sin[x])^4 Cos[x]^9) + Exp[10 I y] (4 (I Sin[x])^5 Cos[x]^8 + 4 (I Sin[x])^8 Cos[x]^5 + 7 (I Sin[x])^6 Cos[x]^7 + 7 (I Sin[x])^7 Cos[x]^6 + 1 (I Sin[x])^4 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^4) + Exp[12 I y] (1 (I Sin[x])^7 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^7))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-12 I y] (1 (I Sin[x])^7 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^7) + Exp[-10 I y] (4 (I Sin[x])^6 Cos[x]^7 + 4 (I Sin[x])^7 Cos[x]^6 + 4 (I Sin[x])^5 Cos[x]^8 + 4 (I Sin[x])^8 Cos[x]^5 + 3 (I Sin[x])^4 Cos[x]^9 + 3 (I Sin[x])^9 Cos[x]^4 + 1 (I Sin[x])^3 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^3) + Exp[-8 I y] (23 (I Sin[x])^8 Cos[x]^5 + 23 (I Sin[x])^5 Cos[x]^8 + 13 (I Sin[x])^9 Cos[x]^4 + 13 (I Sin[x])^4 Cos[x]^9 + 24 (I Sin[x])^6 Cos[x]^7 + 24 (I Sin[x])^7 Cos[x]^6 + 5 (I Sin[x])^3 Cos[x]^10 + 5 (I Sin[x])^10 Cos[x]^3 + 1 (I Sin[x])^2 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^2) + Exp[-6 I y] (89 (I Sin[x])^7 Cos[x]^6 + 89 (I Sin[x])^6 Cos[x]^7 + 38 (I Sin[x])^4 Cos[x]^9 + 38 (I Sin[x])^9 Cos[x]^4 + 66 (I Sin[x])^5 Cos[x]^8 + 66 (I Sin[x])^8 Cos[x]^5 + 19 (I Sin[x])^3 Cos[x]^10 + 19 (I Sin[x])^10 Cos[x]^3 + 7 (I Sin[x])^2 Cos[x]^11 + 7 (I Sin[x])^11 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^1) + Exp[-4 I y] (217 (I Sin[x])^7 Cos[x]^6 + 217 (I Sin[x])^6 Cos[x]^7 + 154 (I Sin[x])^8 Cos[x]^5 + 154 (I Sin[x])^5 Cos[x]^8 + 85 (I Sin[x])^9 Cos[x]^4 + 85 (I Sin[x])^4 Cos[x]^9 + 31 (I Sin[x])^10 Cos[x]^3 + 31 (I Sin[x])^3 Cos[x]^10 + 7 (I Sin[x])^2 Cos[x]^11 + 7 (I Sin[x])^11 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^1) + Exp[-2 I y] (284 (I Sin[x])^6 Cos[x]^7 + 284 (I Sin[x])^7 Cos[x]^6 + 239 (I Sin[x])^5 Cos[x]^8 + 239 (I Sin[x])^8 Cos[x]^5 + 76 (I Sin[x])^3 Cos[x]^10 + 76 (I Sin[x])^10 Cos[x]^3 + 159 (I Sin[x])^4 Cos[x]^9 + 159 (I Sin[x])^9 Cos[x]^4 + 26 (I Sin[x])^2 Cos[x]^11 + 26 (I Sin[x])^11 Cos[x]^2 + 7 (I Sin[x])^1 Cos[x]^12 + 7 (I Sin[x])^12 Cos[x]^1 + 1 Cos[x]^13 + 1 (I Sin[x])^13) + Exp[0 I y] (412 (I Sin[x])^6 Cos[x]^7 + 412 (I Sin[x])^7 Cos[x]^6 + 300 (I Sin[x])^8 Cos[x]^5 + 300 (I Sin[x])^5 Cos[x]^8 + 147 (I Sin[x])^9 Cos[x]^4 + 147 (I Sin[x])^4 Cos[x]^9 + 52 (I Sin[x])^3 Cos[x]^10 + 52 (I Sin[x])^10 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^11 + 12 (I Sin[x])^11 Cos[x]^2 + 1 (I Sin[x])^12 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^12) + Exp[2 I y] (242 (I Sin[x])^5 Cos[x]^8 + 242 (I Sin[x])^8 Cos[x]^5 + 320 (I Sin[x])^6 Cos[x]^7 + 320 (I Sin[x])^7 Cos[x]^6 + 141 (I Sin[x])^4 Cos[x]^9 + 141 (I Sin[x])^9 Cos[x]^4 + 65 (I Sin[x])^3 Cos[x]^10 + 65 (I Sin[x])^10 Cos[x]^3 + 21 (I Sin[x])^2 Cos[x]^11 + 21 (I Sin[x])^11 Cos[x]^2 + 3 (I Sin[x])^1 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^1) + Exp[4 I y] (231 (I Sin[x])^7 Cos[x]^6 + 231 (I Sin[x])^6 Cos[x]^7 + 160 (I Sin[x])^5 Cos[x]^8 + 160 (I Sin[x])^8 Cos[x]^5 + 80 (I Sin[x])^4 Cos[x]^9 + 80 (I Sin[x])^9 Cos[x]^4 + 22 (I Sin[x])^3 Cos[x]^10 + 22 (I Sin[x])^10 Cos[x]^3 + 2 (I Sin[x])^11 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^11) + Exp[6 I y] (43 (I Sin[x])^4 Cos[x]^9 + 43 (I Sin[x])^9 Cos[x]^4 + 88 (I Sin[x])^7 Cos[x]^6 + 88 (I Sin[x])^6 Cos[x]^7 + 72 (I Sin[x])^5 Cos[x]^8 + 72 (I Sin[x])^8 Cos[x]^5 + 15 (I Sin[x])^3 Cos[x]^10 + 15 (I Sin[x])^10 Cos[x]^3 + 2 (I Sin[x])^2 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^2) + Exp[8 I y] (38 (I Sin[x])^6 Cos[x]^7 + 38 (I Sin[x])^7 Cos[x]^6 + 23 (I Sin[x])^8 Cos[x]^5 + 23 (I Sin[x])^5 Cos[x]^8 + 5 (I Sin[x])^9 Cos[x]^4 + 5 (I Sin[x])^4 Cos[x]^9) + Exp[10 I y] (4 (I Sin[x])^5 Cos[x]^8 + 4 (I Sin[x])^8 Cos[x]^5 + 7 (I Sin[x])^6 Cos[x]^7 + 7 (I Sin[x])^7 Cos[x]^6 + 1 (I Sin[x])^4 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^4) + Exp[12 I y] (1 (I Sin[x])^7 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^7));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":476.4666666667,"max_line_length":3353,"alphanum_fraction":0.4926542605} {"size":9259,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 16;\nname = \"16v1 2 2 2 2 2 4 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^7) + Exp[-13 I y] (4 (I Sin[x])^6 Cos[x]^10 + 4 (I Sin[x])^10 Cos[x]^6 + 8 (I Sin[x])^8 Cos[x]^8 + 7 (I Sin[x])^7 Cos[x]^9 + 7 (I Sin[x])^9 Cos[x]^7) + Exp[-11 I y] (52 (I Sin[x])^8 Cos[x]^8 + 30 (I Sin[x])^6 Cos[x]^10 + 30 (I Sin[x])^10 Cos[x]^6 + 40 (I Sin[x])^9 Cos[x]^7 + 40 (I Sin[x])^7 Cos[x]^9 + 9 (I Sin[x])^5 Cos[x]^11 + 9 (I Sin[x])^11 Cos[x]^5) + Exp[-9 I y] (180 (I Sin[x])^7 Cos[x]^9 + 180 (I Sin[x])^9 Cos[x]^7 + 216 (I Sin[x])^8 Cos[x]^8 + 106 (I Sin[x])^6 Cos[x]^10 + 106 (I Sin[x])^10 Cos[x]^6 + 51 (I Sin[x])^5 Cos[x]^11 + 51 (I Sin[x])^11 Cos[x]^5 + 10 (I Sin[x])^4 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^4) + Exp[-7 I y] (512 (I Sin[x])^9 Cos[x]^7 + 512 (I Sin[x])^7 Cos[x]^9 + 322 (I Sin[x])^10 Cos[x]^6 + 322 (I Sin[x])^6 Cos[x]^10 + 572 (I Sin[x])^8 Cos[x]^8 + 172 (I Sin[x])^5 Cos[x]^11 + 172 (I Sin[x])^11 Cos[x]^5 + 64 (I Sin[x])^4 Cos[x]^12 + 64 (I Sin[x])^12 Cos[x]^4 + 9 (I Sin[x])^3 Cos[x]^13 + 9 (I Sin[x])^13 Cos[x]^3) + Exp[-5 I y] (1172 (I Sin[x])^8 Cos[x]^8 + 748 (I Sin[x])^6 Cos[x]^10 + 748 (I Sin[x])^10 Cos[x]^6 + 1052 (I Sin[x])^7 Cos[x]^9 + 1052 (I Sin[x])^9 Cos[x]^7 + 388 (I Sin[x])^5 Cos[x]^11 + 388 (I Sin[x])^11 Cos[x]^5 + 172 (I Sin[x])^4 Cos[x]^12 + 172 (I Sin[x])^12 Cos[x]^4 + 51 (I Sin[x])^3 Cos[x]^13 + 51 (I Sin[x])^13 Cos[x]^3 + 6 (I Sin[x])^2 Cos[x]^14 + 6 (I Sin[x])^14 Cos[x]^2) + Exp[-3 I y] (2000 (I Sin[x])^8 Cos[x]^8 + 1238 (I Sin[x])^6 Cos[x]^10 + 1238 (I Sin[x])^10 Cos[x]^6 + 1747 (I Sin[x])^9 Cos[x]^7 + 1747 (I Sin[x])^7 Cos[x]^9 + 641 (I Sin[x])^5 Cos[x]^11 + 641 (I Sin[x])^11 Cos[x]^5 + 260 (I Sin[x])^4 Cos[x]^12 + 260 (I Sin[x])^12 Cos[x]^4 + 95 (I Sin[x])^3 Cos[x]^13 + 95 (I Sin[x])^13 Cos[x]^3 + 22 (I Sin[x])^2 Cos[x]^14 + 22 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[-1 I y] (2063 (I Sin[x])^7 Cos[x]^9 + 2063 (I Sin[x])^9 Cos[x]^7 + 2270 (I Sin[x])^8 Cos[x]^8 + 1546 (I Sin[x])^6 Cos[x]^10 + 1546 (I Sin[x])^10 Cos[x]^6 + 985 (I Sin[x])^5 Cos[x]^11 + 985 (I Sin[x])^11 Cos[x]^5 + 460 (I Sin[x])^4 Cos[x]^12 + 460 (I Sin[x])^12 Cos[x]^4 + 175 (I Sin[x])^3 Cos[x]^13 + 175 (I Sin[x])^13 Cos[x]^3 + 58 (I Sin[x])^2 Cos[x]^14 + 58 (I Sin[x])^14 Cos[x]^2 + 12 (I Sin[x])^1 Cos[x]^15 + 12 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[1 I y] (2299 (I Sin[x])^9 Cos[x]^7 + 2299 (I Sin[x])^7 Cos[x]^9 + 1566 (I Sin[x])^10 Cos[x]^6 + 1566 (I Sin[x])^6 Cos[x]^10 + 2560 (I Sin[x])^8 Cos[x]^8 + 861 (I Sin[x])^5 Cos[x]^11 + 861 (I Sin[x])^11 Cos[x]^5 + 348 (I Sin[x])^4 Cos[x]^12 + 348 (I Sin[x])^12 Cos[x]^4 + 75 (I Sin[x])^3 Cos[x]^13 + 75 (I Sin[x])^13 Cos[x]^3 + 6 (I Sin[x])^2 Cos[x]^14 + 6 (I Sin[x])^14 Cos[x]^2) + Exp[3 I y] (1776 (I Sin[x])^8 Cos[x]^8 + 1228 (I Sin[x])^6 Cos[x]^10 + 1228 (I Sin[x])^10 Cos[x]^6 + 1619 (I Sin[x])^7 Cos[x]^9 + 1619 (I Sin[x])^9 Cos[x]^7 + 721 (I Sin[x])^5 Cos[x]^11 + 721 (I Sin[x])^11 Cos[x]^5 + 376 (I Sin[x])^4 Cos[x]^12 + 376 (I Sin[x])^12 Cos[x]^4 + 143 (I Sin[x])^3 Cos[x]^13 + 143 (I Sin[x])^13 Cos[x]^3 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(I Sin[x])^13 Cos[x]^2) + Exp[-8 I y] (45 (I Sin[x])^4 Cos[x]^11 + 45 (I Sin[x])^11 Cos[x]^4 + 102 (I Sin[x])^9 Cos[x]^6 + 102 (I Sin[x])^6 Cos[x]^9 + 66 (I Sin[x])^5 Cos[x]^10 + 66 (I Sin[x])^10 Cos[x]^5 + 124 (I Sin[x])^8 Cos[x]^7 + 124 (I Sin[x])^7 Cos[x]^8 + 7 (I Sin[x])^2 Cos[x]^13 + 7 (I Sin[x])^13 Cos[x]^2 + 19 (I Sin[x])^3 Cos[x]^12 + 19 (I Sin[x])^12 Cos[x]^3 + 1 (I Sin[x])^1 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^1) + Exp[-6 I y] (306 (I Sin[x])^6 Cos[x]^9 + 306 (I Sin[x])^9 Cos[x]^6 + 96 (I Sin[x])^4 Cos[x]^11 + 96 (I Sin[x])^11 Cos[x]^4 + 186 (I Sin[x])^5 Cos[x]^10 + 186 (I Sin[x])^10 Cos[x]^5 + 376 (I Sin[x])^7 Cos[x]^8 + 376 (I Sin[x])^8 Cos[x]^7 + 29 (I Sin[x])^3 Cos[x]^12 + 29 (I Sin[x])^12 Cos[x]^3 + 7 (I Sin[x])^2 Cos[x]^13 + 7 (I Sin[x])^13 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^1) + Exp[-4 I y] (92 (I Sin[x])^3 Cos[x]^12 + 92 (I Sin[x])^12 Cos[x]^3 + 700 (I Sin[x])^8 Cos[x]^7 + 700 (I Sin[x])^7 Cos[x]^8 + 204 (I Sin[x])^4 Cos[x]^11 + 204 (I Sin[x])^11 Cos[x]^4 + 28 (I Sin[x])^2 Cos[x]^13 + 28 (I Sin[x])^13 Cos[x]^2 + 399 (I Sin[x])^5 Cos[x]^10 + 399 (I Sin[x])^10 Cos[x]^5 + 571 (I Sin[x])^6 Cos[x]^9 + 571 (I Sin[x])^9 Cos[x]^6 + 7 (I Sin[x])^1 Cos[x]^14 + 7 (I Sin[x])^14 Cos[x]^1 + 1 Cos[x]^15 + 1 (I Sin[x])^15) + Exp[-2 I y] (544 (I Sin[x])^5 Cos[x]^10 + 544 (I Sin[x])^10 Cos[x]^5 + 1218 (I Sin[x])^7 Cos[x]^8 + 1218 (I Sin[x])^8 Cos[x]^7 + 924 (I Sin[x])^6 Cos[x]^9 + 924 (I Sin[x])^9 Cos[x]^6 + 228 (I Sin[x])^4 Cos[x]^11 + 228 (I Sin[x])^11 Cos[x]^4 + 74 (I Sin[x])^3 Cos[x]^12 + 74 (I Sin[x])^12 Cos[x]^3 + 14 (I Sin[x])^2 Cos[x]^13 + 14 (I Sin[x])^13 Cos[x]^2 + 1 (I Sin[x])^14 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^14) + Exp[0 I y] (356 (I Sin[x])^4 Cos[x]^11 + 356 (I Sin[x])^11 Cos[x]^4 + 1021 (I Sin[x])^9 Cos[x]^6 + 1021 (I Sin[x])^6 Cos[x]^9 + 1224 (I Sin[x])^7 Cos[x]^8 + 1224 (I Sin[x])^8 Cos[x]^7 + 657 (I Sin[x])^5 Cos[x]^10 + 657 (I Sin[x])^10 Cos[x]^5 + 132 (I Sin[x])^3 Cos[x]^12 + 132 (I Sin[x])^12 Cos[x]^3 + 37 (I Sin[x])^2 Cos[x]^13 + 37 (I Sin[x])^13 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^14 + 5 (I Sin[x])^14 Cos[x]^1) + Exp[2 I y] (958 (I Sin[x])^6 Cos[x]^9 + 958 (I Sin[x])^9 Cos[x]^6 + 1282 (I Sin[x])^8 Cos[x]^7 + 1282 (I Sin[x])^7 Cos[x]^8 + 198 (I Sin[x])^4 Cos[x]^11 + 198 (I Sin[x])^11 Cos[x]^4 + 518 (I Sin[x])^5 Cos[x]^10 + 518 (I Sin[x])^10 Cos[x]^5 + 43 (I Sin[x])^3 Cos[x]^12 + 43 (I Sin[x])^12 Cos[x]^3 + 4 (I Sin[x])^13 Cos[x]^2 + 4 (I Sin[x])^2 Cos[x]^13) + Exp[4 I y] (52 (I Sin[x])^3 Cos[x]^12 + 52 (I Sin[x])^12 Cos[x]^3 + 794 (I Sin[x])^8 Cos[x]^7 + 794 (I Sin[x])^7 Cos[x]^8 + 382 (I Sin[x])^5 Cos[x]^10 + 382 (I Sin[x])^10 Cos[x]^5 + 606 (I Sin[x])^6 Cos[x]^9 + 606 (I Sin[x])^9 Cos[x]^6 + 161 (I Sin[x])^4 Cos[x]^11 + 161 (I Sin[x])^11 Cos[x]^4 + 7 (I Sin[x])^2 Cos[x]^13 + 7 (I Sin[x])^13 Cos[x]^2) + Exp[6 I y] (479 (I Sin[x])^7 Cos[x]^8 + 479 (I Sin[x])^8 Cos[x]^7 + 148 (I Sin[x])^5 Cos[x]^10 + 148 (I Sin[x])^10 Cos[x]^5 + 333 (I Sin[x])^6 Cos[x]^9 + 333 (I Sin[x])^9 Cos[x]^6 + 37 (I Sin[x])^4 Cos[x]^11 + 37 (I Sin[x])^11 Cos[x]^4 + 4 (I Sin[x])^12 Cos[x]^3 + 4 (I Sin[x])^3 Cos[x]^12) + Exp[8 I y] (25 (I Sin[x])^4 Cos[x]^11 + 25 (I Sin[x])^11 Cos[x]^4 + 123 (I Sin[x])^9 Cos[x]^6 + 123 (I Sin[x])^6 Cos[x]^9 + 152 (I Sin[x])^7 Cos[x]^8 + 152 (I Sin[x])^8 Cos[x]^7 + 61 (I Sin[x])^5 Cos[x]^10 + 61 (I Sin[x])^10 Cos[x]^5 + 3 (I Sin[x])^3 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^3) + Exp[10 I y] (54 (I Sin[x])^8 Cos[x]^7 + 54 (I Sin[x])^7 Cos[x]^8 + 27 (I Sin[x])^6 Cos[x]^9 + 27 (I Sin[x])^9 Cos[x]^6 + 9 (I Sin[x])^10 Cos[x]^5 + 9 (I Sin[x])^5 Cos[x]^10 + 1 (I Sin[x])^11 Cos[x]^4 + 1 (I Sin[x])^4 Cos[x]^11) + Exp[12 I y] (3 (I Sin[x])^5 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^5 + 7 (I Sin[x])^8 Cos[x]^7 + 7 (I Sin[x])^7 Cos[x]^8 + 4 (I Sin[x])^6 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^6) + Exp[14 I y] (1 (I Sin[x])^9 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^9))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-14 I y] (1 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^4) + Exp[-12 I y] (1 (I Sin[x])^3 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^3 + 5 (I Sin[x])^10 Cos[x]^5 + 5 (I Sin[x])^5 Cos[x]^10 + 2 (I Sin[x])^4 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^4 + 4 (I Sin[x])^9 Cos[x]^6 + 4 (I Sin[x])^6 Cos[x]^9 + 2 (I Sin[x])^8 Cos[x]^7 + 2 (I Sin[x])^7 Cos[x]^8) + Exp[-10 I y] (25 (I Sin[x])^5 Cos[x]^10 + 25 (I Sin[x])^10 Cos[x]^5 + 25 (I Sin[x])^6 Cos[x]^9 + 25 (I Sin[x])^9 Cos[x]^6 + 23 (I Sin[x])^7 Cos[x]^8 + 23 (I Sin[x])^8 Cos[x]^7 + 6 (I Sin[x])^3 Cos[x]^12 + 6 (I Sin[x])^12 Cos[x]^3 + 11 (I Sin[x])^4 Cos[x]^11 + 11 (I Sin[x])^11 Cos[x]^4 + 1 (I Sin[x])^2 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^2) + Exp[-8 I y] (45 (I Sin[x])^4 Cos[x]^11 + 45 (I Sin[x])^11 Cos[x]^4 + 102 (I Sin[x])^9 Cos[x]^6 + 102 (I Sin[x])^6 Cos[x]^9 + 66 (I Sin[x])^5 Cos[x]^10 + 66 (I Sin[x])^10 Cos[x]^5 + 124 (I Sin[x])^8 Cos[x]^7 + 124 (I Sin[x])^7 Cos[x]^8 + 7 (I Sin[x])^2 Cos[x]^13 + 7 (I Sin[x])^13 Cos[x]^2 + 19 (I Sin[x])^3 Cos[x]^12 + 19 (I Sin[x])^12 Cos[x]^3 + 1 (I Sin[x])^1 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^1) + Exp[-6 I y] (306 (I Sin[x])^6 Cos[x]^9 + 306 (I Sin[x])^9 Cos[x]^6 + 96 (I Sin[x])^4 Cos[x]^11 + 96 (I Sin[x])^11 Cos[x]^4 + 186 (I Sin[x])^5 Cos[x]^10 + 186 (I Sin[x])^10 Cos[x]^5 + 376 (I Sin[x])^7 Cos[x]^8 + 376 (I Sin[x])^8 Cos[x]^7 + 29 (I Sin[x])^3 Cos[x]^12 + 29 (I Sin[x])^12 Cos[x]^3 + 7 (I Sin[x])^2 Cos[x]^13 + 7 (I Sin[x])^13 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^1) + Exp[-4 I y] (92 (I Sin[x])^3 Cos[x]^12 + 92 (I Sin[x])^12 Cos[x]^3 + 700 (I Sin[x])^8 Cos[x]^7 + 700 (I Sin[x])^7 Cos[x]^8 + 204 (I Sin[x])^4 Cos[x]^11 + 204 (I Sin[x])^11 Cos[x]^4 + 28 (I Sin[x])^2 Cos[x]^13 + 28 (I Sin[x])^13 Cos[x]^2 + 399 (I Sin[x])^5 Cos[x]^10 + 399 (I Sin[x])^10 Cos[x]^5 + 571 (I Sin[x])^6 Cos[x]^9 + 571 (I Sin[x])^9 Cos[x]^6 + 7 (I Sin[x])^1 Cos[x]^14 + 7 (I Sin[x])^14 Cos[x]^1 + 1 Cos[x]^15 + 1 (I Sin[x])^15) + Exp[-2 I y] (544 (I Sin[x])^5 Cos[x]^10 + 544 (I Sin[x])^10 Cos[x]^5 + 1218 (I Sin[x])^7 Cos[x]^8 + 1218 (I Sin[x])^8 Cos[x]^7 + 924 (I Sin[x])^6 Cos[x]^9 + 924 (I Sin[x])^9 Cos[x]^6 + 228 (I Sin[x])^4 Cos[x]^11 + 228 (I Sin[x])^11 Cos[x]^4 + 74 (I Sin[x])^3 Cos[x]^12 + 74 (I Sin[x])^12 Cos[x]^3 + 14 (I Sin[x])^2 Cos[x]^13 + 14 (I Sin[x])^13 Cos[x]^2 + 1 (I Sin[x])^14 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^14) + Exp[0 I y] (356 (I Sin[x])^4 Cos[x]^11 + 356 (I Sin[x])^11 Cos[x]^4 + 1021 (I Sin[x])^9 Cos[x]^6 + 1021 (I Sin[x])^6 Cos[x]^9 + 1224 (I Sin[x])^7 Cos[x]^8 + 1224 (I Sin[x])^8 Cos[x]^7 + 657 (I Sin[x])^5 Cos[x]^10 + 657 (I Sin[x])^10 Cos[x]^5 + 132 (I Sin[x])^3 Cos[x]^12 + 132 (I Sin[x])^12 Cos[x]^3 + 37 (I Sin[x])^2 Cos[x]^13 + 37 (I Sin[x])^13 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^14 + 5 (I Sin[x])^14 Cos[x]^1) + Exp[2 I y] (958 (I Sin[x])^6 Cos[x]^9 + 958 (I Sin[x])^9 Cos[x]^6 + 1282 (I Sin[x])^8 Cos[x]^7 + 1282 (I Sin[x])^7 Cos[x]^8 + 198 (I Sin[x])^4 Cos[x]^11 + 198 (I Sin[x])^11 Cos[x]^4 + 518 (I Sin[x])^5 Cos[x]^10 + 518 (I Sin[x])^10 Cos[x]^5 + 43 (I Sin[x])^3 Cos[x]^12 + 43 (I Sin[x])^12 Cos[x]^3 + 4 (I Sin[x])^13 Cos[x]^2 + 4 (I Sin[x])^2 Cos[x]^13) + Exp[4 I y] (52 (I Sin[x])^3 Cos[x]^12 + 52 (I Sin[x])^12 Cos[x]^3 + 794 (I Sin[x])^8 Cos[x]^7 + 794 (I Sin[x])^7 Cos[x]^8 + 382 (I Sin[x])^5 Cos[x]^10 + 382 (I Sin[x])^10 Cos[x]^5 + 606 (I Sin[x])^6 Cos[x]^9 + 606 (I Sin[x])^9 Cos[x]^6 + 161 (I Sin[x])^4 Cos[x]^11 + 161 (I Sin[x])^11 Cos[x]^4 + 7 (I Sin[x])^2 Cos[x]^13 + 7 (I Sin[x])^13 Cos[x]^2) + Exp[6 I y] (479 (I Sin[x])^7 Cos[x]^8 + 479 (I Sin[x])^8 Cos[x]^7 + 148 (I Sin[x])^5 Cos[x]^10 + 148 (I Sin[x])^10 Cos[x]^5 + 333 (I Sin[x])^6 Cos[x]^9 + 333 (I Sin[x])^9 Cos[x]^6 + 37 (I Sin[x])^4 Cos[x]^11 + 37 (I Sin[x])^11 Cos[x]^4 + 4 (I Sin[x])^12 Cos[x]^3 + 4 (I Sin[x])^3 Cos[x]^12) + Exp[8 I y] (25 (I Sin[x])^4 Cos[x]^11 + 25 (I Sin[x])^11 Cos[x]^4 + 123 (I Sin[x])^9 Cos[x]^6 + 123 (I Sin[x])^6 Cos[x]^9 + 152 (I Sin[x])^7 Cos[x]^8 + 152 (I Sin[x])^8 Cos[x]^7 + 61 (I Sin[x])^5 Cos[x]^10 + 61 (I Sin[x])^10 Cos[x]^5 + 3 (I Sin[x])^3 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^3) + Exp[10 I y] (54 (I Sin[x])^8 Cos[x]^7 + 54 (I Sin[x])^7 Cos[x]^8 + 27 (I Sin[x])^6 Cos[x]^9 + 27 (I Sin[x])^9 Cos[x]^6 + 9 (I Sin[x])^10 Cos[x]^5 + 9 (I Sin[x])^5 Cos[x]^10 + 1 (I Sin[x])^11 Cos[x]^4 + 1 (I Sin[x])^4 Cos[x]^11) + Exp[12 I y] (3 (I Sin[x])^5 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^5 + 7 (I Sin[x])^8 Cos[x]^7 + 7 (I Sin[x])^7 Cos[x]^8 + 4 (I Sin[x])^6 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^6) + Exp[14 I y] (1 (I Sin[x])^9 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^9));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":636.6,"max_line_length":4554,"alphanum_fraction":0.4998429155} {"size":7867,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 14;\nname = \"14v1 1 2 1 1 3 2 1 1 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-13 I y] (2 (I Sin[x])^7 Cos[x]^7) + Exp[-11 I y] (7 (I Sin[x])^6 Cos[x]^8 + 7 (I Sin[x])^8 Cos[x]^6 + 8 (I Sin[x])^7 Cos[x]^7 + 2 (I Sin[x])^5 Cos[x]^9 + 2 (I Sin[x])^9 Cos[x]^5) + Exp[-9 I y] (40 (I Sin[x])^8 Cos[x]^6 + 40 (I Sin[x])^6 Cos[x]^8 + 44 (I Sin[x])^7 Cos[x]^7 + 14 (I Sin[x])^9 Cos[x]^5 + 14 (I Sin[x])^5 Cos[x]^9 + 2 (I Sin[x])^4 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^4) + Exp[-7 I y] (72 (I Sin[x])^5 Cos[x]^9 + 72 (I Sin[x])^9 Cos[x]^5 + 140 (I Sin[x])^7 Cos[x]^7 + 113 (I Sin[x])^8 Cos[x]^6 + 113 (I Sin[x])^6 Cos[x]^8 + 27 (I Sin[x])^4 Cos[x]^10 + 27 (I Sin[x])^10 Cos[x]^4 + 4 (I Sin[x])^3 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^3) + Exp[-5 I y] (176 (I Sin[x])^9 Cos[x]^5 + 176 (I Sin[x])^5 Cos[x]^9 + 360 (I Sin[x])^7 Cos[x]^7 + 289 (I Sin[x])^8 Cos[x]^6 + 289 (I Sin[x])^6 Cos[x]^8 + 61 (I Sin[x])^10 Cos[x]^4 + 61 (I Sin[x])^4 Cos[x]^10 + 9 (I Sin[x])^3 Cos[x]^11 + 9 (I Sin[x])^11 Cos[x]^3) + Exp[-3 I y] (491 (I Sin[x])^6 Cos[x]^8 + 491 (I Sin[x])^8 Cos[x]^6 + 152 (I Sin[x])^4 Cos[x]^10 + 152 (I Sin[x])^10 Cos[x]^4 + 546 (I Sin[x])^7 Cos[x]^7 + 312 (I Sin[x])^5 Cos[x]^9 + 312 (I Sin[x])^9 Cos[x]^5 + 51 (I Sin[x])^3 Cos[x]^11 + 51 (I Sin[x])^11 Cos[x]^3 + 8 (I Sin[x])^2 Cos[x]^12 + 8 (I Sin[x])^12 Cos[x]^2) + Exp[-1 I y] (680 (I Sin[x])^8 Cos[x]^6 + 680 (I Sin[x])^6 Cos[x]^8 + 180 (I Sin[x])^4 Cos[x]^10 + 180 (I Sin[x])^10 Cos[x]^4 + 786 (I Sin[x])^7 Cos[x]^7 + 400 (I Sin[x])^5 Cos[x]^9 + 400 (I Sin[x])^9 Cos[x]^5 + 55 (I Sin[x])^3 Cos[x]^11 + 55 (I Sin[x])^11 Cos[x]^3 + 8 (I Sin[x])^2 Cos[x]^12 + 8 (I Sin[x])^12 Cos[x]^2) + Exp[1 I y] (431 (I Sin[x])^5 Cos[x]^9 + 431 (I Sin[x])^9 Cos[x]^5 + 662 (I Sin[x])^7 Cos[x]^7 + 101 (I Sin[x])^3 Cos[x]^11 + 101 (I Sin[x])^11 Cos[x]^3 + 576 (I Sin[x])^6 Cos[x]^8 + 576 (I Sin[x])^8 Cos[x]^6 + 241 (I Sin[x])^4 Cos[x]^10 + 241 (I Sin[x])^10 Cos[x]^4 + 31 (I Sin[x])^2 Cos[x]^12 + 31 (I Sin[x])^12 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^13 + 5 (I Sin[x])^13 Cos[x]^1) + Exp[3 I y] (528 (I Sin[x])^7 Cos[x]^7 + 330 (I Sin[x])^9 Cos[x]^5 + 330 (I Sin[x])^5 Cos[x]^9 + 55 (I Sin[x])^3 Cos[x]^11 + 55 (I Sin[x])^11 Cos[x]^3 + 462 (I Sin[x])^8 Cos[x]^6 + 462 (I Sin[x])^6 Cos[x]^8 + 160 (I Sin[x])^4 Cos[x]^10 + 160 (I Sin[x])^10 Cos[x]^4 + 14 (I Sin[x])^12 Cos[x]^2 + 14 (I Sin[x])^2 Cos[x]^12 + 2 (I Sin[x])^1 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^1) + Exp[5 I y] (216 (I Sin[x])^6 Cos[x]^8 + 216 (I Sin[x])^8 Cos[x]^6 + 125 (I Sin[x])^4 Cos[x]^10 + 125 (I Sin[x])^10 Cos[x]^4 + 23 (I Sin[x])^2 Cos[x]^12 + 23 (I Sin[x])^12 Cos[x]^2 + 176 (I Sin[x])^5 Cos[x]^9 + 176 (I Sin[x])^9 Cos[x]^5 + 65 (I Sin[x])^3 Cos[x]^11 + 65 (I Sin[x])^11 Cos[x]^3 + 206 (I Sin[x])^7 Cos[x]^7 + 6 (I Sin[x])^1 Cos[x]^13 + 6 (I Sin[x])^13 Cos[x]^1 + 1 Cos[x]^14 + 1 (I Sin[x])^14) + Exp[7 I y] (108 (I Sin[x])^6 Cos[x]^8 + 108 (I Sin[x])^8 Cos[x]^6 + 36 (I Sin[x])^10 Cos[x]^4 + 36 (I Sin[x])^4 Cos[x]^10 + 66 (I Sin[x])^9 Cos[x]^5 + 66 (I Sin[x])^5 Cos[x]^9 + 13 (I Sin[x])^11 Cos[x]^3 + 13 (I Sin[x])^3 Cos[x]^11 + 122 (I Sin[x])^7 Cos[x]^7 + 2 (I Sin[x])^2 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^2) + Exp[9 I y] (22 (I Sin[x])^7 Cos[x]^7 + 19 (I Sin[x])^9 Cos[x]^5 + 19 (I Sin[x])^5 Cos[x]^9 + 11 (I Sin[x])^3 Cos[x]^11 + 11 (I Sin[x])^11 Cos[x]^3 + 15 (I Sin[x])^6 Cos[x]^8 + 15 (I Sin[x])^8 Cos[x]^6 + 16 (I Sin[x])^4 Cos[x]^10 + 16 (I Sin[x])^10 Cos[x]^4 + 1 (I Sin[x])^1 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^1 + 5 (I Sin[x])^2 Cos[x]^12 + 5 (I Sin[x])^12 Cos[x]^2) + Exp[11 I y] (6 (I Sin[x])^7 Cos[x]^7 + 4 (I Sin[x])^5 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^5 + 5 (I Sin[x])^8 Cos[x]^6 + 5 (I Sin[x])^6 Cos[x]^8 + 1 (I Sin[x])^10 Cos[x]^4 + 1 (I Sin[x])^4 Cos[x]^10) + Exp[13 I y] (1 (I Sin[x])^6 Cos[x]^8 + 1 (I Sin[x])^8 Cos[x]^6))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-13 I y] (2 (I Sin[x])^7 Cos[x]^7) + Exp[-11 I y] (7 (I Sin[x])^6 Cos[x]^8 + 7 (I Sin[x])^8 Cos[x]^6 + 8 (I Sin[x])^7 Cos[x]^7 + 2 (I Sin[x])^5 Cos[x]^9 + 2 (I Sin[x])^9 Cos[x]^5) + Exp[-9 I y] (40 (I Sin[x])^8 Cos[x]^6 + 40 (I Sin[x])^6 Cos[x]^8 + 44 (I Sin[x])^7 Cos[x]^7 + 14 (I Sin[x])^9 Cos[x]^5 + 14 (I Sin[x])^5 Cos[x]^9 + 2 (I Sin[x])^4 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^4) + Exp[-7 I y] (72 (I Sin[x])^5 Cos[x]^9 + 72 (I Sin[x])^9 Cos[x]^5 + 140 (I Sin[x])^7 Cos[x]^7 + 113 (I Sin[x])^8 Cos[x]^6 + 113 (I Sin[x])^6 Cos[x]^8 + 27 (I Sin[x])^4 Cos[x]^10 + 27 (I Sin[x])^10 Cos[x]^4 + 4 (I Sin[x])^3 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^3) + Exp[-5 I y] (176 (I Sin[x])^9 Cos[x]^5 + 176 (I Sin[x])^5 Cos[x]^9 + 360 (I Sin[x])^7 Cos[x]^7 + 289 (I Sin[x])^8 Cos[x]^6 + 289 (I Sin[x])^6 Cos[x]^8 + 61 (I Sin[x])^10 Cos[x]^4 + 61 (I Sin[x])^4 Cos[x]^10 + 9 (I Sin[x])^3 Cos[x]^11 + 9 (I Sin[x])^11 Cos[x]^3) + Exp[-3 I y] (491 (I Sin[x])^6 Cos[x]^8 + 491 (I Sin[x])^8 Cos[x]^6 + 152 (I Sin[x])^4 Cos[x]^10 + 152 (I Sin[x])^10 Cos[x]^4 + 546 (I Sin[x])^7 Cos[x]^7 + 312 (I Sin[x])^5 Cos[x]^9 + 312 (I Sin[x])^9 Cos[x]^5 + 51 (I Sin[x])^3 Cos[x]^11 + 51 (I Sin[x])^11 Cos[x]^3 + 8 (I Sin[x])^2 Cos[x]^12 + 8 (I Sin[x])^12 Cos[x]^2) + Exp[-1 I y] (680 (I Sin[x])^8 Cos[x]^6 + 680 (I Sin[x])^6 Cos[x]^8 + 180 (I Sin[x])^4 Cos[x]^10 + 180 (I Sin[x])^10 Cos[x]^4 + 786 (I Sin[x])^7 Cos[x]^7 + 400 (I Sin[x])^5 Cos[x]^9 + 400 (I Sin[x])^9 Cos[x]^5 + 55 (I Sin[x])^3 Cos[x]^11 + 55 (I Sin[x])^11 Cos[x]^3 + 8 (I Sin[x])^2 Cos[x]^12 + 8 (I Sin[x])^12 Cos[x]^2) + Exp[1 I y] (431 (I Sin[x])^5 Cos[x]^9 + 431 (I Sin[x])^9 Cos[x]^5 + 662 (I Sin[x])^7 Cos[x]^7 + 101 (I Sin[x])^3 Cos[x]^11 + 101 (I Sin[x])^11 Cos[x]^3 + 576 (I Sin[x])^6 Cos[x]^8 + 576 (I Sin[x])^8 Cos[x]^6 + 241 (I Sin[x])^4 Cos[x]^10 + 241 (I Sin[x])^10 Cos[x]^4 + 31 (I Sin[x])^2 Cos[x]^12 + 31 (I Sin[x])^12 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^13 + 5 (I Sin[x])^13 Cos[x]^1) + Exp[3 I y] (528 (I Sin[x])^7 Cos[x]^7 + 330 (I Sin[x])^9 Cos[x]^5 + 330 (I Sin[x])^5 Cos[x]^9 + 55 (I Sin[x])^3 Cos[x]^11 + 55 (I Sin[x])^11 Cos[x]^3 + 462 (I Sin[x])^8 Cos[x]^6 + 462 (I Sin[x])^6 Cos[x]^8 + 160 (I Sin[x])^4 Cos[x]^10 + 160 (I Sin[x])^10 Cos[x]^4 + 14 (I Sin[x])^12 Cos[x]^2 + 14 (I Sin[x])^2 Cos[x]^12 + 2 (I Sin[x])^1 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^1) + Exp[5 I y] (216 (I Sin[x])^6 Cos[x]^8 + 216 (I Sin[x])^8 Cos[x]^6 + 125 (I Sin[x])^4 Cos[x]^10 + 125 (I Sin[x])^10 Cos[x]^4 + 23 (I Sin[x])^2 Cos[x]^12 + 23 (I Sin[x])^12 Cos[x]^2 + 176 (I Sin[x])^5 Cos[x]^9 + 176 (I Sin[x])^9 Cos[x]^5 + 65 (I Sin[x])^3 Cos[x]^11 + 65 (I Sin[x])^11 Cos[x]^3 + 206 (I Sin[x])^7 Cos[x]^7 + 6 (I Sin[x])^1 Cos[x]^13 + 6 (I Sin[x])^13 Cos[x]^1 + 1 Cos[x]^14 + 1 (I Sin[x])^14) + Exp[7 I y] (108 (I Sin[x])^6 Cos[x]^8 + 108 (I Sin[x])^8 Cos[x]^6 + 36 (I Sin[x])^10 Cos[x]^4 + 36 (I Sin[x])^4 Cos[x]^10 + 66 (I Sin[x])^9 Cos[x]^5 + 66 (I Sin[x])^5 Cos[x]^9 + 13 (I Sin[x])^11 Cos[x]^3 + 13 (I Sin[x])^3 Cos[x]^11 + 122 (I Sin[x])^7 Cos[x]^7 + 2 (I Sin[x])^2 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^2) + Exp[9 I y] (22 (I Sin[x])^7 Cos[x]^7 + 19 (I Sin[x])^9 Cos[x]^5 + 19 (I Sin[x])^5 Cos[x]^9 + 11 (I Sin[x])^3 Cos[x]^11 + 11 (I Sin[x])^11 Cos[x]^3 + 15 (I Sin[x])^6 Cos[x]^8 + 15 (I Sin[x])^8 Cos[x]^6 + 16 (I Sin[x])^4 Cos[x]^10 + 16 (I Sin[x])^10 Cos[x]^4 + 1 (I Sin[x])^1 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^1 + 5 (I Sin[x])^2 Cos[x]^12 + 5 (I Sin[x])^12 Cos[x]^2) + Exp[11 I y] (6 (I Sin[x])^7 Cos[x]^7 + 4 (I Sin[x])^5 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^5 + 5 (I Sin[x])^8 Cos[x]^6 + 5 (I Sin[x])^6 Cos[x]^8 + 1 (I Sin[x])^10 Cos[x]^4 + 1 (I Sin[x])^4 Cos[x]^10) + Exp[13 I y] (1 (I Sin[x])^6 Cos[x]^8 + 1 (I Sin[x])^8 Cos[x]^6));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":524.4666666667,"max_line_length":3709,"alphanum_fraction":0.4973941782} {"size":10921,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 16;\nname = \"16v2 1 1 5 2 4 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^10 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^10) + Exp[-13 I y] (4 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^5 Cos[x]^11 + 2 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^4 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^4 + 4 (I Sin[x])^9 Cos[x]^7 + 4 (I Sin[x])^7 Cos[x]^9 + 6 (I Sin[x])^8 Cos[x]^8) + Exp[-11 I y] (39 (I Sin[x])^9 Cos[x]^7 + 39 (I Sin[x])^7 Cos[x]^9 + 15 (I Sin[x])^11 Cos[x]^5 + 15 (I Sin[x])^5 Cos[x]^11 + 38 (I Sin[x])^8 Cos[x]^8 + 24 (I Sin[x])^10 Cos[x]^6 + 24 (I Sin[x])^6 Cos[x]^10 + 6 (I Sin[x])^12 Cos[x]^4 + 6 (I Sin[x])^4 Cos[x]^12 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3) + Exp[-9 I y] (123 (I Sin[x])^10 Cos[x]^6 + 123 (I Sin[x])^6 Cos[x]^10 + 33 (I Sin[x])^4 Cos[x]^12 + 33 (I Sin[x])^12 Cos[x]^4 + 142 (I Sin[x])^9 Cos[x]^7 + 142 (I Sin[x])^7 Cos[x]^9 + 13 (I Sin[x])^3 Cos[x]^13 + 13 (I Sin[x])^13 Cos[x]^3 + 69 (I Sin[x])^5 Cos[x]^11 + 69 (I Sin[x])^11 Cos[x]^5 + 146 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^2 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^2) + Exp[-7 I y] (494 (I Sin[x])^8 Cos[x]^8 + 107 (I Sin[x])^12 Cos[x]^4 + 107 (I Sin[x])^4 Cos[x]^12 + 325 (I Sin[x])^10 Cos[x]^6 + 325 (I Sin[x])^6 Cos[x]^10 + 424 (I Sin[x])^7 Cos[x]^9 + 424 (I Sin[x])^9 Cos[x]^7 + 204 (I Sin[x])^11 Cos[x]^5 + 204 (I Sin[x])^5 Cos[x]^11 + 42 (I Sin[x])^3 Cos[x]^13 + 42 (I Sin[x])^13 Cos[x]^3 + 14 (I Sin[x])^2 Cos[x]^14 + 14 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[-5 I y] (1031 (I Sin[x])^9 Cos[x]^7 + 1031 (I Sin[x])^7 Cos[x]^9 + 431 (I Sin[x])^11 Cos[x]^5 + 431 (I Sin[x])^5 Cos[x]^11 + 731 (I Sin[x])^10 Cos[x]^6 + 731 (I Sin[x])^6 Cos[x]^10 + 182 (I Sin[x])^4 Cos[x]^12 + 182 (I Sin[x])^12 Cos[x]^4 + 1138 (I Sin[x])^8 Cos[x]^8 + 49 (I Sin[x])^3 Cos[x]^13 + 49 (I Sin[x])^13 Cos[x]^3 + 9 (I Sin[x])^2 Cos[x]^14 + 9 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[-3 I y] (1618 (I Sin[x])^9 Cos[x]^7 + 1618 (I Sin[x])^7 Cos[x]^9 + 752 (I Sin[x])^11 Cos[x]^5 + 752 (I Sin[x])^5 Cos[x]^11 + 1716 (I Sin[x])^8 Cos[x]^8 + 1223 (I Sin[x])^10 Cos[x]^6 + 1223 (I Sin[x])^6 Cos[x]^10 + 143 (I Sin[x])^13 Cos[x]^3 + 143 (I Sin[x])^3 Cos[x]^13 + 368 (I Sin[x])^12 Cos[x]^4 + 368 (I Sin[x])^4 Cos[x]^12 + 35 (I Sin[x])^14 Cos[x]^2 + 35 (I Sin[x])^2 Cos[x]^14 + 7 (I Sin[x])^1 Cos[x]^15 + 7 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[-1 I y] (1587 (I Sin[x])^10 Cos[x]^6 + 1587 (I Sin[x])^6 Cos[x]^10 + 2712 (I Sin[x])^8 Cos[x]^8 + 2347 (I Sin[x])^9 Cos[x]^7 + 2347 (I Sin[x])^7 Cos[x]^9 + 781 (I Sin[x])^5 Cos[x]^11 + 781 (I Sin[x])^11 Cos[x]^5 + 280 (I Sin[x])^4 Cos[x]^12 + 280 (I Sin[x])^12 Cos[x]^4 + 71 (I Sin[x])^3 Cos[x]^13 + 71 (I Sin[x])^13 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^15 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^15) + Exp[1 I y] (2424 (I Sin[x])^8 Cos[x]^8 + 1563 (I Sin[x])^10 Cos[x]^6 + 1563 (I Sin[x])^6 Cos[x]^10 + 2135 (I Sin[x])^7 Cos[x]^9 + 2135 (I Sin[x])^9 Cos[x]^7 + 424 (I Sin[x])^12 Cos[x]^4 + 424 (I Sin[x])^4 Cos[x]^12 + 923 (I Sin[x])^11 Cos[x]^5 + 923 (I Sin[x])^5 Cos[x]^11 + 137 (I Sin[x])^13 Cos[x]^3 + 137 (I Sin[x])^3 Cos[x]^13 + 36 (I Sin[x])^2 Cos[x]^14 + 36 (I Sin[x])^14 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^15 + 5 (I Sin[x])^15 Cos[x]^1) + Exp[3 I y] (1928 (I Sin[x])^9 Cos[x]^7 + 1928 (I Sin[x])^7 Cos[x]^9 + 550 (I Sin[x])^5 Cos[x]^11 + 550 (I Sin[x])^11 Cos[x]^5 + 2194 (I Sin[x])^8 Cos[x]^8 + 178 (I Sin[x])^4 Cos[x]^12 + 178 (I Sin[x])^12 Cos[x]^4 + 1205 (I Sin[x])^6 Cos[x]^10 + 1205 (I Sin[x])^10 Cos[x]^6 + 42 (I Sin[x])^3 Cos[x]^13 + 42 (I Sin[x])^13 Cos[x]^3 + 5 (I Sin[x])^14 Cos[x]^2 + 5 (I Sin[x])^2 Cos[x]^14) + Exp[5 I y] (1037 (I Sin[x])^7 Cos[x]^9 + 1037 (I Sin[x])^9 Cos[x]^7 + 423 (I Sin[x])^11 Cos[x]^5 + 423 (I Sin[x])^5 Cos[x]^11 + 757 (I Sin[x])^6 Cos[x]^10 + 757 (I Sin[x])^10 Cos[x]^6 + 1114 (I Sin[x])^8 Cos[x]^8 + 170 (I Sin[x])^12 Cos[x]^4 + 170 (I Sin[x])^4 Cos[x]^12 + 52 (I Sin[x])^3 Cos[x]^13 + 52 (I Sin[x])^13 Cos[x]^3 + 7 (I Sin[x])^2 Cos[x]^14 + 7 (I Sin[x])^14 Cos[x]^2) + Exp[7 I y] (638 (I Sin[x])^8 Cos[x]^8 + 323 (I Sin[x])^10 Cos[x]^6 + 323 (I Sin[x])^6 Cos[x]^10 + 514 (I Sin[x])^7 Cos[x]^9 + 514 (I Sin[x])^9 Cos[x]^7 + 151 (I Sin[x])^5 Cos[x]^11 + 151 (I Sin[x])^11 Cos[x]^5 + 51 (I Sin[x])^4 Cos[x]^12 + 51 (I Sin[x])^12 Cos[x]^4 + 7 (I Sin[x])^13 Cos[x]^3 + 7 (I Sin[x])^3 Cos[x]^13) + Exp[9 I y] (109 (I Sin[x])^6 Cos[x]^10 + 109 (I Sin[x])^10 Cos[x]^6 + 210 (I Sin[x])^8 Cos[x]^8 + 174 (I Sin[x])^7 Cos[x]^9 + 174 (I Sin[x])^9 Cos[x]^7 + 48 (I Sin[x])^11 Cos[x]^5 + 48 (I Sin[x])^5 Cos[x]^11 + 17 (I Sin[x])^4 Cos[x]^12 + 17 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3) + Exp[11 I y] (40 (I Sin[x])^9 Cos[x]^7 + 40 (I Sin[x])^7 Cos[x]^9 + 16 (I Sin[x])^11 Cos[x]^5 + 16 (I Sin[x])^5 Cos[x]^11 + 32 (I Sin[x])^6 Cos[x]^10 + 32 (I Sin[x])^10 Cos[x]^6 + 30 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^4 Cos[x]^12) + Exp[13 I y] (1 (I Sin[x])^5 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^5 + 7 (I Sin[x])^9 Cos[x]^7 + 7 (I Sin[x])^7 Cos[x]^9 + 10 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^6) + Exp[15 I y] (1 (I Sin[x])^10 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^10))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^10 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^10) + Exp[-13 I y] (4 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^5 Cos[x]^11 + 2 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^4 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^4 + 4 (I Sin[x])^9 Cos[x]^7 + 4 (I Sin[x])^7 Cos[x]^9 + 6 (I Sin[x])^8 Cos[x]^8) + Exp[-11 I y] (39 (I Sin[x])^9 Cos[x]^7 + 39 (I Sin[x])^7 Cos[x]^9 + 15 (I Sin[x])^11 Cos[x]^5 + 15 (I Sin[x])^5 Cos[x]^11 + 38 (I Sin[x])^8 Cos[x]^8 + 24 (I Sin[x])^10 Cos[x]^6 + 24 (I Sin[x])^6 Cos[x]^10 + 6 (I Sin[x])^12 Cos[x]^4 + 6 (I Sin[x])^4 Cos[x]^12 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3) + Exp[-9 I y] (123 (I Sin[x])^10 Cos[x]^6 + 123 (I Sin[x])^6 Cos[x]^10 + 33 (I Sin[x])^4 Cos[x]^12 + 33 (I Sin[x])^12 Cos[x]^4 + 142 (I Sin[x])^9 Cos[x]^7 + 142 (I Sin[x])^7 Cos[x]^9 + 13 (I Sin[x])^3 Cos[x]^13 + 13 (I Sin[x])^13 Cos[x]^3 + 69 (I Sin[x])^5 Cos[x]^11 + 69 (I Sin[x])^11 Cos[x]^5 + 146 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^2 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^2) + Exp[-7 I y] (494 (I Sin[x])^8 Cos[x]^8 + 107 (I Sin[x])^12 Cos[x]^4 + 107 (I Sin[x])^4 Cos[x]^12 + 325 (I Sin[x])^10 Cos[x]^6 + 325 (I Sin[x])^6 Cos[x]^10 + 424 (I Sin[x])^7 Cos[x]^9 + 424 (I Sin[x])^9 Cos[x]^7 + 204 (I Sin[x])^11 Cos[x]^5 + 204 (I Sin[x])^5 Cos[x]^11 + 42 (I Sin[x])^3 Cos[x]^13 + 42 (I Sin[x])^13 Cos[x]^3 + 14 (I Sin[x])^2 Cos[x]^14 + 14 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[-5 I y] (1031 (I Sin[x])^9 Cos[x]^7 + 1031 (I Sin[x])^7 Cos[x]^9 + 431 (I Sin[x])^11 Cos[x]^5 + 431 (I Sin[x])^5 Cos[x]^11 + 731 (I Sin[x])^10 Cos[x]^6 + 731 (I Sin[x])^6 Cos[x]^10 + 182 (I Sin[x])^4 Cos[x]^12 + 182 (I Sin[x])^12 Cos[x]^4 + 1138 (I Sin[x])^8 Cos[x]^8 + 49 (I Sin[x])^3 Cos[x]^13 + 49 (I Sin[x])^13 Cos[x]^3 + 9 (I Sin[x])^2 Cos[x]^14 + 9 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[-3 I y] (1618 (I Sin[x])^9 Cos[x]^7 + 1618 (I Sin[x])^7 Cos[x]^9 + 752 (I Sin[x])^11 Cos[x]^5 + 752 (I Sin[x])^5 Cos[x]^11 + 1716 (I Sin[x])^8 Cos[x]^8 + 1223 (I Sin[x])^10 Cos[x]^6 + 1223 (I Sin[x])^6 Cos[x]^10 + 143 (I Sin[x])^13 Cos[x]^3 + 143 (I Sin[x])^3 Cos[x]^13 + 368 (I Sin[x])^12 Cos[x]^4 + 368 (I Sin[x])^4 Cos[x]^12 + 35 (I Sin[x])^14 Cos[x]^2 + 35 (I Sin[x])^2 Cos[x]^14 + 7 (I Sin[x])^1 Cos[x]^15 + 7 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[-1 I y] (1587 (I Sin[x])^10 Cos[x]^6 + 1587 (I Sin[x])^6 Cos[x]^10 + 2712 (I Sin[x])^8 Cos[x]^8 + 2347 (I Sin[x])^9 Cos[x]^7 + 2347 (I Sin[x])^7 Cos[x]^9 + 781 (I Sin[x])^5 Cos[x]^11 + 781 (I Sin[x])^11 Cos[x]^5 + 280 (I Sin[x])^4 Cos[x]^12 + 280 (I Sin[x])^12 Cos[x]^4 + 71 (I Sin[x])^3 Cos[x]^13 + 71 (I Sin[x])^13 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^15 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^15) + Exp[1 I y] (2424 (I Sin[x])^8 Cos[x]^8 + 1563 (I Sin[x])^10 Cos[x]^6 + 1563 (I Sin[x])^6 Cos[x]^10 + 2135 (I Sin[x])^7 Cos[x]^9 + 2135 (I Sin[x])^9 Cos[x]^7 + 424 (I Sin[x])^12 Cos[x]^4 + 424 (I Sin[x])^4 Cos[x]^12 + 923 (I Sin[x])^11 Cos[x]^5 + 923 (I Sin[x])^5 Cos[x]^11 + 137 (I Sin[x])^13 Cos[x]^3 + 137 (I Sin[x])^3 Cos[x]^13 + 36 (I Sin[x])^2 Cos[x]^14 + 36 (I Sin[x])^14 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^15 + 5 (I Sin[x])^15 Cos[x]^1) + Exp[3 I y] (1928 (I Sin[x])^9 Cos[x]^7 + 1928 (I Sin[x])^7 Cos[x]^9 + 550 (I Sin[x])^5 Cos[x]^11 + 550 (I Sin[x])^11 Cos[x]^5 + 2194 (I Sin[x])^8 Cos[x]^8 + 178 (I Sin[x])^4 Cos[x]^12 + 178 (I Sin[x])^12 Cos[x]^4 + 1205 (I Sin[x])^6 Cos[x]^10 + 1205 (I Sin[x])^10 Cos[x]^6 + 42 (I Sin[x])^3 Cos[x]^13 + 42 (I Sin[x])^13 Cos[x]^3 + 5 (I Sin[x])^14 Cos[x]^2 + 5 (I Sin[x])^2 Cos[x]^14) + Exp[5 I y] (1037 (I Sin[x])^7 Cos[x]^9 + 1037 (I Sin[x])^9 Cos[x]^7 + 423 (I Sin[x])^11 Cos[x]^5 + 423 (I Sin[x])^5 Cos[x]^11 + 757 (I Sin[x])^6 Cos[x]^10 + 757 (I Sin[x])^10 Cos[x]^6 + 1114 (I Sin[x])^8 Cos[x]^8 + 170 (I Sin[x])^12 Cos[x]^4 + 170 (I Sin[x])^4 Cos[x]^12 + 52 (I Sin[x])^3 Cos[x]^13 + 52 (I Sin[x])^13 Cos[x]^3 + 7 (I Sin[x])^2 Cos[x]^14 + 7 (I Sin[x])^14 Cos[x]^2) + Exp[7 I y] (638 (I Sin[x])^8 Cos[x]^8 + 323 (I Sin[x])^10 Cos[x]^6 + 323 (I Sin[x])^6 Cos[x]^10 + 514 (I Sin[x])^7 Cos[x]^9 + 514 (I Sin[x])^9 Cos[x]^7 + 151 (I Sin[x])^5 Cos[x]^11 + 151 (I Sin[x])^11 Cos[x]^5 + 51 (I Sin[x])^4 Cos[x]^12 + 51 (I Sin[x])^12 Cos[x]^4 + 7 (I Sin[x])^13 Cos[x]^3 + 7 (I Sin[x])^3 Cos[x]^13) + Exp[9 I y] (109 (I Sin[x])^6 Cos[x]^10 + 109 (I Sin[x])^10 Cos[x]^6 + 210 (I Sin[x])^8 Cos[x]^8 + 174 (I Sin[x])^7 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RowBox[{\"\\<\\\"year\\\"\\>\", \"\\[Rule]\", \"204\"}]}], \"\\[RightAssociation]\"}]}],\n \",\", \n RowBox[{\"\\<\\\"event-5227\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"\\[LeftAssociation]\", \n RowBox[{\n RowBox[{\"\\<\\\"j\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"107\"}]}], \",\", \n RowBox[{\"\\<\\\"m\\\"\\>\", \"\\[Rule]\", \"10\"}], \",\", \n RowBox[{\"\\<\\\"rel2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"low_to_the_south\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kusd20\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"Missing\", \"[\", \"\\<\\\"Unspecified\\\"\\>\", \"]\"}]}], \",\", \n RowBox[{\"\\<\\\"balanced\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"Missing\", \"[\", \"\\<\\\"Unspecified\\\"\\>\", \"]\"}]}], \",\", \n RowBox[{\"\\<\\\"kus\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"Missing\", \"[\", \"\\<\\\"Unspecified\\\"\\>\", \"]\"}]}], \",\", \n RowBox[{\"\\<\\\"obj2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"a_arietis\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kus2d24\\\"\\>\", \"\\[Rule]\", \"5.5`\"}], \",\", \n 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RowBox[{\"\\<\\\"year_filter_key\\\"\\>\", \"\\[Rule]\", \"204\"}], \",\", \n RowBox[{\"\\<\\\"table\\\"\\>\", \"\\[Rule]\", \"\\<\\\"pl107C\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"si\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"Missing\", \"[\", \"\\<\\\"Unspecified\\\"\\>\", \"]\"}]}], \",\", \n RowBox[{\"\\<\\\"sip\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"Missing\", \"[\", \"\\<\\\"Unspecified\\\"\\>\", \"]\"}]}], \",\", \n RowBox[{\"\\<\\\"sip2\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"Missing\", \"[\", \"\\<\\\"Unspecified\\\"\\>\", \"]\"}]}], \",\", \n RowBox[{\"\\<\\\"t\\\"\\>\", \"\\[Rule]\", \"14\"}], \",\", \n RowBox[{\"\\<\\\"type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"event\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year\\\"\\>\", \"\\[Rule]\", \"204\"}]}], \"\\[RightAssociation]\"}]}],\n \",\", \n RowBox[{\"\\<\\\"event-5229\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"\\[LeftAssociation]\", \n RowBox[{\n RowBox[{\"\\<\\\"j\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"107\"}]}], \",\", \n RowBox[{\"\\<\\\"m\\\"\\>\", \"\\[Rule]\", \"10\"}], \",\", \n RowBox[{\"\\<\\\"rel2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"low_to_the_south\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kusd20\\\"\\>\", \"\\[Rule]\", \"1.`\"}], \",\", \n RowBox[{\"\\<\\\"balanced\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"Missing\", \"[\", \"\\<\\\"Unspecified\\\"\\>\", \"]\"}]}], \",\", \n RowBox[{\"\\<\\\"kus\\\"\\>\", \"\\[Rule]\", \"1\"}], \",\", \n RowBox[{\"\\<\\\"obj2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"b_tauri\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kus2d24\\\"\\>\", \"\\[Rule]\", \"4.`\"}], \",\", \n RowBox[{\"\\<\\\"id\\\"\\>\", \"\\[Rule]\", \"5229\"}], \",\", \n RowBox[{\"\\<\\\"kusp2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"kus\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"day\\\"\\>\", \"\\[Rule]\", \"16\"}], \",\", \n RowBox[{\"\\<\\\"number\\\"\\>\", \"\\[Rule]\", \"5229\"}], \",\", \n RowBox[{\"\\<\\\"kus2\\\"\\>\", \"\\[Rule]\", \"4\"}], \",\", \n RowBox[{\"\\<\\\"shift\\\"\\>\", \"\\[Rule]\", \"\\<\\\"shift\\\"\\>\"}], 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RowBox[{\"\\<\\\"obj2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"e_geminorum\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kus2d24\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"Missing\", \"[\", \"\\<\\\"Unspecified\\\"\\>\", \"]\"}]}], \",\", \n RowBox[{\"\\<\\\"id\\\"\\>\", \"\\[Rule]\", \"5230\"}], \",\", \n RowBox[{\"\\<\\\"kusp2\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"Missing\", \"[\", \"\\<\\\"Unspecified\\\"\\>\", \"]\"}]}], \",\", \n RowBox[{\"\\<\\\"day\\\"\\>\", \"\\[Rule]\", \"17\"}], \",\", \n RowBox[{\"\\<\\\"number\\\"\\>\", \"\\[Rule]\", \"5230\"}], \",\", \n RowBox[{\"\\<\\\"kus2\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"Missing\", \"[\", \"\\<\\\"Unspecified\\\"\\>\", \"]\"}]}], \",\", \n RowBox[{\"\\<\\\"shift\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"Missing\", \"[\", \"\\<\\\"Unspecified\\\"\\>\", \"]\"}]}], \",\", \n RowBox[{\"\\<\\\"event-type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"king\\\"\\>\", \"\\[Rule]\", \"\\<\\\"seleucid_era\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"obj1\\\"\\>\", \"\\[Rule]\", \"\\<\\\"moon\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"mjd\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"717735\"}]}], \",\", \n RowBox[{\"\\<\\\"kusfrac2\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"Missing\", \"[\", \"\\<\\\"Unspecified\\\"\\>\", \"]\"}]}], \",\", \n RowBox[{\"\\<\\\"kusfrac\\\"\\>\", \"\\[Rule]\", \"\\<\\\"1 \/ 2\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kus2d20\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"Missing\", \"[\", \"\\<\\\"Unspecified\\\"\\>\", \"]\"}]}], \",\", \n RowBox[{\"\\<\\\"kusd24\\\"\\>\", \"\\[Rule]\", \"1.5`\"}], \",\", \n RowBox[{\"\\<\\\"time\\\"\\>\", \"\\[Rule]\", \"\\<\\\"last_part_of_night\\\"\\>\"}], \",\", \n \n RowBox[{\"\\<\\\"kusp\\\"\\>\", \"\\[Rule]\", \"\\<\\\"kus\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"type_filter_key\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}],\n \",\", \n RowBox[{\"\\<\\\"si2\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"Missing\", \"[\", \"\\<\\\"Unspecified\\\"\\>\", \"]\"}]}], 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RowBox[{\"\\<\\\"type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"event\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year\\\"\\>\", \"\\[Rule]\", \"204\"}]}], \"\\[RightAssociation]\"}]}],\n \",\", \n RowBox[{\"\\<\\\"event-5231\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"\\[LeftAssociation]\", \n RowBox[{\n RowBox[{\"\\<\\\"j\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"107\"}]}], \",\", \n RowBox[{\"\\<\\\"m\\\"\\>\", \"\\[Rule]\", \"10\"}], \",\", \n RowBox[{\"\\<\\\"rel2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"low_to_the_south\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kusd20\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"Missing\", \"[\", \"\\<\\\"Unspecified\\\"\\>\", \"]\"}]}], \",\", \n RowBox[{\"\\<\\\"balanced\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"Missing\", \"[\", \"\\<\\\"Unspecified\\\"\\>\", \"]\"}]}], \",\", \n RowBox[{\"\\<\\\"kus\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"Missing\", \"[\", \"\\<\\\"Unspecified\\\"\\>\", \"]\"}]}], \",\", \n RowBox[{\"\\<\\\"obj2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"a_geminorum\\\"\\>\"}], 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RowBox[{\"Missing\", \"[\", \"\\<\\\"Unspecified\\\"\\>\", \"]\"}]}], \",\", \n RowBox[{\"\\<\\\"month\\\"\\>\", \"\\[Rule]\", \"12\"}], \",\", \n RowBox[{\"\\<\\\"rel\\\"\\>\", \"\\[Rule]\", \"\\<\\\"below\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year_filter_key\\\"\\>\", \"\\[Rule]\", \"204\"}], \",\", \n RowBox[{\"\\<\\\"table\\\"\\>\", \"\\[Rule]\", \"\\<\\\"pl107C\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"si\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"Missing\", \"[\", \"\\<\\\"Unspecified\\\"\\>\", \"]\"}]}], \",\", \n RowBox[{\"\\<\\\"sip\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"Missing\", \"[\", \"\\<\\\"Unspecified\\\"\\>\", \"]\"}]}], \",\", \n RowBox[{\"\\<\\\"sip2\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"Missing\", \"[\", \"\\<\\\"Unspecified\\\"\\>\", \"]\"}]}], \",\", \n RowBox[{\"\\<\\\"t\\\"\\>\", \"\\[Rule]\", \"14\"}], \",\", \n RowBox[{\"\\<\\\"type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"event\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year\\\"\\>\", \"\\[Rule]\", \"204\"}]}], 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\"\\[Rule]\", \"4412\"}], \",\", \n RowBox[{\"\\<\\\"kusp2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"kus\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"day\\\"\\>\", \"\\[Rule]\", \"4\"}], \",\", \n RowBox[{\"\\<\\\"number\\\"\\>\", \"\\[Rule]\", \"4412\"}], \",\", \n RowBox[{\"\\<\\\"kus2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"shift\\\"\\>\", \"\\[Rule]\", \"\\<\\\"shift\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"event-type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"king\\\"\\>\", \"\\[Rule]\", \"\\<\\\"seleucid_era\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"obj1\\\"\\>\", \"\\[Rule]\", \"\\<\\\"moon\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"mjd\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"726903\"}]}], \",\", \n RowBox[{\"\\<\\\"kusfrac2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"1 \/ 2\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kusfrac\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kus2d20\\\"\\>\", \"\\[Rule]\", \"0.5`\"}], \",\", \n RowBox[{\"\\<\\\"kusd24\\\"\\>\", \"\\[Rule]\", \"1.`\"}], \",\", \n RowBox[{\"\\<\\\"time\\\"\\>\", \"\\[Rule]\", \"\\<\\\"beginning_of_night\\\"\\>\"}], \",\", \n \n RowBox[{\"\\<\\\"kusp\\\"\\>\", \"\\[Rule]\", \"\\<\\\"kus\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"type_filter_key\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}],\n \",\", \n RowBox[{\"\\<\\\"si2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"lfdnr\\\"\\>\", \"\\[Rule]\", \"5\"}], \",\", \n RowBox[{\"\\<\\\"torel\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"month\\\"\\>\", \"\\[Rule]\", \"6\"}], \",\", \n RowBox[{\"\\<\\\"rel\\\"\\>\", \"\\[Rule]\", \"\\<\\\"below\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year_filter_key\\\"\\>\", \"\\[Rule]\", \"179\"}], \",\", \n RowBox[{\"\\<\\\"table\\\"\\>\", \"\\[Rule]\", \"\\<\\\"pl132B\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"si\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"sip\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"sip2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"t\\\"\\>\", \"\\[Rule]\", \"10\"}], \",\", \n RowBox[{\"\\<\\\"type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"event\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year\\\"\\>\", \"\\[Rule]\", \"179\"}]}], \"\\[RightAssociation]\"}]}],\n \",\", \n RowBox[{\"\\<\\\"event-4413\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"\\[LeftAssociation]\", \n RowBox[{\n RowBox[{\"\\<\\\"j\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"132\"}]}], \",\", \n RowBox[{\"\\<\\\"m\\\"\\>\", \"\\[Rule]\", \"9\"}], \",\", \n RowBox[{\"\\<\\\"rel2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"low_to_the_south\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kusd20\\\"\\>\", \"\\[Rule]\", \"1.`\"}], \",\", \n RowBox[{\"\\<\\\"balanced\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kus\\\"\\>\", \"\\[Rule]\", \"1\"}], \",\", \n RowBox[{\"\\<\\\"obj2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"th_ophiuchi\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kus2d24\\\"\\>\", \"\\[Rule]\", \"2.`\"}], \",\", \n RowBox[{\"\\<\\\"id\\\"\\>\", \"\\[Rule]\", \"4413\"}], \",\", \n RowBox[{\"\\<\\\"kusp2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"kus\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"day\\\"\\>\", \"\\[Rule]\", \"5\"}], \",\", \n RowBox[{\"\\<\\\"number\\\"\\>\", \"\\[Rule]\", \"4413\"}], \",\", \n RowBox[{\"\\<\\\"kus2\\\"\\>\", \"\\[Rule]\", \"2\"}], \",\", \n RowBox[{\"\\<\\\"shift\\\"\\>\", \"\\[Rule]\", \"\\<\\\"shift\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"event-type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"king\\\"\\>\", \"\\[Rule]\", \"\\<\\\"seleucid_era\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"obj1\\\"\\>\", \"\\[Rule]\", \"\\<\\\"moon\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"mjd\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"726902\"}]}], \",\", \n RowBox[{\"\\<\\\"kusfrac2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusfrac\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kus2d20\\\"\\>\", \"\\[Rule]\", \"2.`\"}], \",\", \n RowBox[{\"\\<\\\"kusd24\\\"\\>\", \"\\[Rule]\", \"1.`\"}], \",\", \n RowBox[{\"\\<\\\"time\\\"\\>\", \"\\[Rule]\", \"\\<\\\"beginning_of_night\\\"\\>\"}], \",\", \n \n RowBox[{\"\\<\\\"kusp\\\"\\>\", \"\\[Rule]\", \"\\<\\\"kus\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"type_filter_key\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}],\n \",\", \n RowBox[{\"\\<\\\"si2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"lfdnr\\\"\\>\", \"\\[Rule]\", \"6\"}], \",\", \n RowBox[{\"\\<\\\"torel\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"month\\\"\\>\", \"\\[Rule]\", \"6\"}], \",\", \n RowBox[{\"\\<\\\"rel\\\"\\>\", \"\\[Rule]\", \"\\<\\\"behind\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year_filter_key\\\"\\>\", \"\\[Rule]\", \"179\"}], \",\", \n RowBox[{\"\\<\\\"table\\\"\\>\", \"\\[Rule]\", \"\\<\\\"pl132B\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"si\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"sip\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"sip2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"t\\\"\\>\", \"\\[Rule]\", \"11\"}], \",\", \n RowBox[{\"\\<\\\"type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"event\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year\\\"\\>\", \"\\[Rule]\", \"179\"}]}], \"\\[RightAssociation]\"}]}],\n \",\", \n RowBox[{\"\\<\\\"event-4414\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"\\[LeftAssociation]\", \n RowBox[{\n RowBox[{\"\\<\\\"j\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"132\"}]}], \",\", \n RowBox[{\"\\<\\\"m\\\"\\>\", \"\\[Rule]\", \"9\"}], \",\", \n RowBox[{\"\\<\\\"rel2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusd20\\\"\\>\", \"\\[Rule]\", \"2.5`\"}], \",\", \n RowBox[{\"\\<\\\"balanced\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kus\\\"\\>\", \"\\[Rule]\", \"2\"}], \",\", \n RowBox[{\"\\<\\\"obj2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"saturn\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kus2d24\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"id\\\"\\>\", \"\\[Rule]\", \"4414\"}], \",\", \n RowBox[{\"\\<\\\"kusp2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"day\\\"\\>\", \"\\[Rule]\", \"6\"}], \",\", \n RowBox[{\"\\<\\\"number\\\"\\>\", \"\\[Rule]\", \"4414\"}], \",\", \n RowBox[{\"\\<\\\"kus2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"shift\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"event-type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"king\\\"\\>\", \"\\[Rule]\", \"\\<\\\"seleucid_era\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"obj1\\\"\\>\", \"\\[Rule]\", \"\\<\\\"moon\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"mjd\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"726901\"}]}], \",\", \n RowBox[{\"\\<\\\"kusfrac2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusfrac\\\"\\>\", \"\\[Rule]\", \"\\<\\\"1 \/ 2\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kus2d20\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusd24\\\"\\>\", \"\\[Rule]\", \"2.5`\"}], \",\", \n RowBox[{\"\\<\\\"time\\\"\\>\", \"\\[Rule]\", \"\\<\\\"beginning_of_night\\\"\\>\"}], \",\", \n \n RowBox[{\"\\<\\\"kusp\\\"\\>\", \"\\[Rule]\", \"\\<\\\"kus\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"type_filter_key\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}],\n \",\", \n RowBox[{\"\\<\\\"si2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"lfdnr\\\"\\>\", \"\\[Rule]\", \"7\"}], \",\", \n RowBox[{\"\\<\\\"torel\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"month\\\"\\>\", \"\\[Rule]\", \"6\"}], \",\", \n RowBox[{\"\\<\\\"rel\\\"\\>\", \"\\[Rule]\", \"\\<\\\"below\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year_filter_key\\\"\\>\", \"\\[Rule]\", \"179\"}], \",\", \n RowBox[{\"\\<\\\"table\\\"\\>\", \"\\[Rule]\", \"\\<\\\"pl132B\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"si\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"sip\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"sip2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"t\\\"\\>\", \"\\[Rule]\", \"12\"}], \",\", \n RowBox[{\"\\<\\\"type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"event\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year\\\"\\>\", \"\\[Rule]\", \"179\"}]}], \"\\[RightAssociation]\"}]}],\n \",\", \n RowBox[{\"\\<\\\"event-4415\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"\\[LeftAssociation]\", \n RowBox[{\n RowBox[{\"\\<\\\"j\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"132\"}]}], \",\", \n RowBox[{\"\\<\\\"m\\\"\\>\", \"\\[Rule]\", \"9\"}], \",\", \n RowBox[{\"\\<\\\"rel2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusd20\\\"\\>\", \"\\[Rule]\", \"0.05`\"}], \",\", \n RowBox[{\"\\<\\\"balanced\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kus\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"obj2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"th_ophiuchi\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kus2d24\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"id\\\"\\>\", \"\\[Rule]\", \"4415\"}], \",\", \n RowBox[{\"\\<\\\"kusp2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"day\\\"\\>\", \"\\[Rule]\", \"7\"}], \",\", \n RowBox[{\"\\<\\\"number\\\"\\>\", \"\\[Rule]\", \"4415\"}], \",\", \n RowBox[{\"\\<\\\"kus2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"shift\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"event-type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"king\\\"\\>\", \"\\[Rule]\", \"\\<\\\"seleucid_era\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"obj1\\\"\\>\", \"\\[Rule]\", \"\\<\\\"mars\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"mjd\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"726900\"}]}], \",\", \n RowBox[{\"\\<\\\"kusfrac2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusfrac\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kus2d20\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusd24\\\"\\>\", \"\\[Rule]\", \"0.041667`\"}], \",\", \n RowBox[{\"\\<\\\"time\\\"\\>\", \"\\[Rule]\", \"\\<\\\"first_part_of_night\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kusp\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"type_filter_key\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}],\n \",\", \n RowBox[{\"\\<\\\"si2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"lfdnr\\\"\\>\", \"\\[Rule]\", \"8\"}], \",\", \n RowBox[{\"\\<\\\"torel\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"month\\\"\\>\", \"\\[Rule]\", \"6\"}], \",\", \n RowBox[{\"\\<\\\"rel\\\"\\>\", \"\\[Rule]\", \"\\<\\\"above\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year_filter_key\\\"\\>\", \"\\[Rule]\", \"179\"}], \",\", \n RowBox[{\"\\<\\\"table\\\"\\>\", \"\\[Rule]\", \"\\<\\\"pl132B\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"si\\\"\\>\", \"\\[Rule]\", \"1\"}], \",\", \n RowBox[{\"\\<\\\"sip\\\"\\>\", \"\\[Rule]\", \"\\<\\\"si\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"sip2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"t\\\"\\>\", \"\\[Rule]\", \"13\"}], \",\", \n RowBox[{\"\\<\\\"type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"event\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year\\\"\\>\", \"\\[Rule]\", \"179\"}]}], \"\\[RightAssociation]\"}]}],\n \",\", \n RowBox[{\"\\<\\\"event-4416\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"\\[LeftAssociation]\", \n RowBox[{\n RowBox[{\"\\<\\\"j\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"132\"}]}], \",\", \n RowBox[{\"\\<\\\"m\\\"\\>\", \"\\[Rule]\", \"9\"}], \",\", \n RowBox[{\"\\<\\\"rel2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"low_to_the_south\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kusd20\\\"\\>\", \"\\[Rule]\", \"1.5`\"}], \",\", \n RowBox[{\"\\<\\\"balanced\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kus\\\"\\>\", \"\\[Rule]\", \"1\"}], \",\", \n RowBox[{\"\\<\\\"obj2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"b_capricorni\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kus2d24\\\"\\>\", \"\\[Rule]\", \"3.5`\"}], \",\", \n RowBox[{\"\\<\\\"id\\\"\\>\", \"\\[Rule]\", \"4416\"}], \",\", \n RowBox[{\"\\<\\\"kusp2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"kus\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"day\\\"\\>\", \"\\[Rule]\", \"8\"}], \",\", \n RowBox[{\"\\<\\\"number\\\"\\>\", \"\\[Rule]\", \"4416\"}], \",\", \n RowBox[{\"\\<\\\"kus2\\\"\\>\", \"\\[Rule]\", \"3\"}], \",\", \n RowBox[{\"\\<\\\"shift\\\"\\>\", \"\\[Rule]\", \"\\<\\\"shift\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"event-type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"king\\\"\\>\", \"\\[Rule]\", \"\\<\\\"seleucid_era\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"obj1\\\"\\>\", \"\\[Rule]\", \"\\<\\\"moon\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"mjd\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"726899\"}]}], \",\", \n RowBox[{\"\\<\\\"kusfrac2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"1 \/ 2\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kusfrac\\\"\\>\", \"\\[Rule]\", 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RowBox[{\"\\<\\\"year_filter_key\\\"\\>\", \"\\[Rule]\", \"179\"}], \",\", \n RowBox[{\"\\<\\\"table\\\"\\>\", \"\\[Rule]\", \"\\<\\\"pl132B\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"si\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"sip\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"sip2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"t\\\"\\>\", \"\\[Rule]\", \"21\"}], \",\", \n RowBox[{\"\\<\\\"type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"event\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year\\\"\\>\", \"\\[Rule]\", \"179\"}]}], \"\\[RightAssociation]\"}]}],\n \",\", \n RowBox[{\"\\<\\\"event-4424\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"\\[LeftAssociation]\", \n RowBox[{\n RowBox[{\"\\<\\\"j\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"132\"}]}], \",\", \n RowBox[{\"\\<\\\"m\\\"\\>\", \"\\[Rule]\", \"9\"}], \",\", \n RowBox[{\"\\<\\\"rel2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"low_to_the_south\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kusd20\\\"\\>\", \"\\[Rule]\", 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RowBox[{\"\\<\\\"sip\\\"\\>\", \"\\[Rule]\", \"\\<\\\"si\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"sip2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"t\\\"\\>\", \"\\[Rule]\", \"13\"}], \",\", \n RowBox[{\"\\<\\\"type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"event\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year\\\"\\>\", \"\\[Rule]\", \"179\"}]}], \"\\[RightAssociation]\"}]}],\n \",\", \n RowBox[{\"\\<\\\"event-4448\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"\\[LeftAssociation]\", \n RowBox[{\n RowBox[{\"\\<\\\"j\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"132\"}]}], \",\", \n RowBox[{\"\\<\\\"m\\\"\\>\", \"\\[Rule]\", \"10\"}], \",\", \n RowBox[{\"\\<\\\"rel2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"passed_to_the_east\\\"\\>\"}], \",\", \n \n RowBox[{\"\\<\\\"kusd20\\\"\\>\", \"\\[Rule]\", \"0.5`\"}], \",\", \n RowBox[{\"\\<\\\"balanced\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kus\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"obj2\\\"\\>\", \"\\[Rule]\", 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RowBox[{\"\\<\\\"kusfrac\\\"\\>\", \"\\[Rule]\", \"\\<\\\"1 \/ 2\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kus2d20\\\"\\>\", \"\\[Rule]\", \"0.2`\"}], \",\", \n RowBox[{\"\\<\\\"kusd24\\\"\\>\", \"\\[Rule]\", \"0.5`\"}], \",\", \n RowBox[{\"\\<\\\"time\\\"\\>\", \"\\[Rule]\", \"\\<\\\"last_part_of_night\\\"\\>\"}], \",\", \n \n RowBox[{\"\\<\\\"kusp\\\"\\>\", \"\\[Rule]\", \"\\<\\\"kus\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"type_filter_key\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}],\n \",\", \n RowBox[{\"\\<\\\"si2\\\"\\>\", \"\\[Rule]\", \"4\"}], \",\", \n RowBox[{\"\\<\\\"lfdnr\\\"\\>\", \"\\[Rule]\", \"43\"}], \",\", \n RowBox[{\"\\<\\\"torel\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"month\\\"\\>\", \"\\[Rule]\", \"7\"}], \",\", \n RowBox[{\"\\<\\\"rel\\\"\\>\", \"\\[Rule]\", \"\\<\\\"below\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year_filter_key\\\"\\>\", \"\\[Rule]\", \"179\"}], \",\", \n RowBox[{\"\\<\\\"table\\\"\\>\", \"\\[Rule]\", 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\"\\[Rule]\", \"2\"}], \",\", \n RowBox[{\"\\<\\\"obj2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"electra\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kus2d24\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"id\\\"\\>\", \"\\[Rule]\", \"4449\"}], \",\", \n RowBox[{\"\\<\\\"kusp2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"day\\\"\\>\", \"\\[Rule]\", \"15\"}], \",\", \n RowBox[{\"\\<\\\"number\\\"\\>\", \"\\[Rule]\", \"4449\"}], \",\", \n RowBox[{\"\\<\\\"kus2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"shift\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"event-type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"king\\\"\\>\", \"\\[Rule]\", \"\\<\\\"seleucid_era\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"obj1\\\"\\>\", \"\\[Rule]\", \"\\<\\\"moon\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"mjd\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"726862\"}]}], \",\", \n RowBox[{\"\\<\\\"kusfrac2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusfrac\\\"\\>\", \"\\[Rule]\", \"\\<\\\"1 \/ 2\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kus2d20\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusd24\\\"\\>\", \"\\[Rule]\", \"2.5`\"}], \",\", \n RowBox[{\"\\<\\\"time\\\"\\>\", \"\\[Rule]\", \"\\<\\\"last_part_of_night\\\"\\>\"}], \",\", \n \n RowBox[{\"\\<\\\"kusp\\\"\\>\", \"\\[Rule]\", \"\\<\\\"kus\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"type_filter_key\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}],\n \",\", \n RowBox[{\"\\<\\\"si2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"lfdnr\\\"\\>\", \"\\[Rule]\", \"44\"}], \",\", \n RowBox[{\"\\<\\\"torel\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"month\\\"\\>\", \"\\[Rule]\", \"7\"}], \",\", \n RowBox[{\"\\<\\\"rel\\\"\\>\", \"\\[Rule]\", \"\\<\\\"behind\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year_filter_key\\\"\\>\", \"\\[Rule]\", \"179\"}], \",\", \n RowBox[{\"\\<\\\"table\\\"\\>\", \"\\[Rule]\", \"\\<\\\"pl132B\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"si\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"sip\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"sip2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"t\\\"\\>\", \"\\[Rule]\", \"21\"}], \",\", \n RowBox[{\"\\<\\\"type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"event\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year\\\"\\>\", \"\\[Rule]\", \"179\"}]}], \"\\[RightAssociation]\"}]}],\n \",\", \n RowBox[{\"\\<\\\"event-4451\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"\\[LeftAssociation]\", \n RowBox[{\n RowBox[{\"\\<\\\"j\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"132\"}]}], \",\", \n RowBox[{\"\\<\\\"m\\\"\\>\", \"\\[Rule]\", \"10\"}], \",\", \n RowBox[{\"\\<\\\"rel2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusd20\\\"\\>\", \"\\[Rule]\", \"1.5`\"}], \",\", \n RowBox[{\"\\<\\\"balanced\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kus\\\"\\>\", \"\\[Rule]\", \"1\"}], \",\", \n RowBox[{\"\\<\\\"obj2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"b_tauri\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kus2d24\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"id\\\"\\>\", \"\\[Rule]\", \"4451\"}], \",\", \n RowBox[{\"\\<\\\"kusp2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"day\\\"\\>\", \"\\[Rule]\", \"16\"}], \",\", \n RowBox[{\"\\<\\\"number\\\"\\>\", \"\\[Rule]\", \"4451\"}], \",\", \n RowBox[{\"\\<\\\"kus2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"shift\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"event-type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"king\\\"\\>\", \"\\[Rule]\", \"\\<\\\"seleucid_era\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"obj1\\\"\\>\", \"\\[Rule]\", \"\\<\\\"moon\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"mjd\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"726861\"}]}], \",\", \n RowBox[{\"\\<\\\"kusfrac2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusfrac\\\"\\>\", \"\\[Rule]\", \"\\<\\\"1 \/ 2\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kus2d20\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusd24\\\"\\>\", \"\\[Rule]\", \"1.5`\"}], \",\", \n RowBox[{\"\\<\\\"time\\\"\\>\", \"\\[Rule]\", \"\\<\\\"last_part_of_night\\\"\\>\"}], \",\", \n \n RowBox[{\"\\<\\\"kusp\\\"\\>\", \"\\[Rule]\", \"\\<\\\"kus\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"type_filter_key\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}],\n \",\", \n RowBox[{\"\\<\\\"si2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"lfdnr\\\"\\>\", \"\\[Rule]\", \"46\"}], \",\", \n RowBox[{\"\\<\\\"torel\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"month\\\"\\>\", \"\\[Rule]\", \"7\"}], \",\", \n RowBox[{\"\\<\\\"rel\\\"\\>\", \"\\[Rule]\", \"\\<\\\"in_front_of\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year_filter_key\\\"\\>\", \"\\[Rule]\", \"179\"}], \",\", \n RowBox[{\"\\<\\\"table\\\"\\>\", \"\\[Rule]\", \"\\<\\\"pl132B\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"si\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"sip\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"sip2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"t\\\"\\>\", \"\\[Rule]\", \"22\"}], \",\", \n RowBox[{\"\\<\\\"type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"event\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year\\\"\\>\", \"\\[Rule]\", \"179\"}]}], \"\\[RightAssociation]\"}]}],\n \",\", \n RowBox[{\"\\<\\\"event-4452\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"\\[LeftAssociation]\", \n RowBox[{\n RowBox[{\"\\<\\\"j\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"132\"}]}], \",\", \n RowBox[{\"\\<\\\"m\\\"\\>\", \"\\[Rule]\", \"10\"}], \",\", \n RowBox[{\"\\<\\\"rel2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"back_to_the_west\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kusd20\\\"\\>\", \"\\[Rule]\", \"2.5`\"}], \",\", \n RowBox[{\"\\<\\\"balanced\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kus\\\"\\>\", \"\\[Rule]\", \"2\"}], \",\", \n RowBox[{\"\\<\\\"obj2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"e_geminorum\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kus2d24\\\"\\>\", \"\\[Rule]\", \"0.5`\"}], \",\", \n RowBox[{\"\\<\\\"id\\\"\\>\", \"\\[Rule]\", \"4452\"}], \",\", \n RowBox[{\"\\<\\\"kusp2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"kus\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"day\\\"\\>\", \"\\[Rule]\", \"17\"}], \",\", \n RowBox[{\"\\<\\\"number\\\"\\>\", \"\\[Rule]\", \"4452\"}], \",\", \n RowBox[{\"\\<\\\"kus2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"shift\\\"\\>\", \"\\[Rule]\", \"\\<\\\"shift\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"event-type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"king\\\"\\>\", \"\\[Rule]\", \"\\<\\\"seleucid_era\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"obj1\\\"\\>\", \"\\[Rule]\", \"\\<\\\"moon\\\"\\>\"}], \",\", \n 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RowBox[{\"\\<\\\"lfdnr\\\"\\>\", \"\\[Rule]\", \"52\"}], \",\", \n RowBox[{\"\\<\\\"torel\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"month\\\"\\>\", \"\\[Rule]\", \"7\"}], \",\", \n RowBox[{\"\\<\\\"rel\\\"\\>\", \"\\[Rule]\", \"\\<\\\"below\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year_filter_key\\\"\\>\", \"\\[Rule]\", \"179\"}], \",\", \n RowBox[{\"\\<\\\"table\\\"\\>\", \"\\[Rule]\", \"\\<\\\"pl132B\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"si\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"sip\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"sip2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"t\\\"\\>\", \"\\[Rule]\", \"28\"}], \",\", \n RowBox[{\"\\<\\\"type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"event\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year\\\"\\>\", \"\\[Rule]\", \"179\"}]}], \"\\[RightAssociation]\"}]}],\n \",\", \n RowBox[{\"\\<\\\"event-4458\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"\\[LeftAssociation]\", \n RowBox[{\n RowBox[{\"\\<\\\"j\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"132\"}]}], \",\", \n RowBox[{\"\\<\\\"m\\\"\\>\", \"\\[Rule]\", \"10\"}], \",\", \n RowBox[{\"\\<\\\"rel2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusd20\\\"\\>\", \"\\[Rule]\", \"2.3`\"}], \",\", \n RowBox[{\"\\<\\\"balanced\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kus\\\"\\>\", \"\\[Rule]\", \"2\"}], \",\", \n RowBox[{\"\\<\\\"obj2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"jupiter\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kus2d24\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"id\\\"\\>\", \"\\[Rule]\", \"4458\"}], \",\", \n RowBox[{\"\\<\\\"kusp2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"day\\\"\\>\", \"\\[Rule]\", \"22\"}], \",\", \n RowBox[{\"\\<\\\"number\\\"\\>\", \"\\[Rule]\", \"4458\"}], \",\", \n RowBox[{\"\\<\\\"kus2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"shift\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"event-type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"king\\\"\\>\", \"\\[Rule]\", \"\\<\\\"seleucid_era\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"obj1\\\"\\>\", \"\\[Rule]\", \"\\<\\\"moon\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"mjd\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"726855\"}]}], \",\", \n RowBox[{\"\\<\\\"kusfrac2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusfrac\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kus2d20\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusd24\\\"\\>\", \"\\[Rule]\", \"2.25`\"}], \",\", \n RowBox[{\"\\<\\\"time\\\"\\>\", \"\\[Rule]\", \"\\<\\\"last_part_of_night\\\"\\>\"}], \",\", \n \n RowBox[{\"\\<\\\"kusp\\\"\\>\", \"\\[Rule]\", \"\\<\\\"kus\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"type_filter_key\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}],\n \",\", \n RowBox[{\"\\<\\\"si2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"lfdnr\\\"\\>\", \"\\[Rule]\", \"53\"}], \",\", \n RowBox[{\"\\<\\\"torel\\\"\\>\", \"\\[Rule]\", \"\\<\\\"to_the_west\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"month\\\"\\>\", \"\\[Rule]\", \"7\"}], \",\", \n RowBox[{\"\\<\\\"rel\\\"\\>\", \"\\[Rule]\", \"\\<\\\"in_front_of\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year_filter_key\\\"\\>\", \"\\[Rule]\", \"179\"}], \",\", \n RowBox[{\"\\<\\\"table\\\"\\>\", \"\\[Rule]\", \"\\<\\\"pl132B\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"si\\\"\\>\", \"\\[Rule]\", \"6\"}], \",\", \n RowBox[{\"\\<\\\"sip\\\"\\>\", \"\\[Rule]\", \"\\<\\\"si\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"sip2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"t\\\"\\>\", \"\\[Rule]\", \"28\"}], \",\", \n RowBox[{\"\\<\\\"type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"event\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year\\\"\\>\", \"\\[Rule]\", \"179\"}]}], \"\\[RightAssociation]\"}]}],\n \",\", \n RowBox[{\"\\<\\\"event-4459\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"\\[LeftAssociation]\", \n RowBox[{\n RowBox[{\"\\<\\\"j\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"132\"}]}], \",\", \n RowBox[{\"\\<\\\"m\\\"\\>\", \"\\[Rule]\", \"10\"}], \",\", \n RowBox[{\"\\<\\\"rel2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusd20\\\"\\>\", \"\\[Rule]\", \"2.`\"}], \",\", \n RowBox[{\"\\<\\\"balanced\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kus\\\"\\>\", \"\\[Rule]\", \"2\"}], \",\", \n RowBox[{\"\\<\\\"obj2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"b_virginis\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kus2d24\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"id\\\"\\>\", \"\\[Rule]\", \"4459\"}], \",\", \n RowBox[{\"\\<\\\"kusp2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"day\\\"\\>\", \"\\[Rule]\", \"23\"}], \",\", \n RowBox[{\"\\<\\\"number\\\"\\>\", \"\\[Rule]\", \"4459\"}], \",\", \n RowBox[{\"\\<\\\"kus2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"shift\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"event-type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"king\\\"\\>\", \"\\[Rule]\", \"\\<\\\"seleucid_era\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"obj1\\\"\\>\", \"\\[Rule]\", \"\\<\\\"moon\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"mjd\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"726854\"}]}], \",\", \n RowBox[{\"\\<\\\"kusfrac2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusfrac\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kus2d20\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusd24\\\"\\>\", \"\\[Rule]\", \"2.`\"}], \",\", \n RowBox[{\"\\<\\\"time\\\"\\>\", \"\\[Rule]\", \"\\<\\\"last_part_of_night\\\"\\>\"}], \",\", \n \n RowBox[{\"\\<\\\"kusp\\\"\\>\", \"\\[Rule]\", \"\\<\\\"kus\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"type_filter_key\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}],\n \",\", \n RowBox[{\"\\<\\\"si2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"lfdnr\\\"\\>\", \"\\[Rule]\", \"54\"}], \",\", \n RowBox[{\"\\<\\\"torel\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"month\\\"\\>\", \"\\[Rule]\", \"7\"}], \",\", \n RowBox[{\"\\<\\\"rel\\\"\\>\", \"\\[Rule]\", \"\\<\\\"behind\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year_filter_key\\\"\\>\", \"\\[Rule]\", \"179\"}], \",\", \n RowBox[{\"\\<\\\"table\\\"\\>\", \"\\[Rule]\", \"\\<\\\"pl132B\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"si\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"sip\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"sip2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"t\\\"\\>\", \"\\[Rule]\", \"29\"}], \",\", \n RowBox[{\"\\<\\\"type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"event\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year\\\"\\>\", \"\\[Rule]\", \"179\"}]}], \"\\[RightAssociation]\"}]}],\n \",\", \n RowBox[{\"\\<\\\"event-4460\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"\\[LeftAssociation]\", \n RowBox[{\n RowBox[{\"\\<\\\"j\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"132\"}]}], \",\", \n RowBox[{\"\\<\\\"m\\\"\\>\", \"\\[Rule]\", \"11\"}], \",\", \n RowBox[{\"\\<\\\"rel2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusd20\\\"\\>\", \"\\[Rule]\", \"1.5`\"}], \",\", \n RowBox[{\"\\<\\\"balanced\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kus\\\"\\>\", \"\\[Rule]\", \"1\"}], \",\", \n RowBox[{\"\\<\\\"obj2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"a_virginis\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kus2d24\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"id\\\"\\>\", \"\\[Rule]\", \"4460\"}], \",\", \n RowBox[{\"\\<\\\"kusp2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"day\\\"\\>\", \"\\[Rule]\", \"26\"}], \",\", \n RowBox[{\"\\<\\\"number\\\"\\>\", \"\\[Rule]\", \"4460\"}], \",\", \n RowBox[{\"\\<\\\"kus2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"shift\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"event-type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"king\\\"\\>\", \"\\[Rule]\", \"\\<\\\"seleucid_era\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"obj1\\\"\\>\", \"\\[Rule]\", \"\\<\\\"venus\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"mjd\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"726851\"}]}], \",\", \n RowBox[{\"\\<\\\"kusfrac2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusfrac\\\"\\>\", \"\\[Rule]\", \"\\<\\\"1 \/ 2\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kus2d20\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusd24\\\"\\>\", \"\\[Rule]\", \"1.5`\"}], \",\", \n RowBox[{\"\\<\\\"time\\\"\\>\", \"\\[Rule]\", \"\\<\\\"last_part_of_night\\\"\\>\"}], \",\", \n \n RowBox[{\"\\<\\\"kusp\\\"\\>\", \"\\[Rule]\", \"\\<\\\"kus\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"type_filter_key\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}],\n \",\", \n RowBox[{\"\\<\\\"si2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"lfdnr\\\"\\>\", \"\\[Rule]\", \"55\"}], \",\", \n RowBox[{\"\\<\\\"torel\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"month\\\"\\>\", \"\\[Rule]\", \"7\"}], \",\", \n RowBox[{\"\\<\\\"rel\\\"\\>\", \"\\[Rule]\", \"\\<\\\"above\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year_filter_key\\\"\\>\", \"\\[Rule]\", \"179\"}], \",\", \n RowBox[{\"\\<\\\"table\\\"\\>\", \"\\[Rule]\", \"\\<\\\"pl132B\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"si\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"sip\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"sip2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"t\\\"\\>\", \"\\[Rule]\", \"1\"}], \",\", \n RowBox[{\"\\<\\\"type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"event\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year\\\"\\>\", \"\\[Rule]\", \"179\"}]}], \"\\[RightAssociation]\"}]}],\n \",\", \n RowBox[{\"\\<\\\"event-4461\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"\\[LeftAssociation]\", \n RowBox[{\n RowBox[{\"\\<\\\"j\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"132\"}]}], \",\", \n RowBox[{\"\\<\\\"m\\\"\\>\", \"\\[Rule]\", \"11\"}], \",\", \n RowBox[{\"\\<\\\"rel2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusd20\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"balanced\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kus\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"obj2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"leo\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kus2d24\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"id\\\"\\>\", \"\\[Rule]\", \"4461\"}], \",\", \n RowBox[{\"\\<\\\"kusp2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"day\\\"\\>\", \"\\[Rule]\", \"26\"}], \",\", \n RowBox[{\"\\<\\\"number\\\"\\>\", \"\\[Rule]\", \"4461\"}], \",\", \n RowBox[{\"\\<\\\"kus2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"shift\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"event-type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"king\\\"\\>\", \"\\[Rule]\", \"\\<\\\"seleucid_era\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"obj1\\\"\\>\", \"\\[Rule]\", \"\\<\\\"venus\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"mjd\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"726851\"}]}], \",\", \n RowBox[{\"\\<\\\"kusfrac2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusfrac\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kus2d20\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusd24\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"time\\\"\\>\", \"\\[Rule]\", \"\\<\\\"middle_part_of_night\\\"\\>\"}], \n \",\", \n RowBox[{\"\\<\\\"kusp\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"type_filter_key\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}],\n \",\", \n RowBox[{\"\\<\\\"si2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"lfdnr\\\"\\>\", \"\\[Rule]\", \"56\"}], \",\", \n RowBox[{\"\\<\\\"torel\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"month\\\"\\>\", \"\\[Rule]\", \"7\"}], \",\", \n RowBox[{\"\\<\\\"rel\\\"\\>\", \"\\[Rule]\", \"\\<\\\"is_standing_in\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year_filter_key\\\"\\>\", \"\\[Rule]\", \"179\"}], \",\", \n RowBox[{\"\\<\\\"table\\\"\\>\", \"\\[Rule]\", \"\\<\\\"pl132B\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"si\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"sip\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"sip2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"t\\\"\\>\", \"\\[Rule]\", \"1\"}], \",\", \n RowBox[{\"\\<\\\"type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"event\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"year\\\"\\>\", \"\\[Rule]\", \"179\"}]}], \"\\[RightAssociation]\"}]}],\n \",\", \n RowBox[{\"\\<\\\"event-4462\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"\\[LeftAssociation]\", \n RowBox[{\n RowBox[{\"\\<\\\"j\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"132\"}]}], \",\", \n RowBox[{\"\\<\\\"m\\\"\\>\", \"\\[Rule]\", \"11\"}], \",\", \n RowBox[{\"\\<\\\"rel2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusd20\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"balanced\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kus\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"obj2\\\"\\>\", \"\\[Rule]\", \"\\<\\\"sagittarius\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"kus2d24\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"id\\\"\\>\", \"\\[Rule]\", \"4462\"}], \",\", \n RowBox[{\"\\<\\\"kusp2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"day\\\"\\>\", \"\\[Rule]\", \"26\"}], \",\", \n RowBox[{\"\\<\\\"number\\\"\\>\", \"\\[Rule]\", \"4462\"}], \",\", \n RowBox[{\"\\<\\\"kus2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"shift\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"event-type\\\"\\>\", \"\\[Rule]\", \"\\<\\\"configuration\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"king\\\"\\>\", \"\\[Rule]\", \"\\<\\\"seleucid_era\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"obj1\\\"\\>\", \"\\[Rule]\", \"\\<\\\"mars\\\"\\>\"}], \",\", \n RowBox[{\"\\<\\\"mjd\\\"\\>\", \"\\[Rule]\", \n RowBox[{\"-\", \"726851\"}]}], \",\", \n RowBox[{\"\\<\\\"kusfrac2\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusfrac\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kus2d20\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"kusd24\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"time\\\"\\>\", \"\\[Rule]\", \"\\<\\\"middle_part_of_night\\\"\\>\"}], \n \",\", \n RowBox[{\"\\<\\\"kusp\\\"\\>\", \"\\[Rule]\", \"Null\"}], \",\", \n RowBox[{\"\\<\\\"type_filter_key\\\"\\>\", \"\\[Rule]\", 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rfJ77+Y4p5HXuLa3Rj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\n7vWG9Rtu0Lg2MAgIwmthfdbr\/yQeF46X\/QCccc2atSSn9XxkyJBBY3aw5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3QusJ+uQEs446sYEhvlxvRMeFiFePKshbV\/uC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TU7urUA4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\nrlpjPJjh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53DrCMjzxtrMB8NHyKxfflXPLL2GI0dUP+m+Xjhl1t7itd5\/OyGqzfX5dUef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\nYGBgYGBgcDOgt4AnJu8OOlY4SHLO4ZuMfzIeqOQIZl0PvQZ+yfrq8Xi2\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t5olJqH5TrvN2hBNrQVnQ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\neQjwNBj50cca2zR8+HDloT8c8aGCv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kWNP8F7NcQ+Pjw+xehDQfqznIvwD2I+WsRsRypf9EztMW2JcIM5h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\n\/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h7Vq1aTTdv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\nOfM8yBVDTg74MPiHw5sRPrZYx6ZKmZrXsfjuurXr0o+9fuR8d4zF2A7dN1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QpXUb0t3ny5JHYh\/oExhvfc635ypjCQxd\/g1pWnNSxY0eZB+BmpR9g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\nOXJUtE2X2wdikYkTJwmfAYdLHpyvHR\/qKD6xaIOTel\/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NmMp7Im+JtyPvhFW17Cw6T2gr6JJH7I5eqAZfL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VK83rq1GjRppPUrIFfTDXrJ4ibzy8qtStGgxlzPWmqq0Uuqu0jLq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OYW1ij4N9arBLnugzBGgbyx9upI6dZF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ZK1xP7Ru7TrZtXOXXL58WQIDA12\/LIQQQgghhBASA15HvGTC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\nH0iyAtcliG1Drs74ce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dT0Y7DlkUXoel60aLF0eKmDo2apWTMensY7tu\/QHNyH6Stqa8PrFrqEh13j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\nw06fjnm\/JEdA1\/nrr79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+cOsO1uOv9kkThizfG18qVq7AO7\/HjJ8SjBcAxxwSI\n0WAMYmwhRuoE+PCAjAfHsX+VXyTiAcij\/2nmT\/LCcy9I5syZeS3Bp9GjuPeb\n9LtD\/DQxrqfNeVu6Zzu2LGZsd9q335G7RkwmVapUdn1N3OPPtHiWGtJY1VrU\n8LiOpodyMHPVDx08JD98\/4MUL16c\/Yux0P7V9jJv7jzGOj38SAN5P+o4P44x\n7vFDGP+FJwVi36yhnS6dxYVkk3vyF5A+xlhftOgPOXv2HP3gkI+AmozxrsHq\n5c2YZL1OnX1rHTPiJqi3\/Isx76N2LvgE8MVpqG1NJ\/nz3WM8o2vLggW\/JMjx\nKJ46xIoxw1t7yuSpUr9eA+rWlD6W3gSp0xCvvNyaeT+XEsLjN6nAuF7ww1yy\nZKksX7acumtg5YqV9IyFp8Oav9awHjX423Xr1sv6dX97AK\/hd3gPcqdsH3Bj\n\/kUuz5gxY8g3Of\/m7\/V\/y4b1G1ibF2u6jRs30VOcdXINbNq0ia9D34u6m7iG\nrveVAZzn++9\/IDlymLwx9Mbw0waH4z3mPb53IF68cRz8g69duUZ\/jl07dpFj\n2vHPDjl25Bj9WfHMRi4coOrG+jxur9cwx6P29LvvvCePNGwklYz1OHShqs41\n615bta8LFigoPd7oyXsL92S05+3dj5H0A\/oQ640xo7+SqlWqScaMmT14Y9zn\n8dEbA5gL\/tn6j3Tp3IV+5NANKh09zhM6zT8W\/UlO0anhss8jAMZsXMB6w8Zz\nDfpQjBngp59+kje6v8GcH3BqvoA+Qq6Vs5axN5S\/gMoZwvM1U8ZMNrCeyJs3\nrxQrVkwqlK9IbxPwxU89+RT9qqE1PnXiFOs5+LNPNm7YJP369ecak8dvzXHI\nQ+aljo9uzxorZl1Ssx4ptKgzps9gDXjwPqgDgnwerEuqV3uIaNO6jcyZM5d+\ntLH5HAVovXE+GMtY4+ArOHrsl8HzYp9Gf5VYnAv2fd27vcHaT8qvAte1YIFC\nfP72+7SfyXN7tzCzD5EbCs0yfHUvXbokp06e4v\/EvYhrjjUm5qk45elFMg\/g\n+YL8kMaNmvDexrUtel9Redfon7Vr14X3m5Unp+pzRMgTUKdiXMf\/jGuCNTG8\n0JA\/gxwqjHUzr\/Uu5kVUq1qd+Vnwsdm9azefxThPcj3+3kd6+N2Y\/BY4ettT\nXEzvpxDr+eVEcJAnVL13VV9I7dcieBE5rr1GHOAYb9AZL1q4iHl4yMNBbhPG\nGvTuqClVtnRZ1peC9w60\/6g5pO45D225P\/dryZizVLWHcD\/gfoYXDeKJNy1f\nGnhJKe+mSPsknv3DNZLxHOee3GpqTxSp5jgZXxMNDQ0NDQ2NOwfYM27duo26\n4zq167L+HjhgMw6RgutkaB4Qe7CRKTNz3vFV1dSDdkD9HaD8k6GDwV4Pnj7X\nr15njqDOw4wbEEtbtWq11KtXz44Zwefvoeo1ZNnS5YwHR2gBcNzRAbFP7O8n\njJ9AvYQTs2fNDkzeOA5w+ltDRwre9e033ybnk87yis9k3FM1a9RkXyB\/2af\/\nXAIch0debqgj9h5mao9PnTrFXA\/UK0WsGvHI\/1n6dtTtxHHHOLamYcJxHZUG\nAV6smBfBEUGbgXkT2vNPP\/mUWvQkxRv7GmthJneM+xuaHuhQkYeUMWNGSZ36\nbtu\/sG2bdrzXcc4HDxw07o0L8c8x8vZp9BWTDIA+iuzYPeLmzhZmapCWLlkm\nb775FmuSU6OYMRN1Tcg9wT06bOhw2f7PjoQ5DksTg+e3itXs3b2X2qmHH3rY\nqtd7N2PEijfOkzsvY\/TwJnC9P\/0IxBvpcXw5HNB8X7micJVxeuRIRIc2bdp4\ncESYI1avXs3\/6f1ezBU2rvmGXQ8zQJ6p4L97vNGDMVnlU40cRnAOMZ3n\/K03\n3rRhkww37i3k75Ur96A8XONh6d9vALWGvXv1ZiwZwPeYzyL8D2dT5xBq1v+F\n7nPnzl3kkFHnGLma8GaFTzU+DzzME48\/KYM+G0S9JD1n4+vhbM2NV69ck107\nd9P7AjVm06ZJb3PGePZDpxrX+sbmdbJypa5fl2+nfkvuEs+BlFbNe6BM6bLU\nxiPngfotRx95fJ\/EgFjzju07+VzHmAFKFC\/BPsVeCjm2vqD8OaLjjc1c31R8\nBuD\/witKoV7d+uSnkQ\/w+6+\/M49k7969smfPXupCMSeZNYhC\/drHGAPwqYKf\nP9a+6nwUbxyfY1E6T4w3rLHQ\/8jNe+aZZ+WeewpwjQU+Fzma8P3PlCmTFC50\nr7z84suy9q+1Ma+x4HWMyAnCfYs8a+xf4C3fq0cv6phxf184f9EY17HLhwPv\n+eWXo8j3Y72E65wlSxb6t7Rq+Zx8NeYr8sER+stq4CqRnwitNbhz3FfYc+E5\ngVqtR48c5d6R9QBi29eR8cbGeAJ32\/LZVrYHOXIGXzH2E8gRVMcaZuWtmryx\nj7kMX6w15HXkXRjrSOSVIM+45bMtqeEGN4\/xD797zCd5cueR4sWKS5PGTeiH\n9ucff8qRw0fjn4cYh75RemLm3Ck9pIM3Ns9PPDngUJMbAxd2k2P3Jjl\/s26D\nCewf4VdE3WVwsMUra41rnOCjYQ2HHJ9PP\/2U4wlcMebjLMZeGOvtMmXKMC8k\nZ46crN0Ef3r6NYhY41rzxolyndC3YeG5EyonKDQ0kvwJCf+7CH0U0\/50fD7z\nkII972GMlSjrdvnKAXa7LzU0NDQ0NDQ0YgilBcN6C3tOaFEG9B8gTVEHq1Zt\n+pt518+z6yb+7y673h72g0rnBI45X758rM2KGBfqc6JG7aGDh6x4pfKRkeS5\nrk1knDl9ltoA8MZ2rChlKqlB3ngZ9Xo+WwAce0yAmOX4seM9AE1PoMS44wvW\nGrT8rZHzv2jhH9R8IOdC1RCGvqR3z96yfNmKRLuOKm\/X2a9mrdXwfHfEffbt\n20\/u+MUXXqTnofLRRqzt8ccfv+P4oAQdCxZXj7gm+nvH9h30HwRvkidPXrMW\nvPEa9qRJvo600aBj27ljJ+scIJcI54qxjjg3YjHwqkQtRuhqRo78kjUdT51M\n5JoGEgB943NshDk85EPDj1UdsjGBINYLn7w6deoyrwM5XPRoSJ+R8XDEk6Ft\nxTMjvs9aFYN3esThuFCbG94EGKuI0aZPm561DBVvnCpFKsZvp383PdYaqySN\nSJo5\/4eydl4wNUXB1IFFBfgOKL0xAI9OaIsRO1bvUTpwU4\/kDYc+KTZ+xX7C\n4j8X03tU1XZPCrzxr7\/8Kq1facPnINbCiCfDe6denXrM18DchvwY1OMEDxzl\n+LBew3UBb4t8Aly306fPUDuOmjCfj\/jCuMc+l4kTvubPqBezZPFS4947aK8n\n4nw+jrU4fJORBwI+F1xMqpR323pjjD1orMBjL1+6PE5zitPTZMvmrewf8D6Y\nu1JZ3DF05\/BZBhcGvaBHP0nsPzNQAP8MXE9o16LigGMLXKfSpctItarVmKvw\n\/HPPU7P+5chRBOpxwkv1z0V\/skYnck8xd3jE2J3j0o99gmtcoXwFrgHsujvg\njdt3iHsdGGtMq2eWyb\/dIkeKGtHw6q9atSr5etRgAQ+LcQ0eCOuPL7\/4ks\/W\nGNVgcY5NC+BfwctjnYP9y9QpU7mWj8\/zD5rgtWvWMQ8MOSN1jXsQ+wbUOsfn\n4Hlw05Fjp9YPfM6wlsV+mTnzJ\/lswEDyrfPmzZPff19IryPs+ZHPh1wQ5CLF\npa99vY7P\/Wnmz6xDgvsaewfUtAD3jdqw0OeFWnWWTf4n\/Bnl\/b9UTWZcS3Co\nJ0+c5DljXYEclyeNvihdujT\/P\/ZQahxly5adfvvdunQz5s1J1LfHOB8ggRDu\nE24+jyPkAfoaT2Ltx4KcPrwmMBYuXbjEfiBfHBLi8b953YMCuGZDIMJHQ30o\n3FtPPPGEh14ez3V4VsNvHT4FzZo14\/e4x2xvMPva62uQWNcJcwL89RC3RJ2j\nWbNmGV\/nMkcEa0p8\/eOPP1gDCvXUcX3iVIfBWh\/hWmJu37NnD32D8P8wXyqP\n6pj6\/GO9zryP+NRh0tDQ0NDQ0NDwI8hZ3Ary2GMgx\/+bid+wriZ8vHLlysV6\nWMipRH52Zst7C95Q8LBGjBoxn+zG\/ixXztzcf0MP8cnHnzLGtdpYXyEW5vR0\ncfu8kyxCEZM4T09KxOiRW6144+pVq8vvvy2UkydPSaTN7eOPI+LlVReIENOT\ncvPmLYx5oDa10vbDixJxDtReO6bqcyXW9fOK9yhOCDnspv+TyVdibzZ\/3nx5\n5JFHzBwRqx4hfLvgteh6fyZhOPXn8I+FFgYepKjtjTqk5OUT49r7G4526NAh\nWTB\/AXVX4CeKFinKGC48B\/EcgccjYouosbln9173j93fCA2PGZIPDAnx6D\/E\nSxADRxwZz1rwLJg74FeQIZ3p\/QFPzMEDBzNOAn1wguVoOTgmJxcJvglxWcTV\nwGM4eWNoNVCrF\/6cOO5kHSuJqll9xhgT5lilI4oG8OS0c\/QMgGfDsx41P9R7\noEmC\/og+mNa4MXVIIZzTnQiNrzY1gYG43hseeuOM1OmBc\/Hp0S4R\/4e\/eeM5\ns+fICy+8yJwIcMdOYO6GtvOnH3\/iM\/6cr1oOkZxLqKW7UxwJrqd5XYOJK5ev\nysWLl6g\/vHb1utyG13g0fRMlHDoY9B+8NlFPtzR9L+6y6ueavDF8beB9j3xQ\n5rTFZQw5GvYFq1asIs+JeQMaSvDv8KAAj4i8F\/BLmP8CLdchLvDFGyt\/boBa\nNmPuRK0g8F++gN+lY03oVPb\/KFq0mLzeqTOfp+D\/UIsTuZbnzpwj4GlDP2Jj\nniD3xBwTR+1UF\/WJY78ayxwB5Ir8z8GFI1cmJDgedSod4zq8Hsh12bJlCzXO\nvXr15hoD9y+8TqCh7961u0yfNp25ehF8TqO6fyXx+4n+RMYzA3m1qB+DXIBv\nv53GnJQLFy54HIcztwvcBJ4PqL+Kmujg6B8s96C0aNaCtYCbPd1cihUtLs2b\nNee1QC5rnPrax+sYZ6gbjXrOaq8KjTRq1yPGgPwYXBc+j2LwGWGWPy3+hh7C\nxrmBx8E9hTwa5B7BLw3rR9xLznsE+YmPP\/6EDBk8VJYvX8F7AvyrX9cijsba\nubduMV8fPDY84gmj\/+HzBJw+fdonjh07ZuwV9vF7+DYgrxQ5vjbwzLiVDHJN\n\/Qmvhj7dtm0b74vChQoz5gXPPeiKf1nwK30jUGth9s+z6aW3Zs0aXotIta7i\np\/PAJcchePmXe3iZ++tYEhGq3jlyi4cPGyFPPfm0NG3cVJ584il5te2rfH6g\nNl7b1m2l02udmF+DtQRqh3g8V2LiJ+1YHyE+OnnSFOnVszdzVjBGzp49S68f\n6GKYwxEhbzOUx4r7HWME9ztq\/CC+c9KqFxAT+LuGhIaGhoaGhoaGgp0DayGM\nuuPLXM+gLtvixUtkzKgxzL+GLgBcMGIeTz\/VTGrXqi2VKlQiX9nymZb04xsy\neIiMGjlK5s9bIDt37KKHLTy5\/BnPS9Yw1q43rt2QI\/8d4R4Z+k\/lC45YwLRp\n38mBAwcl0ub28cdjnCan8YM9D3iWad9OYx3HXDlymR59xnXEz6iPBp0N9gkJ\nct6+xoCP15SfGmuh3Q5mvAn7IMSlsF9CXnWKFGb8GPyx5o0TaDyEml5m8HFG\nrQBo1cA\/DBs6jPpcj+uWFOFsYaZfJ3L59+\/fz5gLciegeYEfXPfub8jLL78i\n3bp1N343n88h14\/f37BiFOCL7JwuqyEGgXkBNdegy2bty7Rp6QMJ3iVPnjxS\n46GH+byGHgfxrwSdO33EVjB2kT\/\/77\/\/MpYC31FojuGfAN4YPquow9i2TVte\n09OnEllD7iZUi6TvlCen0pJ7c7q+oPTGqB2N5wTySj784CPGzEKClD+E+f\/s\nOvVRwe0+8gLi\/tDvgBMDtwCfUfjVoE5DpH3rxVX4mzc+ZYxh3F\/gcMaNG+8B\n5EvinKCJu3zpSszrSOMLDt\/Lr1TpyKidtDTqKp8kIet14r6EHrN+vfqsE+rk\njFNQb5ySHBs48S2btsSLazTPJZies6hNAL9ZcKaq1jE0g8WLFudaCBwP9bFJ\nfA3oizdGHi54XwC1ZqCz\/bjvx\/Q79wV4oaMWstK5Y16ARzr6cMvmLXL06FE7\njm1rFIOsmo9WbdRQa\/5x5pHY3LGffaCgnX+4Rk3mHjs11MiVQW5NQvhmh1nj\nDfcLagVgXwrPJvhgwUd5xnczyAVhjQudMfouEPMUcM2Qd3X8+HGeA76i3gGu\nr2r0s7A8kW9ZnDFyipYtWcaxVbdOXXmgVGnWCYFvBWpdY+\/Y+fXOMmf2XDmP\nGsmxPbYo6htPGD+R\/mVYmyAvALlB8GX42rjuZs3hIHMO83GNwz1OxEM\/rtZD\nZp3Rm8yjAZe6c+dO5vNgzqhSpQpz3dV4gp8T7pmSJe6Xxx973Hh+fsicdtZ1\n8tc1tK9RGGtYYLyNHjWanmwvvfhSOF56iZw+1ku4ZgpYBwCYf7Fexr2z8PeF\n3CvCf3zfv\/ut+i7nzWdGAIzZJAmjoU\/hhQANO\/IwM2XIxJprqGN87Mgx7t+P\nHzvBWAz2bfBwQA6A7YPuq\/nh2JW\/gpkvcoN7BfgQ3Lxp1f+FJjYA57bYAueB\n+\/6PRX9w\/4i6DPcWLsLaGiWKlWAuzH1F7uP+qNT9paTWw7Wkxxs9ZdbPs1n\/\nCPsi\/q+YPOus+QfPo4nGfNaieQvG3pB3hDjcsGHD5IcffmB9AqwLMScjvw\/P\nGtznmOdwX0IXDc8P5BNiXhw8aAjnqje694gR8P\/d7ncNDQ0NDQ2NOxBeuiEV\nx3TGqC9evEgPSujgwF9gnwN\/vimTpsjw4SPII8P3Cvvu5cuWy\/btO\/herKGh\ng4hRHrFGrK4Z9gSXL16mL2idOnXoC45YKzRIY0aPYT5lpM3t448jkhNvjPqS\nhw8flp9\/+pkaPOiLESMFt5IzZ07Gy1DXUPkpJQZvjL3kuXPnyMkhxsgayta9\nqj4PGljEnXAcW7duZZwHuSLKKxUxGHh0aZ\/qhAP6+tdffqOHMzh56D\/27Npj\n6q2S8vhXzfje+xmD2orwR0TMe9OmTfQXg47mu2nfMSfhvC+t3h0AxETBlXjz\nxhfOX2BN07dY0\/hBxrTIsxjzB\/Ro8JD95ONP6E99wRhPftEXWOsIzCvgyuBV\ngnqaGTNksvNhELtFTsxHH\/ZljNPt\/k00qKb6JTotQwyAmDHmXPLwKVORX0Xu\nHupleswLAaQhjg22b9vOGBqeKThPaA8rVaxk+lSHhXPCiif1pY\/0N28MIDaL\n2PEh4znqxH\/\/Haa2Mc5jx7sl9nncvs15Bbkob\/V5i7FWaFrBE5v+1KmM+zg1\nf65fvwF1O6gVGl\/eGHMTfD3h34sapNAhImdA5UhgboPeC3p0cNphSXR8K2A+\nP3TwP+YLKi4Idb2xjwKgIcXaD\/Fl1I33BvZfc+fMkxbNn2HuCDkxo6\/A8+OZ\ngFws1l5U94sF5hoEh3sQmLkmTt7YUVPWz7wx7nF40mfMmMmDNwY\/pmohJAjP\nYTXwabhvMd6xT8W4AgcE\/hDPL35mdFrjQIWYXxVHDr3vbct\/Avvy776bztxu\n8CxdunSVXj17ybvvvsf1wo8\/\/Mg9foy8ub0RwbfI9Ki+eOEScyCgccY6APtU\nVd8Gn2frjZ28sZfOz8kbe3tPhFreHWrOx1dcT+QEYA3yZp835blWz0m1qtWl\nePES\/Gx4GeD5CY17l85duA\/DujvGuT3xvD7YV6FGM9a5uOfhK39\/yfvpyWIj\nTx7WqYFvBbTTCgUt4P3wk4F\/Mrjl9957z1hXfST9+\/WnjnvJ4iVy8OBBPoOS\nA0foxn1k1qFoLbmwJkmRgjU0XnzhJfl55s\/kD5G\/AajcHHCy169eDx9H3s1P\nx857X\/HGqIfNGtgmlBdNmPO9wSGWl4npsYxnFPZc3oAOHuv2dWvX8VkDbUmc\n1jgJBHMOv0jvPTxD4B3+PPDcC\/JMi2fJ7TY3AF+FVs+2kjat23Aumjdvvpw9\ncy6c34\/Bs07lq6Avvxr9lTzx+BOs0w4deukHSkud2nWkZctWfJZjfkUd+tGj\nxjAeByA3pN8n\/Vh7DPEd5IQ0N46rbp16zNtBPkJMAI4aNQ+Qaz1j+gxi06bN\nfO67fs9oaGhoaGhoJF94a4bCwuzaw\/y9rxZmxj6QQ3f61Bk5etTMu8Rek35P\nPt5vf5bb55scYK1fsebFfhc1Z5X\/V4kSJVi3auuWrZFcvAA4\/jgiOfHGuGew\nJ4WmsmjRorx+yMVHLAPxDWisENPC\/o5\/kxDXzWsMnD55WjZt2MS8V+y7sC\/0\n8JEXK752+7bs2rVLxo8bzz0OYhnKTxuagf6f9g\/30taIN5ATjjwd8MXYW0JD\ndPDAIc65ycFzjt5it4N8PytE7Bp24B4PHz7COG5yOO9YwWqIL3rojcPMWCw8\nNPv0flMeLFfevBeRxwGP6nTpyLtARwOvWWgfwjtWEv4ZLI7vvf43NG\/wjUTc\nk7yxxQUgzvLsMy1l86YtyWY+j+91jkmDPjF1qtSS5u605I3Bp0ErhniUnRfg\nvB5JDPBeRZz\/nnz38PygDStTuqx8OfJLk\/+wvJrh6624JO9+dIM3jvW1ju3f\nqO+jyj8I9XpPdJ\/tg5eBnwhqDYNPgvYQNV\/BR5q+IiZnnNrKWXjlldb0TMQz\nKV5zioiHdhA8StfOXSV\/\/vyS0vgcgD46Dz4oH3zwAee9WPdhMsPhQ4dlzqw5\n9BZG3BpzKtb+tWvXZi1HPDdNXtT0wIcv9U3Lx\/76tRty7dp17tXUfeShN3aJ\nN0b+K3Tl8BX24I3bt7fqwFu++gl07ZV3szMXy9nIrd8Odv1aRwnLs8LjmqnT\nCXN879XM+ulXqX\/DeMA4UdpEe00Wx+Nx\/oy+hYc+ciTIveXMxXsZY7VgwYLy\neqfXZfEfi+3Pj5Q3dv5\/79cd71ceG76ODXk8qA0PvqZmzZrM03WuSXAvwTsB\ne65Ef3aI0MsWHrXQPsIjHWs39EtkYM6d1Xc+f295DuA90HJD2\/3O2+\/K99O\/\nZz4O9nWaO475OFY5F8jhKVemHGtm4BrlzZuXGlHo\/D3GqYhdg9rjfpREOL6Y\nnoNVfyDcS0IiNKyXcP+hVsSli5eZ44FnA+J58FHxxpIlS2XSpEnSo0dPY27u\nQJ07dNZuXSv0OXh7xDL27tnLPNm\/12+QDX9vlJUrVhpYxdfWr13PPBLkUgDw\n9b9y6Up4fCVGvLHZn+CN586eK28a+y9ojZHLgdgNa03cbdaZSGWs01FzAmtY\neGjAQyVzxsySNo3pm08\/HWNMZcmclWsqMzfvLutZbt7nGG\/QgyA25ARew\/xV\nrWo1fjb2U6hNAQ8T1+8dDQ0NDQ0NjeQLH3sxpTu2c9Wh77DWoErnYeYxBzFu\nBK0AawSFhFhe1456WW6fXzKEqnmJPE\/4CSKHUvHGhQsXZr4jckEjbQFwDnFB\ncuKNsccZP34C\/eKKFLmPMT\/odlGDB3tVaErA15q+8Qn0uV5jABrhSd9Mlscf\nfVyGDh7KuL23zuDQwUPMTUAOO3JjkQcPP1xowZD7Cn4K8Rbs3dzu0+QC3Nvg\n8BHDR41CaIzo8x8UoHxITODlMRhq6ZtClV+uatb7EeNCbA11oOy6ll7vSe4I\ntXUAJseOcYHnLLgV1Okq\/2AFyZUzN3lExBjgx4hYAnRD0OYhLkytstKpO7ml\neB6bs3ZiZGMSc8mGDRvpo12mTFk7LgK+E3VTUbsdPgdu93NSwWefDWQ\/sm60\ncc3Rj\/Dgg1flZWcMLIkCeQ7w5EccDD7F0ITheYM6u6gfhzxFp69uuIYyfJ2q\nvg\/IeVK12P5NQrzX67PDQsWaf03fB3DAmDPefusdqfFQDeqqTC7D5CNSpUhN\n\/jht2nTGvFNeBg0cbPqTBIfGfz6xngv4HvF4cKKoaQwPyLssXxNon59p\/gzr\nR8a6D5MZtm7dZtwnw6VixUrGHJBRUqdMzT6qVauWGcc\/fsLyKbV0xQ7Nsfkc\nCbG1xqHO+saKW3DhnFD\/FrUpoQVV9Wixn4FO9NDBQ1xfhlr7Tg+uN46f56zN\nFOL0fA9We9141FR2G9794qNRg6z4WutcPTxg4vK5PmIJ8JCFXwy0efBSUjzn\nvffeS53ziuUrrWOIwdiLijdW19Xy9FdjXb2OXAlorcGtwMManHW5suXsNQny\nLx5t+ij5IOgQE\/XaGw0eT\/AJadjwEdZwT8H8nJQc+wDyw8BBwT8Gng\/gmMA\/\ngZNSfYi\/wfuAVFZ+DTyrcmTPKWWM9VXVylWNc3qM9cKOHjlGv9ygJL5G8Bfg\nsbd2zVpq0ZH3iGuRK1cuakqxbkVujhp74Z7wIXYejs0d4\/fWnsev5xAafmxK\nI8s8oWA1x5kk8v59+5lrBH+r+fPmc6+PPD1oWhs0aBgBderUZV4q\/KDxFTmL\nzOVy6TqFWnUuwHufOX3WWD+YfuEnT5ziNYLvwDnjfsZ+GnsNVRsceyPWP4hF\nPrK6jri+uJ\/AR0+ZPJWeT3h2YV2UL28+3q8Z0mXgvUjeN5XF+VpcMnniFCns\n15nv4ciVAvC7IvcWkQb1G8hrr73mgbp160nR+4pybYz3IIYErYjmjTU0NDQ0\nNDQSFZHklTPH2xFrsHnjaPhguzZqiG8fQY34Q\/HGiMv\/+edi1kVCLjf2Nvny\n5aNHD\/gmny0Ajj+uSE68MercfD\/je3peIdd90KBBrFMFDTJ84pj3bp9zAn2u\n1zjYvWuPjPziSylUsLA80+IZeputWLZCNiBf18LkSVOoZ4c3NTgKcMbw0a5Q\noaJ0aN9Rfv\/1d+5H7zg9aCICcy\/4PuRDY7+LPbGtjQmA44sTvHhjldPP54Sv\n90fX3D6fRITymANHDI0YvT0uX6HvLXLmwRlXr1qdvCHiEIgpIt6OGMNHH3wk\ny5cvt2sHq+e3M46VULxxqOKNrZivr3kKfNTChYvklZdfkezZczAegrgIYh5f\nT\/yaWhi3+zupANwK+DR4UoA3Tp82PXMFwKsi5yep5+7A\/xBaHsTfsmbJxrGC\nOHmTxk3odYHaG6jvgPeaHFKoGatNKrwxIIn4\/qjeK56\/D7Nqn6p+g5Zo0GeD\npEolqx6oQ9umNMe4HjmM373eqbMs\/H2R+b8SUpcaanrcH9x\/kH4rjz36GD8T\nfArGPHyM4b1x+fLlwL2+fsC6devl\/fffZ+wY8Wf41mfKlIm+v6tWrqbvMj07\nFPfp6xrZz2NnzfMEvJaxxOZNm2XgZwOZK6A4MGqojXUnYvNYL5PjVR71CVR3\nwdTjReSNk3RNWF\/94mxh4nsvFZ9rr57\/Xrpnkx+dKTUeepj8CK4puBLkPw0Z\nPJSeI\/HKjXWck\/PczLyIEJ9\/Az\/q34z9MdZRKm83U6bM5Hng84xaKRhniXV9\nMHbBtY0Y\/jl9FMAtQZcIj4dGjzSWhg0ayiMNHpFHGjYyfm5ETSP0w482eZT3\nA2rtwhcX9z844hzZcki2rNmZT4ZzqV7tIXnqyaeYhwxfF3jeo54A9hK2L69G\nlGPqP0uf3tC4Dlhf4xmEmkGItaC+LMYQOViHViIkRPkieOacePDGksjHbgHc\nJo7x0KFDsnnzZur6f13wK2tQoBYw8ougORgyZIh07tyZNZFQEwDr9Hr16hnj\nqEgELhO5ZMWKFSd3Dg4ZftA\/fP8DuWe3rxk8trF2gL8BvTSMcY7rE6lvYpjE\nbQ1hzW94BqF+MXzBli1bzvx71Lx+9pln5eEaNaVG9RpStkw5KVSoENcueD4j\n1x5zDPZs+Ip8EfDM5cuXp9887nsF5LCgfjl4ecTynBg0cJC0eaUN18Wvtn2V\nOXzw3Q6E66ChoaGhoaGRjBFdrECi+TsVe3DGpTUSF1bDngV+1MOHDWe8D+vT\nHDlycK+DvFHneyO9jkkIyYk3vnoZe46DrFGzYP4C+jzDO457ndDQ8PqNiTBu\n1FhATu7072aQDy5WtJixH6wrLz7\/orQz9iLt2raTdm3acT+jvJHAGSNOUatm\nbdYMW7Z0mZxA3nUA9Gdyg4o1KP1EUq\/pGAG+fBW96tZF2dw+\/kTsE3LG12+S\ncwVQxx5zxZzZc6Vj+45SqUIlxghVfD1z5sxS27gnEYeEJyTr2SluPiSRns2O\n66Ce\/770akr3htpjVatUs+tXat449ti6ZZsMGPAZn\/G49mlSp2E8E\/FhaDRP\nnTzt+jHGB\/BI\/POPxfLE409KkXvvk3Rp0\/P8oDVFfVvUwkQc1G74O695JKB9\nqhMb4uNnH436qGCzviu9NYOCZMKEidK06aPMPVSaN7Nurlk7F7pjeCyWLF6K\n+jV4Wtr3e3znFse1xLFBx3zkyFH58IOPqLGDByTyBwrkL0BflJ07dt3ReWqK\nN77vvqK8RrhWqHWCWrWIYzO3wr7Y0YwRJ1zkjbGX2bRpk5QtW9aqgWL6dqIm\nSv16DTgvsGaomDH7CHxAfI8hof5PUoD3Oiuy38cC9hrAyR0bDRxb506djXmj\npO3PirVLg\/oNue+Bbo\/rk4S6fjG4hmpNAl0iPBbgXQ3vJOxzkJeF50xi6XIx\nv+H5BG+NLz7\/gjlSmNvy580vA\/p\/JuvWrpeVy1fK8qXLZdmSZfTU\/XPRn7Lw\nt4Xyy4JfZcqkKayR+nHfT4zjbi9lHigj95csJaXuLyUPlHpAmj3djL9bYMzR\n0HKjDu35cxfk5o1bXEf6pX5zUofRtmzZSg4Q3icqhwXrLOjRTxw\/yVzOq1ev\n2bXQY9X8cA7I5UYuzqRvJkm3Lt2Yf1C5UhXmm6K2FDhweB1jT+\/LB1n5pjt5\nY+Q1dDWeMYuNMYk8s3+MMQzu1PVnsSMfOczbvyqxrgW+hIVZNRRCjH64wrxH\naLeRa\/\/lyFHMS3nh+RelerXqnF+gDQZ3jD4GB1\/0vmLMjUPuPnI7Nm7YaGOb\nsdZHnsdN+jne9MC+vftYV2zj3xsZN1LrONevg4aGhoaGhkbyRkLECiLRGmkk\nEqyGdSvWjVirwpsUuaItn21J35xlxr6TWrAEyssPBCQn3hhxCfDE4E1QBxRe\n78xxV9cqMe4pZwszfWQ3b97CPNn69epzXwP+GPW2gGLFiknu3Lm5h0RcEnmw\nHdp3kFHGnsjkjE\/QR5j51QHQp8kObvib+fHcoqzHFxbNa8kYiEmBA4Qf9cQJ\nX7N2VZfOXcmn3V\/yfuYHZcyYkf558IqDHwD0mIg3wI\/Rp1YmAecS3O+Il124\ncJGeb0oL74s3xrkcP36ccwy4YuTaQ89Yu1Ydnl9S18j6E4ixQ3sHvgien6o+\n4+OPPS4\/\/zTLGDOnXD\/G+AB1GXbv3iODBw2h1ip7tuzkDJEXAd4BnrUjR46k\nHixCHUqrmb7ukXun31GIpNGv5raprYSXI\/wJoDUqZtXZTGF5Q5t6Y5PDg19q\nlcpV6WO9Y\/tOrl8i1bLGEvQuCA33LMBxYW00ccJEqVSxMq8\/YtnQ58BfFlqp\npO7JHh+E88b38XphLoCeE3pd+Ksi9zBCC4Djjm6s7tq1Sx55pBFj6oqrSZ8+\nvRQuWJg1t5csXkqeIigovFYrY\/eW74DyWXZbO53kkQC8Me5P1O\/9asxXUur+\nByR71uw2bwyNHTyx4KuE53+C8MZxANYw0JVCvwcdL56nyKHFWuvQwUPMv0vo\nz8R4xf2JOkVTjWd5lSpVON7ByX07dRo9deEXAL8YPM8xP6PWLDhu7PVNr+2N\n5O3AeaN+8YzpM+hdBe0ntKR4Ph49cpRrM3jzoo+xDgNnrLml6IF6GL\/\/\/rs8\nXONhrlWxZs1iXCN4VsPzBM8m6IqRb4VnFa4XfIDgE4zrAz4Zetfbt4McHgah\nEWvteOvzExDwYR49egy5b+QUwIcO+wbUtcE6PIfl\/YM9BMYe9Ot4HwBOuUGD\nBtKuXTveG3gOA7NmzaZ398mTJ8lp4jMi0\/QHApQnjfKTUNchIWoQhFk5bqph\nz3X16lXm0e\/bt5\/jBPsx3qMzfpCJ4yfKmFFjZNy4cTJx4tfk8ydPmiyzZ82R\nHTt28P7GmpY4d4E5lOb9GmbXllC4ZIxPeHKfP3ue+cVu97OGhoaGhoaGhkaA\nwmrYh2Bvi5ouq1f\/xXpJ2ItCw4p9KeOnVnwlOSA58cbO6+jR8Hpi7Se9P8fA\nhQsXWAu7d6\/eUuHBClKyZEnGjxVKlChBXzTElUd+MVIWzP+FnqisNRkaaufb\nJqvrEiBwpS6WvxDZGFfN+zW3j9dfMBrifNCNffP1JGphypYpy\/gO9AGIMebP\nl5+vgUdGTjv0MQcOHAiPczr7UH1NwLkE8YyTJ08xfgkOB\/FNvOYrLok4yKpV\nq8j5Kd1CyRL3S4cOHV2ti5YUceXyVeqQoClC\/cJ77rmHQC7PiuUr2NduH2N8\ngXNYuWIln0c4R+RHIL4JH0\/UoIQ3H+o5L1+2nN610B8DyL3C3+IeiKrm9h0H\n7xZm8sbgEc6dO8\/cjT593pSK5SvS9576Yus+VT7VqNf3QKnS0rNHL+Yjnlfj\nLIHWKKGqXoFduyCUcwnqLSIPMm\/evDwO5BCgngZ4kjtZN4e6in1692GNWHBd\nqKXYpHFTGTt2HLkMny0Ajju6cfrff\/\/RB7a0cd8rrRvOD3pMaOTeMZ510GOC\nU1M5lqreJGr1QmPHGp5WvVzNG8cRceSNnXWhkZO6dOkyea3ja\/QrAGeMa4nr\n+sADDxhzTh9ymrZXWSKej+KNnHthdZzgeuDNhfWJqjMKD96\/1\/1Nr5fwOl0J\nw7cqvTHquP+y4Bd5+qmnpVSpB+iX\/fWEr2X\/vgNGv5xjHrFHDoTjuDHWb9+8\nbeKWiSCLo8R+zNlwn+A8zp07Z9aj17xxtMC6AjwpcqfxTExvzK8FCxRk\/ib2\nvehr+kAZAHf61+o1rA8zcMBAmTplKnW+u3ftlj179jIOg\/8H\/h\/9bzd8Vqgk\n2l4fvC4812vXri2FCxfms8L0FSvO2sTlypSj33Sb1m2MPcR79A\/Dmgs1x7Gn\nGPXlKFm0aFFg5yJK5L9TNafVvY9YWHhdDtPPLT6fbceiomm4H5FngJrpGAPI\nVVF+B8iBQv0h3rPen+HwcQwLCZ9bwxGWcH4vGhoaGhoaGhoayROOFmqtQbEe\nxfr0irEOBe\/AvY2OnWpEA+xB4H20aOEf0r\/fAOn3aX\/59NN+NgYOHCRffvkl\nc9gvGntkjC3EKZzxB6011tBIOCCWsGf3XvLGLZ9pydgVYueoYVyxQkV54fkX\nGMP64fsfjftyKzVmty3ONoIGMxGOD3PApo2bZdjQ4fLKy63tem+XfPggwk\/h\nq6++knp169l8VI2HasjgQYMZT3O7r5MScH0Re4JXIvxF2rRpS4BHQ5w+JCnG\nhL3qnSC+d\/nSFZn982xp26adFCpYiLXgENMHf4x7AXoZ+LUPN8YfanQAiLmD\nO4duw+\/rniQYt8N4QX+hhh79KtOktXkTbyBn5d2335Xly1ZY4yxxNUamn8Et\nWbJkqfR4owfj3oo3Bo8M\/c4dxRs7mzHW4FuLGiLIGQEXh5wK1EDFPJuUeWNw\nMFiHwj8D1zsF62qnJOeI51+ZMmXkjW5vMHfm+rUbdtye88atIP49fDqQOxLI\nOrhkh9BwjgbXAV+xHkDt1Jo1a5rXEj4Glvdto0aNZOxXY+XSpUuJzxsb7eqV\na3aeK15T4yXYOE7sZbZt3UY9e0qr7kfdunU5N0Kzi7Gk9jwJVe8D\/wd6QWiG\nhw4ZKm1bt2U9UzzvPhvwGTXD0EFDlxzmbbpr\/X24J68nvBu4SqzVANQlQpzA\n9fES4AAPjBwVaI0x92TIkFFKFC8pI4aPMHXG5OjNfIK\/12\/gvhke4eUfrEDv\nl4\/7fmysjYfx\/VjnYqwjBwr6b+d1TEzeGHGgqVOnynvvvifdu3UnJwwfunfe\neoe8MLSv4LSRg3Pu7DnmKqi6OPgZc2lymEeZKhLqvF\/E7\/EKVTsl2FE\/Rflk\nRJvHYa+NPeF2v2poaGhoaGhoaGho3EGw4vVHDh9lHGP92vXUdKAuFr7fuGET\na3FhH+n6sWpo3AFAbA\/xb9yD0D3Am7VTx07Sq2dvxqF+mvkT71FokhGfNXPo\nLS88P3g+IiYFj4Lu3d+QcmXL0SMb\/sKoxeXNXe7etUd69uwlZY33KR4KNdM\/\nH\/E5Y6Nu93VSw43rN6lV2rB+g\/yx6E8C3ohuH1dCgfpBYyz\/u+df+WHGD9Ku\nbTtqXZ08Jrgk+CnWfLimjQb1G0irlq3o433siFnzze1zCVRAQwS9dtcu3Yz7\n90GfXLFC3rz5WIMP9ff8pT2iHseY01atXM1Yd9H7ippe2Xenoe\/mHac3djZj\nel2xbAVrVhYqVIg8Fzh\/+P7O\/HEmuSYVp\/b4W7fPIQbAc+\/AvgN8NlSvXp35\nDHdZnukYi1myZKHPBsbttG+nyfr165mXBM0oeEDmzuL7oKB468k0ooCzoZsx\nZweZ9QHwFb4P8GhF3STUvlFaY\/j9ZsyQUXr16s21jdLeJfSaRXEzpqbviixa\nuIieLIeM9QbqeICzwTMG4wS6THg8P\/tMSx4jxhyeI7t37ubaCvMM6ifgfkoo\nvgm8D\/JvMJ9Cmzpm9BjjGVZLKleuwlreWO\/Bcx5rP6yt4GeLOe+776bL1Knf\n0uP2m6+\/Ib6e+DUB71vUqJ8wYYJMGD9Bxo8fzzySESNGUEM6oN8A+fWXX1mb\n1\/XxE+BADelHmzzKsYq5B\/UyGj3SWL6b9h1\/T\/15sMkfT548RZo93Zy1FOD9\njPGOerY1jTUucibgdf3yS6+w3i3Wbc77JjF5Y6x\/4JUMb4plxrMeHi7w0sbP\n4MXh9QPPEc1BJgEk4jjR0NDQ0NDQ0NDQ0NCIEip\/FR5IwaGMsygPNOwpsfdk\nHUSlY9R7Fg2NRAd9N4178PLFy+RWUTcNcdZNGzdRI3Du7Hm7BgH9Ia17NyTY\nP37xJm+8Wjp26Ch58uSRTq91Ym2Ey5cvMxaLY4FGB3X54MXYtMmjkj+\/qY2D\nXvTJJ55k3B\/aULf72lV4x4MSA26fY3SIpOHZg3rOyJF4tV17xmMRv4VvtTcQ\nr4WPJHyt+33aj3UzEZd3\/dwCDJgfoLtbungpdUfwrYyMLwYXCZ0xOOOhQ4bJ\nceNeTqzjwrWGtgmw+WCjrVq1mpxH0fuKkXPKlCETuahZP8+6s+obO5txT2\/e\ntEWGDBrCfAlcowIFCsj7771PTgB8mOnLGRSxnmYAg7kCxjMN2lDkJMFPoVLF\nSqxp7fRMx\/eo7\/74Y09Q1\/f999\/L2jXr+FzE8+T8+fNy\/fr1O2t8uDUW8VJY\neL10pTXG\/Dtu7DipVqUa71ncu+COwfsj32fypCn0JnHWo064cSTcz+D6o+4s\n1k7w4Uf+EXJlwNWq+jrnLX67a+eufHakNo4TeXC4l8B9cwxF1uJznM7nstHg\n5w2escA9BY1nXA7myVSoUFFq1KghVStXZe3lpk2akrusX68+3ws+8uGHHqZ3\ny0PVDVR7SKpVrSZVq1blV\/wev6tapSrvoxeee4F88oH9B90fQ4EM49p8+MGH\nUrhQYY5b8MaoC4OczeXLV9jjC2MW+QSDBg0m558jR07JmjWrZMmcRTJnykKt\ncgFjTXK\/Md6fafGsfPH5SPrwe4yfqNZqCbH2w78KDbO91pVHc4iq8at9jpMG\nktqaXkNDQ0NDQ0NDQ0Mj+cDLIzRCLZ3gULvuoOvHqqFxJwBfLD4YHAB8BsHB\nQkd17do1anToX2jlcShtWWiI\/2q\/g5ODHufTT\/ox3lqhfAV5vVNn1j5FrFbp\njYYPGyFPPfW05M6VR+6+Ow05Y+gbhwweQj88rQnViKxhLN+8eZN85crlK1lv\nD7Ugq1SpEgHPtniWfDH80o8dPcbxqes4RgQ4Y2hV4VsJvhHccGS8MThlcMvQ\nGeMaJOa9Cj\/YbVu2EadPnbHHxcKFi+SlF1+WQgUKscZk3tx5pe9HH7OuelL3\nz4wVnM0Y1vCbBUcM\/9P33nlPunbpataZP3XK9r9E7pHH37p9DtGAHse3Td4R\nGtE9u\/cY17ovtXs2Z3zXXfQ6hi939uw5yJdXrFiJ3rDwrR88cLDMmTWH\/jjQ\nkbp9TskSXk3V6sRaBdcOuR\/wiWjauCnrCYAvTpUyNfk31Ivt3rW7md\/AHLfE\nOUYcE2q3\/\/nHn\/L6a6+TN61ds7b8PPNn2ffvPrluPB9Qmwe5b++\/9wG54ixZ\nspL7Qw4cct3ACfryfQ4\/8YTryy1bthhz8hvGOqoiNa7wZM+QIYNkypSJP2fO\nlNnkJLNkoa4Vr9vIaMKZR5UtWzb2deWKlckzv\/LSK\/LFiC9k88bNxtrsovtj\nKJBhtM6dO0uaNGmY54g5p2SJkjJ71mzOu2F2ndkw5khCB47n6dNPNyNfD79q\nrIfBFSOvZe6cecx\/2rJlK+c1j\/GT2Hyg+igPL3NxxatZQ0NDQ0NDQ0NDQ0ND\nI5lBaZHdPg4NjTsNEv49eQBLHxOO8HpdKsfDn\/cp4sSIy4JTQt206tUeoral\nbdt28sUXI8nxwWuxTu06UuCeAqxLmy1bdqlapZoM6D9A1q\/72\/0+1ggcRNIw\n9hGbPXfunOzatVtmzpxJ\/014dzqBWsjIU4BHhuvnEqCAzg46Y8S4Hyzn25sa\n\/EOJ4iWkVavnWDN69aq\/\/OJNPf276fJWn7dk5Bdf0rcVuTHwXscxVKtanTpz\naMoRj4dXKI7J7zWs3YSzGWsycHOocw5dJ3IlFv+5mH7NHP\/4kzBHDpFqbp9D\nNAixPDPMZ5mZM4JzGzx4sDRp0kTKP1ieuQ7gjPE8AZ8DLjmd8XPuXLnJk6H+\nATgy6Fl3bN\/p+jklSziamaNg5rcB8HVetmSZdOvajc991IWlR7WBXDlzyZNP\nPkVfEozVRB1LxrGsX7de+vfrT1\/zurXryhvde8jqlauZ74b7ZtnSZcxLgB4X\nfCyOD7rdSZMm089a1UL2dd4Jeay4T08Y9zK8tHv26GnqiR+uKdWrP0TtMI4P\nGu38+fN7gD4DRh8XKlRYypcvT09khcaNG7Nu\/aCBg2TC+IkyZ\/Yc2WA8H1G3\nVufqRQOjdejQgfMLYTwXUVd97dp1pq+zlVetfH7g97yQPugzuRYZOXKkfDXm\nK3pioM4TfMGRR3nx4kVP\/brb56mhoaGhoaGhoaGhoaGhkVCQADiG2Byrr+b2\ncWloxBaWnhjxJidMfbHDZw7vFT8fm9GgGYZmp03rtlKieElqAsuULkvNBbUa\nVi1a1CWF5ge1Slnjze1+1Qg8xKa5faxJCPCkhP4aHq3QD4NvcHLF4HXAxcFf\nExxLu7avysoVq\/x6jF06d6HPOHSjM2bMYN121PRELWNwxmnTpqU3cctnW8na\ntWvvvDHgbI5nArgtpYkMs\/L87Ob9926fQ2QIVecUZnLH1rNNHfP+ffuZK\/Bm\n7zc5PhSHBt1lqlTgJFPaSJs2nTGOChnPmbdlxfKV7p9bcoSjhYaG2Tz\/1StX\nZeuWbex7aMBRjxzXI02atJI6dWrmjMGf5Mzps3Lr5u1Ey\/vAPXHjxg35+uuv\n5YnHn+Dnt36ljfz80yzZtXM3c2G+nfqt9OndR6pVq0ZuEMcH35Qur3dh3ooa\ne\/b4TKy+DDXzJUKs8Y78D9T2Hj50uAz8bBA9ND795FNqoFFv10bTR+Wxpo\/x\n\/Jo3ay5vvfW2jBg+wgbqHsO7AZr7EJVTqJrb4yeAEWaN5w7tO9g11YFy5R6U\nbdu2hY8HL42wWS871EOfzpwK1JtBrSdffud+Oh+7vlRSrGGioaGhoaGhoaGh\noXFnQu9bAheRNbePKyHPze3j0NCIBegpZ3vjhdq11Vz3ATAavBzBHcMjtWeP\nXqzLlyd3Xnor3mXF3TJlykwfSMRB9+zZS39It\/tUI0ARXXP7+JIgoHVasXyF\ndO3Sjd7T3t7U+fLmk7p168lrHV+j7\/G2rdv4N\/48RnAlqMcJ7rhF8xbyZp83\n5aHqD0nePHnJGePrU08+Jd98PUkOHjx0Z48FcKzBofR0vnnzFnmJ8FoFoebv\nQ8PC64uEhv+d68ceBcKctVIsvgPnBA3r\/n\/3y9\/rN5BXg14VfhbgdgoXupfe\nwgql7n\/AGCdPy7dTp8m\/e\/e5fk7JBr4arlmYmcNwyxiDS5csk3fefoccG7wB\nUJMC+SjwMMibJ59dfxt1N9Q4TYxjRT2Pffv2S+fXuzDXBHlrTZs8ypyZt998\nW155ubXUM+Y76NPh\/YwatpgXX37pZZn5w0x65qvz8weUfzAafDX+O\/SfHDp0\nSA4eOCj79+8n1q9fT+\/siPhVfv3lV9myeQv\/RgG1GuCJDK8Om8p0ewwlAWAu\nxbOv9SutPXljY\/0KHj7MOZc68zVFPLl59Ro83NW87Px9AJyrhoaGhoaGhoaG\nhoZGwEJzxoELX83tY4olwhwevhHqpyXB89G4g6Ga8b2tJ\/P+vcvHiFrLp06d\nZhwTHrjQxiCmrwC\/xMGDhzDu7\/axagQ4omtuH18Sw2njvlzy5xJ6tKKuuIqD\nZ82SVYoVK05u9tV2r8q4ceNl4W8LZe+eva7UhV69arX07fuxVKxQkX7E8CYA\nh1ywYCEpXbq0NG\/eQkYM\/1x27Ngply5dMnmWAOhfV+DQG4PnAH8MHtmDNw7x\n4o2T4JqbvHGIxY\/fuEk9K+pzX7p4iR7m4Ms+eP8D6dWzF3OWgH6f9pcpk6ea\nuQ8XdB3XBIOzOV7HeIP3MTxH3n33PalcuYpkzpyFuSkZ02ekz0ixosWkVcvn\n5BfjeuG9ie0vDw\/7JUuWStOmj5K7Zn3akiXp\/Yz6wUXuLUJeG\/WM8X3tWrVZ\nHxwaZIyrK5ev+G9+UV1q1SKJrJ7y9evX5cyZMxFx2gT8JLxr1irtLDy7mW+o\ndKduj6UAxtUr1+hv8Fyr5yLwxlu3bPU5dtnPEerIOBBi5sLovtfQ0NDQ0NDQ\n0NBIwtDredfBvNygYOZHJz6CTdw2v6fvq7G3vqPq5SVjKL9DQO3Xw5Jg3DTJ\nQzW3jyMpI7Lm\/L1bx+bQh+Hn8+fPs9YbYvuu95tG0kR0ze3jS2JAPU9o7HLm\nyMmasOBxAPhRt23TTkaNHMU6oG4fJ7Bn9x56x1aqVJm8TpVKVagx7tq1q8yY\nPkN279rNIaA4UbeP1zU4dbk+4DEvJ0XeOAZN1RbF+h2exzev3yQi+MG6fS7J\nARE6P\/x18PmbN26Wnj17kltLkSIFOeN0adPxK\/yfGzdqLHPnzJPjx47b4zcx\njxe839QpU+lBjeNBDWwA\/DF+hrd5xowZLT67lYweNVo2GefAPANxZ34JtfIj\nWFM5Ds3XfIA8kqBbQazJe9v43\/g5ycwBLuHCuQuyYf0GafZ0M44Vn7yxeP4N\n+jVYxRMcUPVkPHyiA+AcNTQ0NDQ0NDQ0NDRiAF3nJeAALzp4nf7w\/Y+Jjh9\/\nMPH9jB+MrzPpewefL+Spa+446cPMuw+zNQOIxUCXw7iJuH98dwxUc\/s4NBIV\nyl8U9xg4Y+TmuH1MGskAvprbx5TE0L\/fAKlapapUr\/aQtHy2pbzR7Q1i3Nhx\n8vffG2Tfv\/tYAzNO\/z+ymolxxJVLV+gF+ucff8pPM39iTdu5c+ayHumhg4eo\nA8TnqvnG7b51G07vCZ9eFMlsX6M8ZEIdPtaqdgPyPnXup3+vBXixJYuXyjtv\nvytly5ZlrofKS0GOSvr06aVK5SrGHNSfnDE0sf44NngsrFq5ir7795e8n3Wv\nwRXDk7r0A6XlsUcfky5dusqggYNk3rz55Jmx\/wTXhxZmnZ9f+9PSG2MMw9fY\nG0ov7ITyog+1OOJgKwda8ZXq3iBCQ\/W9EQNcu3pNDh44JM899zz1xv+zeOMH\nrfrGqt+dsnDuNX1oju3awgFwXhoaGhoaGhoaGhoa8YPWIroL1HGaM3uOdH69\nM\/O\/ExvwoAJaPovvn5c2rdtI34\/6yuRJU2TZkmWycsVKxh3wlVhp\/rx50xbG\nL69fu+6Kl6M\/gH3zxg0bZfny5bLmrzVy4vgJagrcPq6ogGsB70LEf1A\/Dddr\nxYoV\/Iq6YNAxXVJ8lrh\/vBoayQJifVX6Nh0j00hoeDe3jycJwMktjBnzlbR+\npQ39e2dM\/16WLV1O7N93IAIPERskNGfsjdu3guTkiZP0YMV6C3yK2\/0akJAA\nOAY\/j2vFG3v0gbMFwLEmZyhv6k0bNrFmcZUqVaktTpUyFb+innGe3HmlbNly\nrHe8bOmy8Ovih332NWO+OPzfYfpOd+\/2hjzS8BFp9EgjadH8Gen5Rk8ZPWqM\n\/Pbr79zPgWPmoWE4ue19L5b\/fGS8sZeeODTEizd2wNa5Ov632+MmKQC5AxeN\nvSTqG0OfftddKcgfgzfevGmzxcdbz8EwT4g1hny9rqGhoaGhoaGhoaERwIiu\nGe\/RMW938c3X37D2VLas2ZinnuhInVruTn038+LvvvtuArGOovcVlXp16knj\nRk1YG6tJ4yZE0yZNjZ+bSreu3WTyN5Pl8OEjcvv2bXP4JLOxc2D\/AWnfvoM0\nqN+ANQUXzF8gJ0+edP24osKtW7dZz27M6DHy9FNP85o90rCRNDa+vvzSyzJ8\n+HA5fvyErSdw+3g1NJIdnN6pOgdLIyGhmtvHkUTgrNNw88YtuXb1utyAjy\/8\nSm8FEUG3g+33xAX+WPOEx94dr+u5JWZIzrmwMWluH2Nyg6Nhvf33+g3Sp\/eb\nUq5cOep5lZ8v9lL5898jdY19VO9efejjhDmI\/8NPY1Jpd0+fPs2c0bVr1hlY\nKxv+3iA7\/tlBTvnC+YucB5XvsNLlBsT6xVdz9p93P4ZG8Xci\/j\/+JA6Mn\/bt\n25M3TpkylaRMkYo+1Wv+WkvPb7yHHgeO52GoVRPJ+bpP\/l5DQ0NDQ0NDQ0Mj\nCQJr2yWLl8jQoUPp69ShfYc4A3\/fpXNX6dmjF\/OMP\/n4ExkyeIiM+nKUfD3x\na\/rO\/fzTz\/LLgl9k8Z+LqeFEbTXkcaJ2DLiff7b9Y2F7AuAf2UZs4\/\/GZ2w2\n9rGbNm6ipnLXzl30z8K+Vq\/t\/Qt4lmH\/vuj3RdK2TVvJnSs3+Vx4ncFbzC8o\nga+lpNT9pfgzeOMC9xSQe4D890RAqfsfkNq1asvzzz0vr776qnTs2NFj7A8b\nOoye16jDt3fPXg\/8d+g\/e88ZqIAPJPTVtWrWkrx58krhQoWZp9\/ptU4yaNBg\nanmPHjkaOY4ek2NHj8txwLivThw7Qb3yiRMnqR0CoC3fu3tvjLFxwybOF5Mm\nTZLPBnxGTbr3vNOu3avSvFlzqfFQDR5zpYqVjetUR+rVrcdrhety8vhJs\/Zd\nAPSzhkayhC+vVA2N+EI1t48jiSA+OuIY643duvZ6ftFQiKq5fWzJCVa7evUq\n\/Zbmz5svb7\/1Drk05PqCX0uVMrUUKliIfHGP7j3km68nGXv7v+XC+QvueDMJ\n+O1b3NNAGw3Ajx++RPAvsDlj6\/3hc1tg9HWEFtXfuH3MyQ1Ge\/\/996WgMZ4z\npM8gd6dOI8WLFpcxo8bIP1v\/oZ49ODjY85lo5Tcpz2pXnpUaGhoaGhoaGhoa\niQDUIzx75qx8+MGHUv7B8pIyRXjecFyAv0+XJp1kzZJV8uXJRx4O+cgPPVSD\nXlFPPfmUPPfcc\/Jqu1ela5eu8mafN\/nZ\/T7tJwP6DyAvNPCzgaw7NGjg4ATA\nIP4\/AP\/7swED+Tnw7Ov3ST\/5duo07m0vX7pCjYbb1+NOAvwHURurW9fuUrZM\nWUmfLj1rT0Ev2qNHj8THGz0Y3+jZo6f06tlbunXrTu\/q6tWqk0cuUqSIFLk3\nHPcWvtfj+3z58jNmAt0yfKyQc1+hfAX6W40YPkJGfj7SAxMnfE1OFpyyN9+K\nexD+0G7vMVHjC7UFUZMsXdp09n2NumBljGv09tvvUBseKb6ZJJMMTJ40mZgy\neYpMmTJFpk6ZKlOnmhj71Vj54vMvYgzknoAXhob4gVIPUCOOvTzyDAoVKuR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viOMSh2LFi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\nsStRwvgYo6iaN7RtO+UY06dLz9+\/TZs2ZeCpPXfO3CDgPnj2w1se41ynTp3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qEmO+Lk4aefxTkL5c+Xn2sDNGvajIb\/PZy9q8+dPcfxt6gZjvFJa4iRUeM6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\nzVlrFT6K0MF07tRZfjP6A\/zT5UtX5PGjx6Y\/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Nk1f69+0vu3bu0vi04u1giy8jzgQf4lOnTpG7hccf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\nYuzM6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9e1ucuDvA\/FTn\/oxr3Fdw2F9\nvbCWOxERERERERFR\/HDMhYaFaQ++y5euyDdffyuvv\/a6vPbqazJn9hy54XNT\nggJRz\/q+XLxwUfbt3S8fDvpQ48bInymQv6DUrPmSrFmz1vTHQ0RERIlLhPrM\n0Q3j9+Ihxor+xvXr1ZfcufNEiBuXKlVKtm\/f7lhfp\/nAT4pXWf894EGAnP7v\ntHw9+mspXaq0rrHLny+\/vNH8DVn9y2o9rzJi5TGNRxOZ4ezZs\/LVqNHyYvUX\nxdPDU18blStVlk+HfarHeLzcr72uAF4XeN1dunhJ9uzeI3v27NE1qg\/8ba9H\ns58bIiIiIiIiIqJnln0Y+cbIu0Htufnz5suhg4ckICBQQkMs8vDBQ7l9y1d8\nb\/vKxIkTdU41VarUOh+aJUtWmTfvJ\/MfCxERESUuzrHYaIbGWK3nIjgfsbg4\n33DL5i1Su1YdyZUzd4S4sZeXlyxdslQuX7osIcGhMY7x3vW7K5v\/3Kx9P4zb\nq1G9hkz6blL8xdqIXAzHO\/Lte3TvKSVfKCnJPVOIRzIPqfliTRk7Zqz2ttHh\n6vu25xQHBQTJzRu3ZP269TJ06CfyidWihYusP7spgdZrE7OfHyIiIiIiIiKi\npATr+P3v+UtQYJD+vy0nJkxC7bnJ8+bNk8yZM2uvPuQfYH51+vTppm83ERER\nJULGsP+\/Iz5rHzgvQe0TrHFD7NiVceNdu3ZL61attZ60c9w4T5488sGADzSu\njBia5hvb850fl3d8\/tx5GfTBIClbpqzj9tq3ay\/nz1\/QXEnTn2uiGPC9fUdj\nti+\/9IrkyJ5DY8Y4ltGve+oPU7UGkcvv1\/66CngYIN5nz8msmbOlQ4eOUrhw\nYTWg\/wDxuX6DcWMiIrOwTwARERERUdJjH4gNa01Gi0V\/rv3E7DXjYPeu3dLv\n\/X5SrFhx8fDwtPKQGdNnmL\/9REREFC\/87vjJ1StX1b\/\/\/Cv79ux7xInjJxy\/\nE1PXr10XHx8fueFzQ\/sC3793X89BQoJDJCQkRO8bcVv8f6g979eVj+vUyVMy\nbuw4qVa1msbGjPhYxowZpW6dujJ71hwJDAiy37cRO5Yo507PnD4jc+fO05zM\nLJmzSMoUKaW49Vxp5JcjTd9\/RLFxzvuc9dx+phQpXMSxTjRtmrTStm1b+e3X\n3zTv16X3ab\/WwPcXzl+QlStWSts2beWF4i9IlixZpGhRLxk6ZKjcvXtPgoND\nTH9+iIiSHIsTs7eFiIiI3BLW+mNu5+rlq4\/FNfXuA3mjPtd8IszToUfUgb8P\nqPPnLpi+jeQGnEc0v4O4MXJpli1dJi\/WeNE2x8q4MRER0TPtxLET8vtvv6vJ\nkybLwA8GPWLCuAmO34mJjRs2yl9\/btYew+iTsX\/vfq3l7H\/fX+7dvacxZF3D\nZh\/R9kGOw+PC\/Zz856TGqDw9k9v6uCZLJilSpJQ8ufPIp8M\/1dxLxI61VnVo\npH7MTre14OcF0qhhI8mcKbPGnjNlzCRdu3aTdWvXmb7\/iGLj8MHDMmrkKMmW\nLZv8z3osYw1Enlx5ZPBHgzXXGH28XRY7wBd7v+\/Q0FDZ\/NdmzS3G6y9b1mxS\nvlx5ebtLV732sP0yESUZxjB7O5I6SzTM3i4iIiIyHa7lsPYfMePbt31lx7Yd\nsuHXDY+F+lKIV+LvYtIPjFyzn4ycjODgYIV9gFyOLX9tiTBXN3PGTBk2dJh8\nNvwzWbN6jenbTm7mMdcB6IN88MBBaVC\/gc6LInbMuDEREdGz69tvvpVXXn5F\nVaxQUfNoI0N8x\/idmKj1Si2Ns77a7FVp\/npzad+ug\/R7v79MnPidzJ0zT\/7Y\n9IfmICO\/ELVQUKsavYZ1m5xHHB4XzpkRO+7SpYuug0MfV8SOUyRPIRkzZJQ3\nO70lf\/7xl9y6eUu34XG3Ne2HaVKpYiVJny69nh8h5jXi8xHy9\/4Dpu8\/otg4\nfuy4vuazZ8+hxzJyjUuWKKm5+Q8ePNT4rivuR+cYQm1zBegN\/vfff8vwYcP1\ndZQuXTqpVq26voY2btwkly5dEh1u8PwQUQIxhtnbQURERERRwpwN1v7O\/2m+\nfPHFF\/Laq689cS6oU8dO8s3X38je3XtdX8uKwofTz3xv+8rRI8fk1\/W\/yeJF\nS9TYMeOkb5++Ur9e\/Qj7p3KlKlKpQiXp07sP48YUK3g\/QD3KetZjyujdx7gx\nERHRs6tH9x6Oz3xXwbqzdGnTaX5utqzZJW+e56RkyVJ6ztq7Vx\/tb3rl0hXt\nZ2qxhOnX4KBINWrFNY+vb993NTaWInlKza1MlTKVeqnmSzL6q9Fag1rzjaNY\nC4saS8iT\/ujDj+T5557Xv8ueLbv+7ZLFS+XK5Sum7z+i2Dh08JCMHDlKj2Pk\n36dLl14qlK8oP\/ww1fY74pr7Mdam47WN+veIVderW0+yZskquXPn1vedbVu3\nia+vr8vuk4gSGXGDbSDuCyIiInJAjTjvs96yb+8+WbRwkfYzbfF\/LaRK5SqO\ndfSPgzX26O+Fnl5bNm\/RmGYI+xE9kdFDNvp\/D98\/Bw4ckK3Wa+ktW7aoxYsW\n65psXGOj3h5gHxQtUlRy5sip68SdY8dNGjeR8ePGW\/fxftMfNyUeqFO9dMlS\nqVG9hs6tZsqUSfv5mb1dREREFD\/iK26cOnUayZA+o8aO8TV9ugzWrxl0jeqU\nyT\/I5YuXNaaEc+NgI9\/Y1TUSrbczZPBQeS7Pc3pek8a6TenTphdPT0\/Jmyev\nNGvaTHbv3C1BAUF6LYM+x\/p39oF+rJO+myS1atVy9EdGLw\/EwM6eOasxb7P3\nH1FsIFY7aOCHGr\/VuHHadFK+bHmZ8v0UrdXukvtxeh0jn3\/VL6ukSqUq+l6A\na4vatWrrutQH9x+E5zezLipR0iRusA1EREREpBAznjVjlrz1ZmcpVbK0Xi+i\nZltyz+TW60ePGM0Fob5bmdJl5NPhn8nf+\/\/WWKfZj8tUUfUDcR7W\/8eaa+Qz\nRPVviBlrXzUrzEP17tVbGjZoqOuyoVSpUpIqVWqd88K+MvZXlsxZpHKlytqj\nzblWNWpXo1c17tP054YSB+vYvXuPvP9ePynmVUzndsqULisrlq8wf9uIiIgo\nXiCOhBhOXHw16iuNRQG+x89mz5qtcM0x\/ccZ8uO0H9XaNevk6OGjeu1gxIwi\n5Pu6IG6s59X221i+bLl06dxFz21yZM9hixt7eEqaNGmkSJEiei3z159\/iY\/1\nvBlxbL0NseUa7961W\/uv4m+N66DXX3td42A+131M33dEsYW1yK1attI1HDie\nMQ9Qrmw5W9w4rrHbKF67v67\/VXq900ty58qt1xZlrfc1duw4OXjwoF6n4j1A\ne527wXNDRCYQN9gGIiIioiQM\/b1Onz4jc+fMlb593tWc1CKFi0qmjJl07gTX\ncUUKF5GqVarKO9Zru6jmhJC\/+uGgD6VsmbIat8ycObPGmJC3fP\/efdMfo6mi\niBsHBQXJ5cuXtV8s5qPQT+rGjRvaQw052v+d+k+2b9+hc2jDPhkmH334sbzX\n9z1p17adFC\/+guTJk0dr4qEPFGDOqnatOtKzR0+ZNnWa7hPkgv7yyyq9j6tX\nrjr4XPPR\/semPy+UKGC+1s\/PT376ab7WqsN6hBdeeEEGfzRY9u9jzjoRERFF\n78rlq3Lo4GGF742f4\/wiOChYAq3npIjJ4twUQux9jR8ZLtgWxL6QNwy4j1Mn\nT8nP83+W9u3aS4kXSmjOMa59EDNLnTq11pweOmSo9lxGfvGDBw\/0HB7n04g5\nV69WQ3Mz8TeIsb3Ts5f1nP5ErK99AqyP\/47vHYWYtNn7jJKmyZMmy4s1aurr\nIDxuXF5rAMTptqO4Dr5165Z8\/tnnUrpUaUmdKrUULlRYOnV8U\/bu2atzE3h9\n4j3Csa6aiJIecYNtICIiIkqCsI4XPYh37dwlk7+fLE0aN5U8ufNozjBixohL\nehX1kkYNG0nf3n3lixFfyubNW6K8rTu+fnL40BGtaW2sue\/Z4x3GjSGKuDHi\ncJiDmjh+onz80WDtNezt7a3rqhGLmzNrjvZLq1O7juR7Pr\/kypFLa05j\/+C6\nGrWnq1WtJm+9+Za89+578v7778uE8RM0Bh3CPGJyocCAIDly+IgMGTxE60pi\nDgn57ht\/36jzpmZvHxEREbkvxIERFwZH7xr7QGwoKtGOOGyHUb8H1z84Vw4N\nsWicGn04Fi5YKE2bNBUPD0\/x9EhuqzudzBY7Rg0l1Ov+ZeUv2s8Yuce45vlu\n4neSJ09eW36y9fzIq4iXjPl2jN5mbGNd6Oe8a+dudfb0WdP3GSVN34z+Ro93\n9OrGtTx6VFWsUFGmor+xuOh+rAP5+LgOfv311zVmjJpZrzZ7TWsQXLt2zVFj\n4HE9nIjoGWYMs7eDiOKHMczeDiIiihbWs2\/4bYP06d1HcuTIqfEgrUdtvU5E\nDuvbXd6WEZ+NkE0bN2ld49u3bsvDBw+jvC1c32E+qGvXrowbRxZF3PjSpUvy\n+ecjtM40crRxnezt7a3rrydOmCj169WXbNmyaZ285MmTa6+1UiVLSZvWbeTj\njz6WKZOnaKwZ81fYN4j\/I0cB+0fn28x+zPTMuOt3V6b\/OF2aNGlqPQ6TS\/58\n+aVvn756zCFPyOztIyIiokTmccPV92WvS42YsSXEIiFBIXr+EhwUotcvyCE+\nc\/qM5j7iXBvXQ4gZ\/89+PYO6SyVKlNTY8Zhvx8qsmbOt5+rfaY0frLPF76Cu\nL3obz5wxM1bbhnOpBT8v0HP7Th076VrQZUuWmb9\/KElCjav8z+fX2mE4rrEe\nomiRojL6q9GaA+xY9\/GUjDjwoYOH5P333tcYddo0aSVnjlz6Gjh65JjWqLfF\njM1\/PoiIiIiIiJIa9B3GmuL2bdvrHAnW1aPOWpXKVTSOjFrHGzdu0tzX69eu\nx\/h2MafCuHEkUcSNUYe6VavWUrBAQSlUoJDmLBw7ekzu3LkjX4\/+WmrXqq2x\n\/Lp16kq3rt20p\/E3X38jS5cs015zqGuN3IQAo9caUTxAzfS9e\/dK17e7aq16\nrGFA7745s+foOhHmARAREVGsOQ\/nnxnfuzJmpHFjW21q5BgHBwZLUICtJjbi\nyMZ9Yy0t6kx7eXlJunTpNI8YcI2Er6jBhF4+r736mnqx+ouOer7Zs2XXXjJL\nlyyV+\/f9HwvrcM+eOSsnjp+QtWvWal2nvHnyah+QmjVqyqTvJpm\/fyhJ+vDD\nD7XPt7GOHPHjbFmzy4D+A3RtRVxqqBtrNwICAmT1qtVS8oWS+rrJlTOXVKta\nXebOmac1jkKCQ3l9QURERERElMAQ6zl\/\/oKuG8b6YaypT5UqtV63IVb56fBP\ndQ0w4kWR\/9aoF\/W4aznGjaMQKW6Meaq91uelUsXKkjZNOq1Djbp2iOUj7wAx\nOcTuX2v2mnw\/6XvZuWOnHDxwSM55n9OcYuxD9nqi+ITXeHBwsBw\/flx7bKP+\nAHJq8ubNK6NGjdK61TwGiYiIKE6c1lTGtzB7\/Bh5xjgXN\/KN9d\/FVjv3rz83\nS9++70rFCpU0DxL1ehE7QxwNNXsR282WNZvkzpVbcmQLj69hHej4ceO1RhPW\n3D7OyuUrdU0oetG8UPwFzWfG7VWtUlVGjxqt\/V1N3y+UJGEeAMeykW+MNRNY\nM9qqZSv5bf1vep0al9u3WCxy9uxZ7a2E4x6vKaxfR88mXO9aHHMN5j8XiUbk\n9el87oiIiIiI6CkgZjxo4CDtVYQ18lg\/XyB\/Ae1LvGL5Crl08ZL4+\/uH16Fy\nrNG36M8AfcGi7D0WxrhxTOA5XrhgkRQrVlyf\/1w5c8v4cRPkxPF\/9PlF3Wnv\ns95y8t+Tcu3qNa0Lhppdtr5woXrNzVrUFJ9Qv9HHx0dWrrDNbebLl0+8vIpJ\nl85vaw9tHJM8BomIiChRsV7XaH\/j4FDb9YzTWthg6zn49es+8tuvG+STocOk\nTu26UrRwUcmUMbO973F4\/jHiaujJqn2Qrdc8iCW3btla3un5zhMhBocaLqht\nbfSP7d6tu67Tw3XTDZ+4xeaIntasmbOkYYOGtlrt9ut51GtvUL+B9lS6dPHy\nU8clcW2BdemLFy2Rjh066esnY4aMWlsLvZdw22Fu8BwkOvZYcRhj7kRERERE\n9JQQ60GN41qv1NLcwRQpUkihgoXkzU5vyvJlyzWe6fz7WIuPtfen\/j0lO7bt\nkHlz52n96pkzZsmqVavk9w2\/67r6\/2fvLsCjupowAJc4gQR3gntxd3crLsVd\ni1MoVipA9a8BBQrFitNiLRQN0uLuEDxACBaSEOL5\/p3Z7LIJSXF2E7779H0S\nNrs3995s0nvOnJk5efIUrl65qtq3a8+48VPs8NyBYUOGaU06uU5SD+y7\/32v\ncWJrHxuR8Lv\/QH+\/Pxz5IcqWLau5B7K25I\/fV+Ga4e+ErF2w9jESERERPRdT\nfCUiWuTjx+Wj3N9IDxjJ+f3m62\/QokVLzQl2cUmqeZfGvsfvmJnGPC\/ClGs5\nevRo7Nq5y\/rXht56O7bvwPBhw5EqZeoY79XKlSrj22++xaWLl1+4hrTMB0if\npkEfDEb+6LXTMhbu1Kkzrl25pn3HWZ\/6BVj0b3\/8d82iRhxzkImIiIiI6Cku\nXLiA2bNn6xp3iRlLvLJN6zZYumTpE8+V3Nbr3tc1Ljx71myMGDZCa9Xmypkb\nhQoW0h6nEm+WvqfTp07Hqj9WKVmjzLhx3ExrqKUOtfRHc3dLYR4zTzNcQ+kb\nZe1jJBLeV721Vl2lSpW0hn2pEqUw6fPJCPQPNNYigPWPkYiIiOilRW8SM5Yc\n5IiISPj5PcD5s+exetVqfDT6I1SuVAXZPLIb8zAtYscvEzdu0rip5nBK74+4\n+gMRvWknT5zE1199o3XTZYxqqlVdsUJFfDnlS1y6cMn4XMstrn3Fftyw3b17\nT9djNGnSFMmTJ9ecfck1lnj0jRs3NR\/5uY43vu\/9tokVN5ae7XIthfw9i4xj\nfQwREREREZGlDes3aM3Z9OnTa56xxIzXrV2Hmzd9nniu9Dj+4bsftOdx4XcL\nI0eOHHB3d9deXzLWy5Qxk9a3lhi0jPmaN2uuZL+MGz9J6nwb63sDU3+aiiKF\ni2qeQepUqVGhfEVs2bwFQQ+DrH6c9HbTtemGj5L73rhRY6RLl15rLw4cMFDz\nj2PXdCQiIiJK0KI3U18eU56erJO7cf2G3qNPmfwFunTqYrhnr4D0hnsjFxeX\n54oRS5\/kNKnTap6ljK26dumKhQsW4vKlK7pW1+rXgMjgzOmzWgNL4samGuzy\nsUjhIhj8wWDD1888\/j0x9ayKvR\/TZvGY9jW+cBGLFy1GuXLldO2FxKU\/GPgB\ndmzfqX2Tpc7Zsxyjxkht4FrZDMu4sWVvsXBjb7EI6XEVwTpRREREREQUvz\/X\n\/YXevXqjdKnSmissecaxY8YydyFjt59+\/Am1a9XROLGsrc+ZM6f24+revTs6\ndeqksc68efJqrmyWzFmQJUtWlSxZMri6umo8efKkybh86TLnQ6JMvdSM9be+\n\/+575M9XQK+r9DiWnO0Tx09Y\/Rjp7SZzDrImXXJeNm3ahGJFiyFlipS6bkRy\n5K9cvmL1YyQiIiJ65WD8KPEoyTeOjDQ9aKyvKzGvdWvWYexHY1GmdBmkS5Pu\ncVzNzh4O9g6aPyn1nGJy0phxhvQZUK5sOe1v\/NvC37R3kNXPmSiW48eO44sp\nXyBt2rQa2zXFjTNmzIh69eppvrDksUqM1xyLjG+L3qfEl2UMvHfPXu1\/I3Xf\ndT2FYf8\/T\/8Zj4KC8cDP\/+nzBfJB9mdRj9lcg\/ltzqONHTeOjERYmOFnFBpq\nZPhZSezY6sdJREREREQ2a9+effj+f9\/r2l7pZxzXc+7euYs9u\/doHWrjXIid\n5hW\/374DTp08bRh7hOlzvvvfd9rLWOpWybp7Uy0rIWuUW7VsrbnMxvXI1j93\na5O4sdaMMozjpB5Xvrz54OqaDFWqVMX\/vv0fLl++bPVjTCjMPZue8fmmddem\nml2mul3Mm33yukaER2qNuh9\/+BG5cubS331ZL3LwwEG9Zm\/1vAwRERElXjB+\nNMZeoqLru0Yh+FEwbt+6jV07dmHS55NQrGhxrRdkihvnyJETNarXQMsWLdGu\nbbsY2rdvj5EjRmLa1Gna++fgwUO4euWqYTwQbv3zJYrl4sWLmDNnDooXL45U\nKVPpWghZF+GaNBny5s6rMeVDhw4Z62hFGNdES7w3NHpspfux3KL3K79Hy5cv\nR8ECBeHu5g4nRyekNOx\/7q\/ztK+x\/I6FmfobxzXWQHTtLs4rxC06dhzgH4jT\np05j3tx5Wt9M1qjc9r3NMS8REREREf2ne3fv4fy58zh8+Ai8r3nH+ZxDBw\/p\nWnipo5bUJSmyeWTDyOEjdY2w\/wN\/HbPJulXZjzy2aeMm9O\/XX+sum2LH8rqs\nWT0w8eOJ8DrvpWNBa5+7tclY+uaNm1i7Zi3atmkLt+TuOhZn3PgZ6XjYuF79\nYWCQ1vSW95X8W2KdpjrgMepwwVgX7dSpU1j\/13qdm5jx8wzMnzcfO3fswo3r\nN61\/XjbEdH3\/\/edfjB83XmvOv1voXf17cOLECc45EBERUeIG48eo6LixCA0O\nhd89P40bTxg\/ATmy59BeM6a4scSMP\/3kU72\/XLZ0WQwrlq\/A7n9349qVa6wV\nSzZP1oZLX5pWrVrp+lEZq9pH59NLDaIG9RtgxoyZCAwM1FxWc9w4OqfVXLva\nYpM1GDJuk1pmpt+ZdGnToWqVali7eq2xpnL0eC6uuLEph1bi1PI9Hz58iICA\nQN1nlEVdAGtfO6szXLf9+w5oXbNm7zVD7Vq10atHL1zwumD8uVj7+IiIiIiI\nKEGScdctn1s65yH1o2QtsPQwbtumncbc4nudjBN\/+mkqataopWNKxo3jJjFN\nGbdJjLhy5crmunaMGz8jy7jxw5hxY\/l47959w\/W9iEMHDsFzmyc2btyIv\/76\nC6tXr8akSZMwoP8AdOvaDe3atkd\/w+dLFi\/FecN70+rnZUNM1\/fQocP46suv\nkCd3Hs2L79iho+YbS668tY+RiIiI6I2QD5HGuPG9u\/exds067fcjdaelHpOQ\n+\/lePXtprSa\/+36aRxzbE+saiWyUxBdl7P7JxE9QpkwZrSUt73PJD5bxvfSv\n6vB+B32OxI7Nm7w2Mrp+dBRibDK2uHL5qq6teOedd\/R3RnrhfP3V1zh86AhC\ngiX+HKFrNGLEjIHoWkjGml0SO5aY8eVLl3Hu7DndZzjz9mOY\/PlkFCpYCEmT\nJtW6ZhUrVMLRI0cf54ITERERERE9Jxl3Se5wv7794OLsYhgn2qFkiZJYvWo1\nrntfj\/d1ccWNWaf6SYwbvzpR0Uyb9OM9dvQY5s6Zi4EDBqJa1WooUqSo9uSW\ntQ\/JkyfXj7KuvVLFyroWYumSZdqrztrnYktMcWOpS7Bxw0bNNU7pnhKlSpbC\nX3\/+hQd+D6x+jERERERvksSs\/O4\/wNxf56J5s+ZwcHDQeFoK9xQoXqy41oO9\n7XtHn2ftYyV6GTJulzrqs3+Zjfr16sPFxUXzjSV2bG9vr5+XKFES48dNwLKl\ny7W3jcRzdYveh6l+tYx9w8PDdZwmvzvvNX3PWJvM8LtTvlx5LIsei8nzLfsP\nRUbHimUfpt5E8pwHDx7o+oyPJ3yM8WPH49c5v2otNGtfM1uyetUa7UdWq2Yt\ndOrYWfuKnT1zVtdbW\/vYiIiIiIgoYZKx2Yb1f+s6ellTnDpVGp0bOXnyVLxj\nDYkjnTh2AsOGDkORwkV0LCi9kOrUroNVf6zGtavXrH5etuKJuLFhzGxv54Cq\njBs\/v+hN5ufu3L6DBfMWaE5szRo1dY11xowZ4eHhgRLFS6BRw8Zo3Kgx+vbp\nq3HlhfMXYs3qNTh5\/KTGR+Pto\/U2ie6JZazJGKnr\/o8cPoL69RroGpAM6TOi\nU8dOWLJ4if7Om+dF3\/brRkRERImbYZM6vD43b2m+ZNmyZTV+JvfxmTNl1h7G\n\/1WXiSghkfkAea9v3bIVQwYPMeeuSp6w5gob3vdp06ZD6VKl0a1LN8ycMVN7\nIt+4cQP37t3TOtIyThCyL\/kofZqGDB6q+3K0d9Sc5Xp162Hr5q3w8bkF0ya5\nzjIOEZJ\/LK815RtLnvH+ffvx5RdfokSJEjrXMHHCRK2rbe1rZkskD\/zPdX\/h\nu2+\/w6o\/VuHUyVO6\/j\/QP9Dqx0YUJ84nEBHR2y4S\/P8h2TwZmy1etBitW7XW\nXkbS17hnj57wveUb72tuXr9p7IHUshUypM+gPYtK6hrk8RqTs\/Y52ZIn48Z2\ncDCMnSUHlnHjZydr0GXtuvDze4BjR46hd68+cHdLAbfkbsiSOQuKFSum\/bcG\n9B+IH3\/4EbNmzNI5PZ+bPlpnUNamPwx8iNCQMMaNRXTM2HQtZL3\/lctXMGL4\nCJQpXQapU6VG9mzZ0aVzF2zZvAU3rt\/Q+Zy3\/roRERFRoif1p48a7jfbtG6r\n90RSL0jGPDly5NTY2s4dO61+jESvQvCjEDy4\/8Aw\/r+t68lHDBuBTJkymWPG\nMkcgcV\/pdZzT8P6X9bnf\/+97LFywENu2boOv721dZyExYBOZS5B16Tmy5dA1\n5jLHIGOKPbv34s6dOzBtEmeWOmaR0bnH2pPXMNYIDAjUeOjYseNQtkxZ\/f7v\nNW3GfOM4yHyO1A+X+gdybeRn8TAwSK+rtY\/thVlu1j4WevXelvkE2MAxvC0s\nN2sfCxHR00SCcWNKEGRcMeajMSiYv6B5TPcsceO\/N\/yNGtVrmGtU9+83ALt2\n7sIj9jSOIXbcWOabHB2ctKYy48bPIDq2GRYSZhgHByDA4PLFy1i58nc0adIU\nzs7OyJQxM9q2bYd5c+dh9797dI7huvcNzUkOCAgw95eTemoiyrLYtbXPz8rX\n1pL0F7t75x7Wrl2HwYMGo1iRYlpHIHv27GjSuIn+zsscjl4\/ax87ERER0Wt0\ny+cWPLd5ao6j1GSSe3i7JPbInSsPPhw5Crv\/2W3u9cE+xpRgwRh3DDaM4WVe\nwPuat97zd+3SFQUKFNSYsYz3hXyezDUZPLJmQ5XKVXS9bs\/uPfHz9BnYtHEz\nzp87r\/uR\/fr6+qJXj146t2BveK3kKkutadn\/o0ePYNpkbCZjNdP47FHQI\/29\nmzljFiaMm4DKlSojd+482j\/nm6+\/0RrZCToe+prI9dPrGGmM22vNcP5dImtD\nPI9znpyIiN52jBuTLYlj8\/f3x+lTZ4xrgbPn0HX0kl\/Yq2fvJ+PGFtvePXsx\n+IPByJc3n8aMZS3ypM8naT0kGaNY\/VxtiIzfzpw+gwnjJ6B06TI63yRzT7JO\n+7eFi3Djxk2rH6Otk1rKch1lLkNI3bP1f21A506dtRevxDiXL1sBLy8v7aUl\n8xUyn2AaO1v7+G1e9P+r5Fo9CgrGpYuXMH\/efLRv2x6ZMmWGq6srPLJ66N8J\nqU1w4cJFBASw7hkRERElXlJnRerWSHxMxjtCxkp58+TDuDHjsOffPQgPDddc\nzTAZ\/8D6x0z03GDsTWyO3Rr+k\/phv6\/8HT2699C5AXc3d+3vrfnH8rugfZeM\nY9qMGTKhVs3aGPTBYMyaOQv\/\/vMvjh09Bk\/P7WjZoiUyZcykr5X1F1IPSupa\ny7peE5mPkMcuXbqE06dOY9euXTq2kzXWsq49d67c2t9p9OjROLD\/gPWvFxE9\nO8TzOOfJiYjobcecY7IV8Wy3fW\/jn13\/oFfPXsiTO4+O\/yR+3Kd3H603Ffv1\nMpaU\/kWLFi1C\/rz5dQwpNaOkjtXcX+ca61MxTheDjMFl7Ny3Tz8ULFhIr7Gz\nkzPatGqjdcAkJ9bax5jQSP2tQwcP4\/PPJ+l7V97DMt9gfo5ps4FjTTAsYsfh\nhvfsoYOH8PWXX6Nc2XL6e25nZ6fzRlLPfuHC33ReR3IFoiKirH\/sRERERK+Y\n5Btv2+qJGtVrarxY48ZJ7JA\/X35dL7t79x4E+Aci6GGQ5mvqZgPHHS\/L44uM\ng7WPj6xGa0tHGvsMR0X3BpKxlaybGDpkqI4H0qZJp\/2W5PdAco+TuyZX0i9I\n6ldnzZoVBfIXQJHCRVC0aDFd25smdRqNLZvixp99+hm2e27Hrp3\/mO3YvgMr\nV6xEv779ULtWbbz7bmGNNadwT6FjkN49e2PF8hW4fOkyAgMfWv1aEdErwP\/n\nEBHR245jMLIV8WwSA5a45ZTJU1CxYiUdA\/5X3Fhyib29r2PKlC+Q1CWp1qqS\nuRMZT+7Zs0f7Eln9XG2MxI337d2Pxo2aaA9eiRu7OLtorzTGjV+MzM3dvyc9\n545qbfS7d+\/q\/IZ8zbJfr7WPM6GSuSPJMzi4\/6DmyVesWFHnSaUmeNasHjp\/\nOm3qNJw5fVb\/hphfC+sfOxEREdGrIPVtNv29CdWrVdd6Qaac40IFC2nepNyH\nGmv7GmvcmDcbOPYnRBoPLTy6fg\/ralNs2lZYYsemsZRhk1piWzZvweeffo73\n23dAhfIVkT5dejg6Oup4VtZCy3yAqQeys5OLjhlMvyvG3GQ7nWPIly8\/6tap\ni+7deqBnj17aF6tH957o1rU7WrVopTFniRXLWFn6iRcrWgxt27TVmPG1q95a\nz9ra14iIiIiIiChRiWeTMaHMd8ybNx\/N3mum473\/ihtLvyEZO0q9WhnTybhQ\n1h8vmLcAF7wuWv88bZDMI+3ZvQe1a9VB+vQZjHFjFxcdBzNu\/GJMveS0rtnd\nezFqo0dFGln7GBM6ic3Ltd25fSc+mfgJypQpg9SpU+scUbq06fTvxfff\/aB5\nx5L\/HWOzgeMnIiIiehlXLl\/BimUrULFCRXOepeQdFytWDPPmzoOX1wXIFmUR\nZ4ux2cA5CD2+CGPP0wD\/AO2RIx81R9oGjo9sCKJjx5J3HJ2DLHXYpafwqj9W\n6VpzqRmtecROTho\/llxiiRtLbNjJwdgHXOpZa01r6QluZ6fjX3vtkeyozxGO\nBvJvedw0r6B1zDJm0t+5EcNHYPOmLbjl42v960JERERERJQYxbPJWDAkJFRr\nUEm9X6kjJfmEXbt01VpQ5vkEQNf43rlzB99++y1q1qgJZ0dnJE2aFPXq1ceO\nHTvhe+s2czzjECNunC6DzjdpvjHjxi\/HtBk+N8\/XvYr9Rsb6\/C2uG6F16UPC\nsG\/vPs07LlWylM7nyLxO6tRp9O+A1Kc\/e+as9kXTnmiw\/nETERERvSzpiTJ+\n3ATNLzblTqZIkVLvf6Su7tUrV6Gb5etMmw0cv6n\/SFhouOZEy7ju+LHjWLxo\nMTZt3IRz585Z\/xjJJsk9vdzbh4aE4mFgkK4R9b3lC6\/zXpgzew66d+uuvxd5\n8uRB5kyZzbFjU66xKW4s\/9aY8TPEjeX1EpP+5utv9P0p44u7d+7qMVj7ehAR\nERERESVK8WwyJpS5BIkLjR41WmtNSf1pySHWdfSGsaHp9Q\/8HuDggYNo3+59\nZMuaDS7OSVGmVBmMHTMWFy9cRGAA+w3F5cm4sR3rVL8iUdHzYa80v5hx4xjn\nL+tFZM7m8CGZOx2v6\/\/t7e01v0D6mkuvMokdy5oSrRUOGzhuIiIiope08e+N\naNSwseF+J7M5buyR1QPt2rbXPily72Pe5DW2dr8YfZ8staX87vtp3uai3xah\nY4eOGDhgIJYtXWb9YySbpDWrIyJ1rYHkG8t41tT\/+Py581i7dh0mT56McWPH\naR2yypUqaz\/j7NmyI22atDqfoHFjO3tjHrKTs\/7u5MqZGxnTZ0QGw5g4S+as\nyJc3PxrUb6j7kDXsP0\/\/GSdPnEJgQKDVrwEREREREdFbIY5NxoQyDpSeQTJO\nk7pQ0sNUxnUyftu2dZv5uVevXtW19RUrVNKcw6TOSdGhfQcsWbwEfn4PEBbG\nWmdxiR03NvV\/at68BdauWWvM07aB40yITHHjV7cvmHOXIyOia\/pFRj2OTdva\nfOAbIu\/hh4EP9e+BxI6LFyuONNFzQlKz+qPRH+HM6TN49OgRdLOBYyYiIiJ6\nGb8tXISMGTLp\/Y4pblywYCEMHjQEVy5dMeZBmjZ5jY3eJ8o93HXvGzh65BiG\nDx+BlClS6v3bsKHDrH5sZPtkHCRjgQhTT2yLTdaVHzl8BFN\/nIqhQ4Zqn+IK\n5SpoDvI7ht8XezsH7XksfYvr16uv66ZlLkGeU7tmba1xtmH9BqufIxERERER\nEcG8SdzYGBsDtmzZonnG0q\/I3c0dJYqXwPx58zXfUPocHT1yFF9\/9TUKFiio\n9aRcXV01hnTo0CGtY\/V4p2RJxtl79+xF3Tr1kCF9BmOvJ8M4ukGDBhpzv3nj\nptWP8a0n0yDRcWKJF0sOvqyvjwiPNPb3sogh2+qc4Ou8NqbPpb\/5vj37MOrD\n0VqzWtaYyDqIzp27YNs2T+03rZu1j5mIiIjoJf0651e4uLhonRVT3LhA\/gIY\nMngIfHx8dIxk3uQ1tniPaNhCDfe0Ut9I6kv169tPa8bIPVzfvn2tf3yUIMTX\nw1vWjfv5+cHLy0vjx\/\/s\/AcbN2xEt67dzHHj7NlyoEmTplgwf4GupZZ1qFu3\nbMWO7Tuwf99++Nz0sfr5ERERERERER5vhs9NNX6PHT2GkSNGonDhwnB0dELa\n1Gkx8eOJWoP62tVr2stIatJmzJAR6dOlR+lSpbXW2S2fWxpTs\/o52SiJG0vM\nvWePXsifL7\/G2ZIksUP5cuUx6fNJen2tfYyJQYzcY9P2PPuIfFyPzfuaN7yv\nemtvX\/n5mWPHb2Pc2IJcC1\/f29izZy9aNG+pde2lJ3rJEiXx4YejtCbBc193\nIiIiIhv0y6xfjPft7zwm9\/ISN9Y+M5abvMZG7xElvi11f48fO6F1hXPkyIE0\nadJg4MCBVj82SmAst+jHzPnI4ZEqNDgUX3\/1Ddzc3HSskC9vPnTu1EVjxFY\/\nfiIiIiIiIoqfaZPPo+c4JO\/1z3V\/om6duuZaym3btNWcWFmfLrnFEjN2S+6G\nIu8W0fXqsmY4JDjkra7h+zQyjj518hQ+HPkhSpYopddVyOejRo7CubPnrH6M\niYXEd4MN78egoCDNjZVr\/7TXSM+32753NLb\/z65\/4LnNE7NmzFLyudT1kzkQ\nU17+W\/s+jz5v6WH88GEQenTvCScHJ50Pkj5m9erWw5kzZ6CbtY+ViIiI6CX9\n8ssvsLez1\/WeprixxMAGfzDYGDc2PRfRH23xHtHi\/u3e3Xv4feXv6N6tOypW\nrIQJ4ydY\/\/jIdsW1WX49es1ueFgEggxjA1l7q3WbQsIwc8ZMXWMh9amzZMqC\nmjVqYrvnduufExERERERET0XGfM9DAxC165dzXHjvHny4f327+PPtX\/qHInM\nnbg4u2h\/ouXLluPaNW+rH7etk9il9H4dO3YcypergGSuyZR8Lmv+z587b\/Vj\nTPCiN6mXfuuWL65evQbva9c1dvy010q+\/I7tOzF86HC0aNYCjRo2RjaPbEo+\nl55b8jOMsvY52gBzr2fDxejTuw8c7B2V\/F0oVqwYjh07ZvxB2MCxEhEREb2M\n2b\/M1t48Ejd+J1bcWNYcWvv4nspivaPcv4WEhOKC1wXDve3fmDZ1OvvK0vOL\njhUrc4+fSISHhRvrM0Ua+\/3MmjlLe1ulcE+JvHnyosP7HbF37z7rHz8RERER\nERE9FxnrhYaEYsbPM1C7Vh24u6XQXsdFChdF9249UK1qda1f7eDggPbt2uPi\nhUt4GPjQ6sdt60xxY1nTX6lCJc3XTp7MDdk8sqNB\/QY4eOCg1Y8xIZPrGxAQ\niJMnTmLN6jVaT33q1GlK8ucPHTiEy5euaM8tmSeb+fNMjB0zFr169lIdO3RE\n82bN8V6T99CoYSPUr9cArVu1xuhRo7F61RpcuXzFPA8SZYt5JG9K9LkH+Afg\n7NlzaNumncaMHR2cdF6ob99+uHTpEnSz9rESERERvaRfJG5s5xAj31jrVA8a\ngjsJJW5s+jx6k360\/g8C4HX+Aq57X7f+MVLCYoobR1iw6BMka0slhiy9jMuV\nLa99r0oWL4mPPhqDE8dPWP\/4iYiIiIiI6LkY60yFa5xtyuQpyJUjl8Y3JX6c\nO1duZMqUWfNkPTyyYYxh7GeKpVn7uG2dxDW9znvhqy+\/QvVq1fUauiZNhmQG\nuXLm1tik\/wN\/qx9nQhUaGqY11hcvWoyuXbqiefPmaNiwIRo0aKg5sZ9M\/AQz\nfp6Jzz\/7XP9do1oNzRWRmut5cudBgfwFULxYCfTq2VtjxaM\/HI1f5\/yqtdkl\nL8Oyt\/HbXKdazl\/WiRw\/fgIzZ8xClcpVo+PGjmjcqAnm\/joPt2\/fhm42cLxE\nREREL2PWrF80z9guiR3s7Oz0Y8GChTBs6PCYdaptmeVm+Lfcz0m\/Y4kfS+3q\n2M835ZJa\/bjJpsmYyBwzjrR8PMrwvorA+r82oFPHzsjukV3Hv5K7f+niJasf\nNxERERERET0fnUcwjP+CH4Vg545dqF2rNjKkz6A1aB0dHeHk5KR9THv26Il1\n6\/6Ebi\/7fS03G7gGr4PEja9d9cbiRUvQsEFDvZ4O9g76Ua6nxDUPHjhk9eNM\nqKQ\/scTlR40aBTc3NyRLlgyurq5KempJznz6dOn1o\/zbNakrChYohBbNW2Di\nhIn45utvMH3az5qvfPfOXSVxfNnv2x4rVtHnLnOMZ8+cNVyr6ShbthzSpU0P\nO+35lwS9e\/XG\/n37ERgYCN2sfcxEREREL2nur3ORPFlyODk6me\/f5R5y6JCh\nCSNuHHuLivV5HBg3pmcV1zhJHosIj8SmjZvQo3tP5MieEy1btNRxwr1796x+\nzERERERERPR8Hq8bBs6dPY+PRn+EEiVKmuuyyRr7dGnTad7moUOHXzrfWGJz\np0+dxrWr1\/DA74Huz9rX4HWQuLGc35nTZ3WeKUO6DHB2ctbrmdQlKSqUr4Af\nf\/jR6seZUIWFhMHnpg+WLlmKHt17oHXrNlp3ukWLFlqHetAHg57w3f++x7q1\n63Bg3wEcO3pM34eB8dVcf5vixoj7cX9\/f8PfhHOG6\/YdmjRuitSp08DFOSlS\npUqNMmXK4qcff8KN6zcQGhpq\/XMgIiIiegVWLF8R3aM1hXEdrb2j1qmWe8nb\nth43ftomz4m+xzX2qDX2qTXV2bH68ZPti8QT46SoKGPvq00bN5vjxt27dsf9\ne\/e1H5bVj5mIiIiIiIiei2W9Kd9btzWu1qplKzg7O+tcicSO06ZNi2+\/+Ran\nTp7SGlQvHDc2fK8LXhe1fvCK5Suxb+9+ja1KnWxrX4dXTeLGcl5yrSRXs3ix\n4pq7YIrHi7Zt2mrObGBAoNWPN0GJNF7fh4FBuHzpMv79dzfWrFqDZUuXYeWK\nldi7Zy9Onzz9BMkpft7vY\/Vzfd0st+jH5D0rczwSV587Zy7q1a2nedtaq9Hw\nNyFP7rwYPeoj7NyxE8HBIYl27QcRERG9fXYb7isHDhiIPHnyGO\/ZkyRBzhw5\n0bdPX9z2vW3143smT9sMzwkPi0BocKjWnJL+L3JvHWXt46YES+YTNlvGjbtJ\n3NhP31vWPjYiIiIiIiJ6RtExMXPcOEJiRWG6LlhqKGfzyKb5se+88w5SpkiJ\nQR8MxtbNWx\/nG79ITM3wmm1btqFSxcqoVbMWBg8ajD279zx\/PC8BsIwbL5Fa\n1fUbIlXKVI\/jxknstH90xw6dtKeutY83wZD3q9RWD49ESHAogh4+QkBAIO7f\nv4+7d+9qLTSJwz8KevSExLg+4aVZbtGPSd8772ve2u+5RvWa2uNc6tWb6jWW\nK1tOa9rfvXtP61hb\/RyIiIiIXpGrV67ijz9Wodl7zZDZcA8kvU5q1KihPU78\n7vtZ\/fieWawtKipK7\/H8\/Py056zEx7d77sChg4dxy8fXPG6x+nFTgiTvnUMH\nDuGrL75Co4aNMH7ceF0fHsa4MRERERERUcIQHXszkViw9CTyfxCAM6fPYNCg\nQdqDV2JFWldZ5kuq18AXU77QHER53ot8X4lRb\/hrA\/LlzY8smbOgaJGiWlN4\n9i+z8c+uf5TkNMtaflusaSUx9fPnz2ucV451x\/Yd+GPlH1i44DeDhbhy+Yr5\nuZZx4+PHjmPa1GmoU7sOMmXMZK7\/LfnHObLlwMgRI7Ft6zbN5bb2OSYE8j6S\nunphoeF6jSMiInQuzLzZwDEmGJab4d83b\/pgx46d+Pqrr3W+VGrUS111U3+\/\nfPnyYcCAAbjufV3nHq1+\/ERERESvUEhwCHxv+WLK5CmoW6cu8ubOq\/fqnts8\ndR2itY\/vuVhscr8sa3UPHzqMJYuXYOyYsfho9BjMmzsfZ06d0fgea1XTCzOM\nz65739A14l9+8RUWL1qMAP9ArtslIiIiIiJKICxzjCVvU+qUyZhO1tfP\/XUu\n6tSpozXZJE4kOYYSN0qfLj0aN2qMX2b9orHTF4kZSQxV4qPVqlZDlixZtRa2\nxE+rVqmK4cOHK6npvGvHLo3B3rlz10xitgH+AQh+FPyf6+GjYnnaMUmsVvb5\nMPChromW+ZQ7t+\/ESXKjJQdT1k\/LsUqfsyaNmqBalWqoXau2xpFN+7WMG8u\/\nb964qXkK1avV0Gsq11Zq\/ko8LrtHdvTr0097Pie4+SirvYej9BpL7Fh6Het1\nNm02cHwJhnww\/KJIj2LJ2d7490aMGDZC+\/o5O7tovQEnR2e4JXdHunTp0KVz\nFyxfvgKBgaytTkRERImPrKeV2PH+\/ft1XegnEz\/Ftm3btKaNxF6tfXwvSurx\nLFu6HEMGDdH1wAUM93oNGzbC4sVLtG8O843ppURCa57fu3tP89lvXL+ptczY\nz4aIiIiIiCjhMMWOZY7AVMP35ImT6NO7LwrkL2Du5yV5x\/nz5kfqVGmQPXsO\nzZldsmSprieWmHPUc9SrlrkIqX\/7+8rfMaD\/AJQoXgIuzi6GfafWvmGierXq\n6N2rN4YMHoqRw0eaff7Z5zp388+uf+F91fvx2mVT3eIIU950xGOGf0dGmPKq\n8URtbXnc56aP5g+vWb1WY9ZjRo\/B8KHDMXjQkCc0adwERQoXQe7cefRY8xg+\nli9XHh3e76Drqs+eOWved+y4scw\/Xb50GZM+n4RcOXPBPbk7HB0c4WjvqPXv\n8ufLj44dOmK753arvzcSisc\/96jneh+SBcMWFBSEU6dO6e9Y0yZN9b3o5uam\n\/Yzlb4CsGalft77+fsjaCO9r15k7QERERImWrKmTmtQXL17UcYKvry90s4Fj\ne1FyPt9\/9z3ea9oMefPkRfFixQ3jvj7Yt2+\/4fxuG\/sb836aXlQc42yO0YiI\niIiIiBKY6HirzBFITFPybNevX6\/5sFKbVmKZhd8tjAb1G6BNqzba30vyjjNm\nyIgRw0fAc9t2c1z0WceD8lyJUfv43MLaNWs1htqvX39d616saDFkz5Zdv6fk\nI5csURJFCheNVgQVyldEi2YtMHDAB5j02STM+HmG5j7PmjlLzZwxEzPUDP2a\nMvxbHjc9R82yYPj3lClfYMjgIejSuSsaNmiEMqXLoHKlyqhetfoTJGb+XtP3\n0LVLV62v3a9vP3w68VMsmL8Qe\/fs0\/XVpnONHTc2+XPdn2jVsjU8snrA2dEZ\njg7GWuAuLi56bYcPG46dO3Yy7\/g53sdPsPYxJRBBD4O0doC8Jz\/79DNUqVxV\n35duyd00Hz5N6jT6eyjv9xnTZ8DrnBf87j+InleMsvrxExEREb02cW3WPqaX\nIHWVpv40Vde7ylhn6JBhWLN6jdaQiozuW2TtY6QELK4xGMdlRERERERECUtk\nzM8l1\/i7\/32nPbwkPpwpUyYMGzoM036ahu\/\/973GcyWWJDmyNavXxA\/f\/6B5\nihGacxz1TN\/T1E9ZtgcPHmicVWJQUrt6zEdj0LJFS9SvVx81atRE1ixZ4ZbM\nDclck8E1qYGLK1wMxyX5yc5OznAycHR0hIODw0uRfcj+pA6v5D1nSJcB5cqU\nQ9069Z4wedJkzTmQOm9PO9f44sbSv3nq1GkoXaq0npspbiz1gIXE7bp37a55\n2dJnjDE6eh0kF1\/q0s+ZPQctm7dE5oyZkSpFKqRKmVrjxfI3QN6jEz+eqO95\n\/wf+CHkUou9H3WzgHIiIiIhei+j1tYnpHjw0JBQnjp\/A+r\/WY\/68Bdi9ew9u\n3LihudVR0edr7WMkomcU33pprqUmIiIiIqKXEWssIX1NpXZ0xvQZNTYstWpl\nDfq5s+dw+OBhjB0zDhUrVNQYazaPbGjerDnmz5sPLy+vOPcXF51\/ia4bLTFR\n6akqn\/ve8tV5jN3\/7tZc261btmLO7F8xfux4dO7YGZ06dEJHgw7vd8T77TsY\nvI\/27dqjXdt2aNumLdq0bqNat2qNVqqVkn+3jv5am9Zt9bmxyT5kf5JTOXzY\nCI2dy3nLccR25vQZjXU\/S43e+OLGEn87deq0xt0b1m\/4RNxY8rylt6zkMs\/+\nZTb27z+AwMCH1n+\/UKJy5PBRw3vwR9SsURM5sufQuunJk7np+y9lipTar3vK\n5Cn6POntbVzD8LjuO+ciiIiIKNFKhHFjrfv0KBh379zD1avXdP2v6fHEdJ5E\nb4X44sOMGxMRERER0cuwHEsYNqnrLL2FkydLjgzpM6Bp06bar1d6GAf4B8Bz\nmycGDxqsuYhSx1Z69Ep+8IrlKzTuq3mIT\/melnFjWdse3\/NkX7d8buHggUPa\nC1msXLESK4Th+y0Xy5Zj2dJlWLpkKZYuXorFi5Zg0aLFWPTbIguL9fEli43P\nWbpk2RNkH7LPVX+s0t6tXl4XEBj49Hzip4kvbiyM6\/1P4n\/f\/g\/lypbX3GpX\nV1ftKf2OgeR6ZvfIrnWzP57wMbZs3oLr3tet\/56hBEvehzdv3MThw0fw94a\/\nMWXyF9rfLqV7Sl0nIu+5dGnTo0iRomjWrJmua5A849CQsBh1C835KJyLICIi\nosQsscVfojcZg0VGj0\/knk7GK6xR\/eR1ivOx2I8TvWlP69GU2P5uERERERHR\nmxUrbiw9ft3d3GFnZ4fq1avj++++h89NH\/2azCkEPwrWWKzkwrq7u2uN52Su\nydG\/b3\/ND36WfryW69njXNtuscmcRkREhPbcik9YmEFImMa2QoJDDccYosf5\n6NEjXU8v\/5bHJU4rz5OcySeEPd6ffL\/IyEhjTNt8IC\/mv+LGQuZnJC4vOcWS\nu+3h4RGdd5xE48fyc5B4nvQ8btu6Lf74\/Q\/rv2cowZL34rq16\/DBwEEoWLAQ\ncufKrT3LpU57kiRJNM\/43UKFMX7cBJw+dRoPHvjr74O+Pq7NBs6JiIiIiF6c\nMYb87D2HiMgGPCVuzHW+RERERET0wmLFjfv27auxYIkhtWjeQnNw7969Z36O\nxDmllrTUca5VqzbSp0uvcc0SxUtg+LDhOHr0GB74+f\/n94yKHsdY\/vtVnItp\nbCRk\/bwcqzA9FmWFNbfGY\/nvtftSs\/r8ufPYvGkzvvryK9StWw+ZM2cx16wW\nzs7OWke4Tp26ep3XrlmLy5cuI87N2u8pso7o97\/5fS+PWWxXLl\/RfP2ePXqi\neLHiuj5E6gqkcE+BDOkzony58ujWrRt++vEn\/PvPv\/q+fJZa7ERERERECR7j\na5TQPC1uHBHF9zURERERET03U8xW8oS9r3mjffv3NcdV4pR9+vTFnt17EOAf\nGGM8EhgQCK\/zXhg7ZixKlSwNB3vJOU6GCuUrYN7c+fA65\/Xf35c1k+J1wesC\npk\/7GQ0aNESaNGlhb28fI35sb2ePNKnSoFvX7lgwfwHOnDmjfWdDgkOM+zBt\nNnAu9AZZzA1ITXnJczfly0sOvdQ3l7runTt1RoH8BZE0aVJ9P0meseQb16ld\nF+PGjddc5EsXL+nvuLGWPPi7SkREREREZGtYp5qIiIiIiF4VGD+a4kzy8eLF\ni5g1cxaqVK6iPU4zZcyESZ9Pxs0bPggNDXv82khjznFwcDBWr1qNLl26aOxJ\naitLjeXu3Xpg8+Yt5u8RJ45h4iU1sx\/4PcDP039G3Tp1td+xZdxYYvpOjs4a\nO65QrgKGDBqC9X+tx43rN1hb7m1mMTegv9MR0e8Fw+bv7485s+egTes2yJI5\nC1K4pTC8h5z0\/SR9ymvVrI1f58zFsaPH4f8gAEGBQVrzPUbcOK7f17j6av0X\na18jIiIiIiKitwHHYERERERE9Dxg\/GiuXWT4b\/++\/ejSuSvy5smLlClSonSp\nMpgz51fNQ5Y4cex9SD7jubPnMH3adJQqWQqpU6fWurfFixbH1J+mag6sxED\/\nM95k7etgw6QW+Px589G\/\/wBUqlQJ6dKlM8bn7ezh6OCkseP0adPr9W7VshWm\nTP5Cf4Z3bt+1+rGT9ZnqCMjv7i2fWxg54kMUK1pM6whIXfns2XOgXdt22sd4\n8aLFOHXiFO7dvad1qcMNv9vmOtdERERERETWZtqsfRwJBedciIiIiIjoWZk2\nw+eSnyrx34iICGzatBllSpfV\/MOMGTOhZYtWWrNWa93G2ocp3hz8KBj79u7H\n8GEjUKJ4SbgmddV61b169sJ2z+3a5zjOHFiOYZ5Kfi7SV3rvnn34YsoXaFC\/\nAbJnyw635G5wdnR+QrGixfHJxE+wZfNWjRPK6619DvQGxd6iH5c4sNSfHzhg\nIN4t9C7c3d0Nv98Z8V7T97B29VpcvHAJj4KCERIcirCQMI0ZR8VujBxrn0RE\nRERERGSDWPeJiIiIiIieVewtyhhTknxiqUsrMeLixUogZcpUyJkjJ0YMH4md\nO3YiPDQ83vrHkZGRmqN46NBh9OvTT+OaTk5OyJ8vv\/ZGlj6pcR4Lxy\/xXhdz\nj1oDqRUsNauvXrkKz22eGDjwA5QoXiLOuLHkentk9UCLZi00B1xeZ\/XzoTcn\nrs3weGhIKHxu3sKCeQswoN8A1KheE4MHDcai3xbhuvcN7V0udejDwyK0L7L+\nrse3WfsciYiIiIiIiIiIiIiI6OXEtUVJL91wBAYE4tKFS5gxfQayZ8uBVClT\noVzZcli0cBG8zntpbPm\/+ubK1wMCArQ3cv169bUfb7JkyVGuXHmsXr0aPjd9\nzDVzzRg3jp\/GjqOMNH4ciQiD+\/fuay7xt998i65duqFyxcrI5pFdY8ZODk5w\nsHdAkneSIGuWrGjSuAnm\/joPB\/YfwG3f2wgLC7PuOdGbEXuLiv799A\/EqZOn\nsPHvjVr7XNYgXPC6oDnG8nXJTTfHjOPaj8X+iIiIiIiIiIiIiIiIKIGLvUU9\njvlKXrH0P03umhxpU6dFs\/ea4+SJUwgMfGjscxpfjaPIx\/ve\/e9ujPloDNKn\nSw97e3uNX44bOw57\/t3zZNw5kcWN5fxCQkKM\/Zxf1X7juUaS33344GFMmTwF\njRo0Qob0GeCaNBns7ezxzjvvqNSpUqNa1Wr45utvtE9y0MMgq18jeoNMm2kN\nQnQP87iYvq4iY70eNnAuREREREREIhHNIRAREREREdkiU7xz2dJlaN+2PZyd\nnJElc1Z06dwF3t7Xte9x1NP2Ex2b8vXxxe8r\/0D5cuW1R3L6tOnRskVLrFyx\nMs7XJKYxn1zDY0eP4fy5869uv7GvUfQmucP+\/v5aA\/zPdX9i7JhxKFK4iOYb\nm+LGjo6OGjseOWIk48ZvI9MW\/T56It\/fkqk2uuX7DbH2QURERERERERERERE\nRIlKlGWMSB6DMQ45b+48vNf0PTg7uSBH9hzo3as3fH1vI84tzv1Gaa7tkcNH\n0b9vf7xb6F24JXdDsaLF8Nmnn+HixYsICrKIXSayuLH\/A3\/MmT0H33\/3PVav\nWq2xWskL\/q\/63s8lnu2693X8ue4vtGndFlkyZ0GSJEnMsWMxYMBAxo3fVniO\n58azRuG59kFERERERPS6mDZrHwfZjvjq4hERERER0TPReHHE45q0+jii48bz\n5qF5s+ZI5pocuXPlRp\/efXD79rPHjU37unnjJhb9tgj169eHg4Mj3N1ToEXz\nFli8eLF+zfzcRHZvLz2E+\/XthzJlympf56+\/\/gYH9h9EcHCI1vl+6e9hefmj\nojQPXH5ut3xuYd\/efRg\/boL2O5b64BIvlvix5BwPHjwYJ0+cRFDQI6tfIyIi\nIiIiIiJ6QxLRnEu852dZMyv6MV2\/z1paRERERETPJna\/UxjjxrN\/mY3GjRoj\nqUtSZPPIhu7dusPX1xdPbE\/Z\/8PAhzh39hyGDxuOzJkzw9XVFaVKlsKoD0fp\n45bHkZjGMAH+Afht4W\/o1bOXnm\/FChXRoUNHzJwxC2fPnH2l30vqh2\/b5mn4\nmc0xXOcRqFe3ntaplr7SpnxjyT2WWuOr\/liF+\/fuax9ra18jIiIiIiIiInoD\nYvciSkws6uhFxRc3jrJ4HC\/5\/YiIiIiIErkoy\/towxYaGor\/ffsdqlapCidH\nZ+TOlQf9+\/V\/Mt\/4GfYdGR6J4EfB+OWX2ahWtRrc3d2ROVNmNGzQCNu2bkNg\nQKDxuYls\/BIaEopTJ09pXvXQoUP1WhYvXsJw3g3xw\/c\/wHObJ3Zs36ExZInj\nSk3vSMPPIDIyMt5a1pERUXotfW\/54uiRo9iyeYuaNXMWPhj4ARo1bIT8+QrA\n0d4R9vYOsEtizDUuUKAAunXtpjFj6YEcER7x6uplExEREREREZFtip5rMeUL\nJLbYcew6esZzlC\/+x2ZxXZ5gA+dERERERGQTLO6PQ4JDNB84X958cLB3QOmS\npfHxhI9x7949mLfn3P\/OHTsxYvgIZMqUCU5OzsiRPSemTZ0Or3Nej79\/IrtP\nl3rUEg+W2PjPP8\/QmLGLswvy58uPalWro06tOvhyypc4dPCQ9kOWHOAwA4m1\nx6ijFC08NBy3bt7C1i1bMXTIUJQpXUZJ\/2m5po4OjrC3s0eSd5LE8NHoj3Dy\nxCk8Cnr0ampkExEREREREVHCYZmLm0iYYsYyzyHzKCamuLGsy\/fze4DTp8\/g\nzp27Oueiz41+vjmObgPnQkRERERkyyRuLHHiIkWKat7qu4Xe1ZjvnTt3Xnif\nV69e07rNefLkgZ2dHdKmTaex6X92\/WN8TiKMG5vImETyilcsX4GRIz5E0yZN\nUbxYCeTMkRPly1VAyxYt0aVLV\/To3kP17NETPXuKXlrn2kS+1uH9Dhp\/lp9J\n6tSpldT+1h7G7yRBOsN1lVhyqxatDN9rJGbOmImDBw5qXJoxYyIiIiIiIkpU\nEuEcAj0biQ9LXTaJAUdECw+P0PX4wcHBOHfuPDZt3IQZM2Zi\/Z\/rtSac\/4MA\nhIaEGeuwMW5MRERERPRMpMay1FKWnFjJN86VM5exTrXv7Rfbp+E+XOor79m9\nByVLlISDgwOSJUuGZu81w6LfFsV4XmIe8\/nd98Phw0fw\/Xc\/oGOHTqhSuQre\nLVRY84WzZsmKNGnSagzY3t5YX9pE84aTxJQyZUp4eHioXLlyoVDBQihRogRa\nNG+BTyZ+giWLl2gt6wjGiomIiIiIiCixMW3WPg6yGnPt7eicY4kbS8xYar55\nX\/PGJ598qj3SKleugkaNGmPMR2Nw5sxZPAx4GLMPMqx\/LomO5WZ6LBHP9xER\nEREldlK7Z\/Wq1ejcuQucHJ2QNauH5rpKX90X3afcx588cRK1a9VGCvcUGjuW\nPsdy327t831TZBwjudwSP\/Y6fwHr\/9qAL7\/4Cr179UbXLl1Rt05d5M2TF8lc\nkz2uM50kCeyS2MHOzl5rUAvpX1yhfAX06d1HjR0zFtOnTtf+xYcOHsa9u\/cQ\nYBgnyfeKsoHzJiIiIiIiIiJ6lR7XqY56XH\/a4Pw5L8yfNx\/16zfQ+SxZp5\/N\nI5vORy1csBAXzl+w+rEnepabtY+FiIiIiF6axI03b9qsOcbOTs56fy21k319\nXyJuHBmFK5eu4MORo1CsWHGNh7q4uGBA\/wFWP983KnoLCQnBzZs+OHLkqPYr\n3rhhI5YvXY6pP03FsKHD0atnbyUx5d69jPHhvn366c9kQP+BmPHzDGzbuk3t\n3bsXp0+dhrf3dfj7+1v\/HImIiIiIiIiIXjOJHUdaxI4fBT3ChvV\/o13b9jqX\nJbkQKVOkhLtbChQpXER7su3ft9\/qx53oWW4WPyvmNhARERElTNLnxXOrJwYN\nHKRxY6mjLPHLGzduvHCPXIkb3\/a9g2VLl6N5s+bmGszSt9fa5\/tGxbFFGW6c\n5ZqHhYZpvaSTJ05h7559Rnv3Yd\/e\/TqukT7Fhw4ewuFDR3BLcr\/j26x9jkRE\nREREREREb4ApFhkaGoozp89g0meTkCljJiR1cYVrUldkyZxFY8YtmrfEtKnT\ncPzYCZ2jsvZxJzrxbXKpDdc7QvPBo4zXnjWriYiIiBIUyTfetHET+vbpCycn\nJ+TIkRPdu\/fQ+++gh0EvtE9ZVyg9Zg7uP6i5sxIzlvrLEo+29vnaAu3LI\/fR\n4ZEICnqk1yq2h4EPzSTGbO1jJiIiIiIiIiKyBTJX8sfvf+D99h3gYO+gc04e\nWT3QulVrjBg+Ej9Pn4GdO3bi5o2bjF2+DvFskn8i84xhIWGaMyG1xXntiYiI\niBIWWQN47NhxTJo0GRkzZETWLB5o2rip1q72uXnrhfcr9YIk9jx40GDt3cu4\nMRERERERERERvQyJA9+5cwefTPwUZcqUNde4K1WqFGbNmIUd23fg0sXL8H\/g\n\/3gdfmQsNnAeCZrFJnX1ZA5Q+t3duH4Dvj6+Wl9PYseM2RMRERElPHIP98Bw\nL71yxe8oUbyExo5LlSiF6VOn4\/TJ0y98fxf8KBjnzp7DkMFDNG4s3ro61URE\nRERERERvK8aL6DUwzTe1bdsOGdJnMMeNq1Sugg3rN+DSxUsaxwwPDzfGLS03\nGzj+xESur\/w8tmzeit69e6Nbt+746suvcOXyFTwMfLEahkRERERkfVJDxtPT\nE40aNNK6PlmzZEXHDh3x94a\/X3ifsfONGTcmIiIiIiIieoswbkyvgfe161i9\nag0qVqgEZ2cXc9y4evXq2OG5A763fI3PjW+zgXNIDAL8A+B13gvLlixDn959\nkTNHTp1TbNy4MdasXoNrV69Z\/RiJiIiI6MWdPXNW1wSWKV0GbsndUKRwEfz0\n40+4c\/sOwsLCn3t\/st7w\/DkvDB0y1Bg3Zp1qIiIiIiIi2wAbOAZK\/OKLG8MG\njo0SrP1792PCuAnImyev9kQzxY2rVasGz62euHXz1pN5xpabDZxDYnDB6wIW\nzF+I0qVKw9nJBQ72jnBwcMS7hd7FqA9H4cD+A1Y\/RiIiIiJ6QYaxnPQeuXjh\nItq1a2e4z3OAi7ML+vbpiz279+gaQlMPmCgRFaX34PoxCmaW+5S48QWvixg2\ndDj7GxMRERERERG9DSJjfc6esvSK7f53t8Ylc+XMpfNN5nzjatWxfdt23PKJ\nI25sA8ed2Gz8eyM6d+qMPLnyIHmy5HB3c9efwUejP8KmjZu01\/Fz75c\/KyIi\nIiKbIbWqHwY+xNixY5ErVy44OzujWNFiGvc9f+68fl3uu0NDQhH0MAiBAYEI\nCgrS+HBwcLB+lK9FaQAZuO17G7\/OmYuGDRpqrnGSJEnQqxfrVBMREREREREl\nWowb02u2edNmdOvaTXusvaP17ZIga1YPdO\/WHSeOn8CD+w8YN36NIsIjEBAQ\niGlTp6FQwUJIlza9\/izKlSmHzz\/7HNu2bsPNmze1f118+wgJCcWxY8exc8dO\ns2PHjsHP7wFCQ8Osfo5ERERE9Nii3xahRfMWSJsmLVKlTKV1q+fMnoNTJ09p\nXFnu+yRebIwbP4ozbixfP3L4CHr26Il8efPB0dEJ2TyyYdy4cVY\/PyIiIiIi\nIiJ6AxgrptdgyeIlqFSxks5ZSdxYaua1btUaixctRkhIiDFmLM+13GzguBML\nY1+68xg2dBgc7B2Q1MUV5cqWx8cTPsbxY8cRERFhzCmx\/BnE2sfdO3fx4cgP\nUb9+AzP599EjR3H\/np\/Vz5GIiIiIYKw\/HRGFUydOaV\/jIkWKwt3dHW5ubqhQ\nvgK+\/uprXLl0xbxe8Il7QIvt2tVrhvv1JSj8bmE4OTppv+T27dpj5cqVVj9P\nIiIiIiIiIiJKWCRXwfvadXz6yWfIkD4DnJ2ctU61o6Mj2rVth2VLlyEsLNzq\nx\/lawfrHIL3sdu7YpTnfkustfY1btWyFw4cPw8\/PDzE2i9dJ7cLjR49j1sxZ\n6NSxE4oULoLMmbOYVapYGePHTcChg4esfo5EREREZCSxY1nXt3fPPsN9+Keo\nXq0G0qROiyyZsqBq5aro328Apk+brjWBZG3h1avXcOf2HV1rePnSZXh6bseM\nGTMxZsxYwz1ja6RNmw6urq7InSs3Jk+awns\/IiIiIiIiIiJ6bqa444D+AzRe\nbPI8cePIyEg8NOzn0aNgq5\/PC4H1j8Hnpg9++uEn1KxR0\/gz+I++dFLT+uHD\nh\/qaA\/sP4Juvv338uliyeWRH+\/bvw3Obp9XPkYiIiIgei4yMgt99P+zftx+f\nffIZalaviXx58iFD+oy6nrNWjVr4YOAHmPbTNMz7dR5+X\/G7xpHnzPkVoz4c\njbp16umawUyZMiN5suTIn78A3m\/fAX+u+0vvE619fkRERERERET0CsS3Wfu4\nKFF6FXHjsNAwnD97HlevXLX6+bwQWP8YTp44iSqVq8A1qate\/3feeQc9e\/bU\nGoZayzC6nqF8lJjxubPn9Gcz6INB2svO9LrYZC5x0qTJOHb0mNXPkYiIiIhi\nioyIRHBwCM6eOYsVy1dgQL8BKFG8hPaMcU\/urjHknNlzokC+AlqLuljRYvox\nv+Hf2bPnQMqUqeDikhQZM2RE3z598c+uf3Hd+7q5xjUREREREREREdGzetG4\nscSKfW74wHPbdvz4w48YOGCg1rretnUbfG\/5Wv28niqOTXrHydzdbd\/bGpcV\nUg\/wTRyPxHWLFi1mvv7muLH0lZae5ho7lpyUB1p38H\/f\/g\/vv\/++xoVdXZPp\nayR2LHnHtWvWRq5cuTTvpFzZcli44DdcvHDR+teciIiIiOIUGBiIK5evwHOr\nJ374\/gd07tQZBQsURKYMmZA9W3akSZ0GbsndkcIthfYwTpEiJTIaviZx5MaN\nG2PE8BFYs3oN7t65qzFjqU9j7XMiIiIiIiIiIqKE5UXixoEBgbjgdQGrV63G\nkMFDdL7K3c0dhQoWwuBBg7F3z16EBIcgygbOL16xNjknb29vjd\/KnNvP02eo\ntWvW4tTJUxpLDn6NdbhPHD+B8uXKm\/tLS9y4bdu2uHTxEh4GPtS5P\/n++\/bu\n05hxzZq1kDlTZvPPy909BYoWKYrvvv1Oaxl279Yd1atVR5fOXbDdcwdu+SSA\nWD4RERHRW8y0hvHG9RvYsnmr5g83atgI7zVthpIlSmmNmYIFCqFQoXdRvHhx\nVKlSFf0N9\/BzZs\/RdYV37tw17su02cA5ERERERERERHRS4h8zWJ9vxeJG0tc\n+LNPP0OF8hWQKWMmJHNNBgd7B813zeaRDdOmTsPlS5d13svq1\/NZGLbd\/+7G\n5599jgoVKiB\/vvzImTOnyp8\/P6pWrao95SRW\/rqOweu8F95v\/z48PDzMcWP5\n3v369tN5wICAQJw\/dx4DBw5Ejuw5kMI9BZwcncw\/r2pVq+GH73\/EyROncMvn\nFi5cuKjx7jOnz8D7mrfGnq1+nYmIiIjoSZHGetXhhnvu0JBQXc+o9W\/OnMPh\nQ4exZ\/ceLF60BL\/Mmo1Fvy3G3xs24p9\/\/tX7V1l7eM1wryf3ilIPSGvVWPt8\niIiIiIiIiIjojQgMeIiLXhexa+cu\/PH7KsyftwDLly7HDs8d8H\/g\/0z7CAkJ\n1dii9NT13OaJlStWaszSMm4sceBaNWvh008+xY7tO\/DPrn\/MJk6cqDFjqZHn\n7pZCY8VCaiJLnuv6v9brXFdCmLeSHF6fmz746suvULFCJbi4uGjM1pLkUnfq\n2Bmr\/1j90t\/vYWAQLl+6gv379mPrlq1a11ssWLAQ1apVQ5o0aaPjxpJD7I4C\n+Qtg\/LjxGosfNnSY1qW2\/DlJnrHEjL\/84kudN5R5RsvvJ3nKQUFBOg9p7WtN\nRERERHGT++aIcGPsODw0HGEGGkcONsaRr165Ci8vL1y7eg337\/vh0aNHuv4z\nODgYYWGP48UJ4f6biIiIiIiIiF5QHPmh9PaR2J\/MDd2\/dx\/Hjx3HwgULMXTI\nMDSo3xAlipVAjeo1MPiDwfo16WcW3z4kRurn90B73W7csFF7pw0fPlxVrVI1\nRjzS3s5e824bN2xs+F5Dzc8TZcuUNT8vS+YsGkMWgwzHsHPHrjfWE\/hVkF7M\nW7duQ5PGTTRWbsr1tSR5vXny5MXHEz7W+tsRL5BHLXN4Mrd39sxZLF28FBPG\nT0Dvnr3Rp09frUHYulVrpEmTJsbPwPRzKFCggJLPY389a5asui+J\/9+9ey\/u\nfnaw\/nUmIiIiomcQV62gp22m11n72ImIiIiIiF4F2MAxENkqjv8pyhjb3Llz\nl9ZRbtmipfYTllrF6dKm01zYNKnT4N1ChTFsyDDNXY1rH\/fu3tP60j9+\/yO6\ndumqcd6CBQoiZ46cKnWq1DFjkkmSIHmy5EifLr1+L9PzRMoUKc3Pc3F2QaqU\nqVTtWrUxfdr011rP+VWT2n8fDPhAr5+9nYPm+caOG9slsdNa3O3atsfBAwc1\nfv+830fyRdb\/tQEjho1AyRIlkSd3Hnhk9YBHdK52xoyZYtSdjv1zEPJ57K\/L\ndW\/YoCF69eyFcePGaW64ry97GRMRERElOIjnsbgetxRPPxoiInoJcW3WPiYi\nIiIiIkr0wsMjEBIcqnmi0s9MckWFxCYlN3XD+r\/x4w8\/oX+\/\/ihXtrzGiiWO\nGTt+KHHNokWKYdSHo7TXmd99vxjf5\/Sp0xp3lhijR9ZscHRwfDJG+ZJKlSqF\nSZ9PwunTZ6x+XZ9G8n\/lGq9dsxYN6jdA1iwesLOzfyJmbCLnJzWiJTb\/7Tff\nYs3qNbh04ZLWBpefl\/Skk31GxTFnJ72F5bmjPhytMX\/JG3Zzc0eG9BmQOVNm\nZM6cJYaMGTLC2cn5ma651AqX\/O+aNWqiebPmWLlypdYvjHEMnEckIiIisn2I\n49+I4\/FoUXHlJhMR2RCZ4wjwDzDzN5CeVjdv3HwmN67fMIxvvXHp0mWcOXMW\nR48cw769+7Bzx05s\/Hsjfl\/5O5YtXYYli5dg8aLF+G3hIiyYvwDz582PQfpC\n\/fbbIn3uqj9W4e8Nf2vveOndde7sOf1e0hNAxu5yzHr8cW02cE2JiIiIiCiR\nit60dvQ9P\/jeuq2x3qDAIAT6B2oe7IzpM1Cvbn1kypgpzvrFcdUtLlSwkMaY\njx09hvDwxz1tpZduhXIVkDa6f+6rIsfg6Oioypcrr32CJd5t9ev7HyTGGxIS\ngiOHjmj+dY1qNYzXOEmSJ2LFEqOXc5Qa1kKvueF50stZxqSnTpwyjH8D9eco\nOcVREU\/Gjq97X8df6\/7SPsQSrxdSA7y64fvWq1sP9es3eKxefcPj1fXnFNf6\nAL3e0fuQ2LI8r0rlKvratm3a6hjY+5q31a8xEREREb0Ay83y8VgxYrnfNN53\nRln\/mIkoUZK\/L5GRkdqnybS+XXuwG0hf9f8UGqbxV1\/f2xrvVafP4NTJU8aY\n74aNz0Rqdq1etQZLFi\/FtGnTdS38sKHD0K1rd+2pVbRIUeTJnRfZs+XQWl4y\nrk+bOq3W5ZI6aSJVqtRImzad4WuZkTtXHpQsXlLH3VJ3TNaEz5wxS+PIMo8h\ntdOk3pscv64Pj5Q\/urE2G\/jZEBERvRVgA8dARPQGRBkEB4fgkcQZw6PHXIYx\nifTNlb7DmzdtwfSp09GzR0+ULFlSc09dXFyeiGdK3LF40eJwdnaJEVd0d0+h\nseMRw0dgy+Yt5u\/7uuLGUuu6Xdt2yhQzlnXE1r7O\/+XypctYvmw5unfrjhLF\nS2gt7qQuSeOMG0v97oIFCqFWzVoan5X60smTJ0fq1Kk1dtzh\/Q6YMvkLrQ8t\na5TjyvWQXHKJ5X48\/mPtoyx+\/OFHeHpu1zGzpXXr\/tRa3w0bNtTexbGvd\/Fi\nxfFe0\/fUkCFD8fP0n3WdtbxW1ktfv34j3h7XRERERJRIRMeOmWdMRK+LjOul\nltWxo8exd+8+7JDx6to\/sXL5Sixdsuw\/\/bbgNx3zjvloDHp076mk75Osm65R\nvQaqVqn6TGQMXqliJV2jXrJEKRQuXAT58uXT\/llSu0viwlKDS+qvubq66rhe\nJE\/mpl+Tnl4SRxbyuUiXJp3Gl\/Pkyav1wEqVLIUqVWQtdn00btQE\/fv21zG5\nzKdcunhJY8cyj8N1OkRERG8YbOAYiIjegNhxY6mDdNUwFtvuuV1jgB8MHKRr\nX3PlzKX5pppzmsTY5zZt2rR4t9C7qFO7Dlq1aIW6tevq2EjiiZILK72OZYwk\nsWSJKU+eNFlrLUls2tTHt0zpsjq+KpC\/gNY3llxbUfjdwjqGirPHbnQ9ZOlz\nXLlSZfNrxNAhQ7XWkziw\/4DVr++z8Nzmifbt2mtf4di9hGPHjXPlzI0WzVvg\nyy++xP++\/Q7Dh49AtWrVkTlzZtjb22vMuWL5ihg2dDjW\/7Ued+\/c0+sd+3tK\nPXKJ3f8651cltbDiOjav8174beFvaNq0aYy4scSvZTz74cgPMW\/ePCWxYqnb\nZa6jRURERERvD8aMiSgOsqZE1qU\/eOAPn5s+uj79+LHjus5YxpCy5jn2+mWz\nnTvNz5FaVjNnzMSnn3yGUaNGY8jgobr2ukP7Dlrr6r\/IGFriw0UKF4VHFg8l\nY1rT+FbqZ7klN\/ZuknkGmZ+QGG6Z0mV0zuFZ48qqajUdo8v3k\/XedevURaOG\njdCsaTO0bNFKtWjeEs2aNde4cP269VHT8Dzp9VSzZk19TY0aNQz7qYqypcsa\nvn8VNG3yHkaOGIkVy1fA398\/uqdYZJx9qYiIiIiIiJ7Zf40porcrV65i0aLF\nWrNYeuwmS5rMGPt1cjaMpZyUg52xRrKstZ348UQcOngYX3\/5NepEx43fMYy7\n5DX58xXQmLCpnrHERr28LmjsWPrwnjx5CqNHfaT5rhJ\/lD4\/Ozx3qM8\/\/Vzz\nZ2VNblxx43x58qFzp85Yu2ad+TXiwvkLCNM6VeFax8nq1\/wZzJ49B46OTrCz\ne7IOdGylS5XG+HETtKaWjBXlWs7+ZbZhHNnU+HNydIaLc1Jd3yzrkmUsLs+J\n6\/tK7Fhyy4XUyo7rObJ+YED\/ATp2tqxTLTHjGT\/P1D7Vpn0Y62ZFWf16EhER\nERGRDbHcrH0s9GZ\/7oaPUsP+ju8dnDh+En+v\/xszDeNImQdo06oN6tdrgNq1\n6mjer6hbJyZZwy5kjbrEcCWv193d3TDmddE5CiFrzU29k\/6Lqc+TaT285fhW\nYsb58+bXmG3nTl0w6sNR+Pqrr3WN9bq16565jrXYvHEztm7dhp07d2G3YTy+\nf99+HDp0GEePHMXxYydikMcOHjiIf\/\/Zjd3\/7sbe3Xu1X\/K\/\/\/yLTX9vws\/T\nZ6Bb127IlSuXHl\/P7j1x\/tx53L\/nh7CQMOYcExERvW6RcbD2MRERvUIypoi9\nHjUqKgpBD4N0za\/00JkwfoKOy6TXTvJkyeHi5GImschsWbOhZYuWGquU8dOR\nw0d0zCJrXyUf1cHBQXNj5fNxY8ejebMW5rGY9Pr5yDA+lLXFEmeU9cYH9h\/E\npo2bsH\/\/AXPvHvH7yt\/RsUNHZM6c5Yk8Y4kZjxs7TtccS71l02tEfDFSWyHr\nrK9cvqL9hadMmoJBHwzWNcnPWoe7Qf0GWLJoibEGdZSxN7KMG\/\/44w+MGT0G\npUqWNv+8JBdc1l9LrfFbPree6zjl5+NjeM13\/\/sOBQsW0veCKY+8dq3a+OqL\nrzR2LfF\/a19TIiIiIiKyYZabtY\/lLRb8KBh3bt\/R8aPUm4rhTEzS70kel+fK\nuE9qef3555+YOXMWPpn4CQYOGIjevfugV89e6NWrt0Ev4+eWLB7r1LGTziPI\nXEOlipV1bkDWJmfOlEVrNMt688eyGL6WU2uQST3o6pK7W60GKpSvqH2dpA+W\n5ANLryzpUyX7ktplQta2y7p0+Z4fjf4Ikz6fhB9++AG\/zPrlP82bO097R0nN\nLplnkPM9cfyE1t+6fu26jr+fleRUy\/j7tu9t3LlzF\/fu3sP9e\/fhd98PD\/we\nxCCPydfk52Jy9\/Zdw2vv4Ob1m7pOe8niJehjuNbSG2r4sOHak1n2GRYazrgx\nERHR6xZX3JixYyJKBIzx4iiNMcpaX9PfNsnJ9fcP0PWvso5WalLLOCxpUlet\neSxrciWHNVXKVFqnukL5CjreW\/TbIvO+JcdU+td269ZN44qmesoyltu0cbOO\nKVO4p9B9SS9j6Wks9ZGfdswHDx7CZ59+hrx58saIm8o4UsaBEmu29nV9VlIn\nWuKrMnaUsefcX+dqP6VCGo91i3F+Ep\/VNdRu7jEel3XR8rXePXvj6OGjMXs2\nGzYZcx4\/elzHkxKzdzX8DCXGK5+PH\/d\/9s4COqq7ieJfcXcJDsXd3d2lLS3S\nFile3GlxKF7ctZTiDi3u7hJcEyS4SyCBJPO9e3ffstkkECCwAead8zvrb5\/u\nvvnfmTs9Ze+evW+1zJj\/rl27pVGjRrZlwHEAr64\/h\/0pR4+4ik8QNcqKoiiK\noiiKonzh2I+nOU7OXrZPDF8jhofmC33R4+o1mz6JHkHubu7UNsE5cPachTPQ\nhs9R\/4XOePToUfo9Iz8bfX5HjRwto62MGjnKPyNGycgRlvujjfeOGD5Cevfq\nbcSwjeilnPrr1BI5UhTGqIz\/rX2s7Pst4bWoRvwKL2h4PydLmoxxblBgnunS\npmPuM3RgaMRVq1RjHnTbNm3Zj6pd23bSrk07y631Pp7v1rWb9Ovbj1hqhP+S\nTRs2cb09rnrIkyehO7fcxI994v3ssIy3oKcxPLqxP6Bv4zHGF+Af5sdGx85f\ndkVRFEVRFEVRPh2gE6PvDbRLYPMjNqYHDx6I69Fj0rp1G8mTJ6+kTZNOYsIX\n2tpXF7fQH\/E8YkT0DEbcaa9Zoh+y20V3qV2r9ivd2Pgc9MXDhw\/TexqextCO\n30Y3vnL5iixetJg6tr1+irxieFrv\/0R6FwPEdIcOHpLFCxfTYxp509ge8NQK\nY8TT9usHb2\/UbufI7n+9oeVj3Yf\/OZw1y46+0ngM3+qZM2ZK1cpVWZdt1mcj\nRxs51G+zzNC4x48bz9picxkKFSwkE8ZNYM4zlsHZ21VRFEVRFEVRlFDI6zRj\n+8nZyxnaseqI8CNGfLxj2w7qhnNmz5W5c+Yy1h4+bDg13Z49ezFfGL5cv\/\/2\nO72oQOeOnaVF8xbsGYW+Utmz5ZAECRJIvHjxJH68+MEmbpy4jGExPgBfaHuP\nZ1MrxnPoWYUYF\/5XiG2LFysu1avVkMaNmkiH9h0Y63bq2Ek6GvC2Q0fSrUs3\n1gbDlxm679Ily2T3zt1y4fxFelzfuXPHX02uv\/pca00vQP0u4m\/ktiM+9jcG\n8gkCWRheYBh34bo9eszHL1\/4aB63oiiKoiiKoijvBNNPrbXGiJkQWyAv9fr1\n6\/SZbtOqjeTJlceIA+NJtGjRWBcMPTNhwoT0g2rZspWMGzuOXsfubu6Mv+zn\nDw3xj\/5\/UBs2deM8efIwboWH9IrlK6RalWqSIH4C6sbQMJctXc5Y7nWeSvCb\ndj3iSi8rxKlmPIp5QL9cuWKl07ft64CvFPyt5s2dL4MHDZGG9RtKlcpV2J\/Y\n9Hz2V08cNqzkypmL9dwD\/hhIjy3719HnGf2dZv8z+7XfCw+x6dOmS+WKlZnT\nHSVKVMmSJauMHTPurZYf+ep169aVZMmSc2wAeeVDBg\/h\/lZvakVRFEVRFEVR\n3sibJmcv3wfm1q1bjM8APL7QFwpaL\/r7vokJ4ycwZ3jggEHSu1cfadumnfxY\n90cpW7asVKhQgZQrW04KFyrMGDO3QV4jhsyfL7\/Nsxn34RmG1+F1hdgO9b8R\nI77qCYy64K+gAX\/1FR\/DYyp5shSSJnUaxqdlypSVunV+lKZNmkrzZs3pb9Ws\nSTPLrY3mtvvQqFEL3P33HjJ61GiZ9fcs1spu3LBRdu7Yyb69YOdOy308B\/bs\n2iOHDh7mtkIsCp383t37mq8cBJYxHj+nL4eiKIqiKIqiKJ8g1gn+RfA4gr8V\n+uygbw96EqGXUPSo0elpDM0X+mT69OmlUsVK9CM+eOAgc1uDmj9qh1FDDD3X\n1I0bNGgg27ZtY10y\/KTr12sgSRInsfgcZ83O3siXLl1+Y94vfLigVUK\/htYa\nzohjTR114ICB9OWCFu7sbYyY7Rm36x32aIYfFnTtju07SuVKldl3CXG5o1aM\nfGz4gMN7O1euXMwHh2dYDyPGdqyzxns6tOsgW7dse+PyIM7u07uP5M2Tl\/NP\nkyat9OvbnzXEXl7eb\/w8cgMQu6MuOkaMmPQJGzl8JH2wnb2tFUVRFEVRFEUJ\npQQxmXnMPj4+ltxh2wvvh22+RpyLXq+oL4XOiHjG86kn49gnweHxE4L8WMSg\niJfhA33ZiFkvXrjIPr+I8Y65HhPXo67BZvmy5czBBojPGjdqLKVKlJI8ufO+\nlkIFC7MHMOIx+DcjHxjxNHKxEa\/HjBnTRqxYsSR27NgSJ04ccUnowveibzB0\nX2jF0Izh+Vy4cBHmcFv0ZNzmp+dYzpy5JHv2HAbZmf9dvlx5+fHHn1gf\/JsR\nn04YP1HWrFkr+\/btp4cW+v7u33dADoD9Fg7uP2i5bzx3+NARepQhVr979x73\nAWJ223539jH6mWB6WTt7ORRFURRFURRF+bSBdoz+Pqv+Wy01v63JnsXwmqKm\nafWmRpw4aOAg6sqIjxHnIb4Pap5voxtDm0aci57HR48cfaOvEuJLxJtTJk+R\n3DlzU3c2ddQiRhwNTRlxvbO3q7f3Czl7+qzMmjmL6wovLnhKQ+vFMkO7DeDj\nZYDtDk0Zfl0Yg0BO9ZrVa+SbGt8yx9v+vYj5kaMdnFpfe90Y+eP4fuSiTzRi\nfnzHmz6PHG+MbaDPFNZl9KgxcuL4SY69OHtbK4qiKIqiKKEcXwnap9jZy6Z8\nWIKYvLy8GFc+eviY2i71Lt9gzO81YB7w0Xrm+VwePnhEL2P0\/kXv19Onz7Af\n0wFTz3wD0EH37tknW7dspScXaoL\/HDacfXOhnyI+K168BOtvs2XLHmwQ65n9\ne6Hnos8v4m\/kRL+ODOkySNEiRS11xLlys264QvmK9K9CvI4a4DKlyzLGQ753\ntWrV5NtvvmU9cpPGTZi\/DE8w1CzPnTNPNqzfYMTfrow5AWJx6NrmY1diPD52\nXE5Z632hlyN2RO4x\/JGhq2MfPjV1dqvmbnuOz1vu23tEI+ZXfVNRFEVRFEVR\nFCX0gR44iPkWLVwkDeo3YN5y1MhR6UGcOHFi5hdXNGJO1Lsivr5x\/WYAT2p7\nEPvduH5DZkyfQf05apSoNt341xa\/Mhb19PT0pxvjdXhgo98S4nPkhQdn2U+d\nPM08Z\/hdwbe6aNFiRuz+DWuO0cPImdv1sREzQ2cdNGAQ43iMCUQNxIfaBOMA\niP\/xXnhXw8Maftbm\/HAffadQB27\/OYw7ILYPzjIhNwD7BWMJ5uehIffp1Ydj\nAG\/6\/LWr12Tzpi30RPtrxkw5fuy4PHn0xOnHsKIoiqIoihLKsfZjtemCjpOz\nl0\/58Fj3M2I9b29vefbsmdy9c4\/5wJfcL8vZM+eM+OKEHD54WPbt2efPq\/hN\n7Ni+Q7Zv287c5dWr17AH7ux\/5siUyVNl5IhR8kf\/AayRbd+ug7T8taWDl3LQ\nNG3STJo0bso4udYPtaSyEasVM2JOeEChbjdhAhfGcfR0DiLOQ1wNbTh5suSS\nLm06+kMXKVIk2MCnquZ3Nclv3X5jn9+xY8cyn3fSxEnsVzRn9hwjPvtLpk2d\nTg+vGdNmyD+zZsv8efNl8aLF7BEFL+ytRkwJ3zDEqaiZvnfvvkXDNfaJzwsf\nW3\/cT7nvr6IoiqIoiqIoivLuID68e+cutUD0JYoRPQbjWtShxogWgz7QHTt0\nZC9e6IqIKdEr53V5wZjnnt17pEvnLtSCESujnjhq1KjSo3sP9jbGOMHatevk\npx9\/lsSJXunG+Aw+G1zdGCCmRc7zOmN+o0aNkhHDR8jCBQuZ6+zMbQvtHDXC\nGBdA\/XCYMGH9gfWNHi06c8vhGwbP5+6\/d+eyw+fLrB9GH2p4qiHOL160ON9v\nrzWj7hfeaMFZJuSD7965W36s+xO9vVHrDD8y1HnDR\/u1n\/f9CISCc0JRFEVR\nFEV5S+ynIF43e27aYgnHydnr8BEwvZN9g6izNHV1Yv888fP\/uj+C993+vZtf\nMMZAryLTtxl5r\/CFQhzy4MFD+jchFxfx4p3bd94beDzfunlLPK54iNsFN2qX\n8DHesW0H\/ZOg88LPCDnAiBs7dezE+lh4ML0J6MFt27SlxlunTl2pWqWalCxR\nkn7LqO2F3xN6MIW362\/kr0+QEZ8hZo0QIQJjYeQ+IzaGJ1acOHHpoRU\/Xvzg\nE99yC\/9o+E1VM5bnm+rfSIP6DenhhZg1uCA+xPYBl9wv+T\/nrPsW+9Os28b+\nQyyM\/Yt97RfI6Wb7uC96Vvkyzsc8vJ9789b2Ob9X36MoiqIoiqK8JzournwO\nBHa86jH8+WDsS9QZb9ywiXnUmTNnkXDhwjFXOq4RG+fKkUuGDRkmu3bskktu\nlziOwPGGN+jGL1++lGXLlkm9n+tJ+PCWuBzxMupo586ZKw8fPKS\/9bKly1jH\njHga78F7f\/rxJ1m6eOlb9SbGGIqn5zOORSCOdnd3p2b78i205w8B4vQL5y\/K\nLw1\/YQ23o8cY\/KWRsz516jSZN3eeLFm8hDny586eZ6xvbgPE7IcPHZa+ffty\nO2IsA7XboGqVqvLPrH\/ovRbcZcK26f57D0mSKIkxr4hSuFBhGTZ0mLi7uTv\/\nmFQURVEURVE+TYKarK+beiU0qkB149d89pPFYV2gxyEWgmcvrsv9TEGP28eP\ndZ4vvF5Y6z99bRqzqeu99H7J16HtES9vu\/pQB\/3Y7nsxjxcvXsizZ8\/5\/fCP\nQm0vYgzU6sIHCv12EZMgtkC96uhRo2XwoMHSp3dfekJBw23bpt170bpVa2nR\nvIU0atiIcd\/3333PGBFeSMWKFKPXc8YMGVmTi\/jJ9HEODujbC1DXC40YcRNi\n2pgxYjH2ihQxEnXhAD2CjMdhw4Qz3hNdXBImosaLvF94PCPHuXXrNtKrZ29u\ni+HDR8ioEaNk1MjXMVrGjB4rY8aMpV8XaoL\/mv6XrFyxUtatXW9s711y8sQp\n5uy6u7mL+0V3cfOHm1y8YHJRLly4wH7Kd+\/eJajRDuw8of5rxNiIxQHONV9f\n31fHWGCnlzWPgMcWdGOrdszP+vi9Gvv5HM5FRVEURVGU0IBqxsrnih7HnxVH\nDh2RYUP\/pM8Wal\/DhAkjsWPHofdWr569ZPeu3axR9fZ6YfOqel3PKYxd3L59\nm\/FxhfIVqEMjHk+RPIW0bNGSOdKIdR8+fCgTJkyQzJky83tRexsvXnzWNm\/Z\nvPWt6o1DKxi3efToMftG9ezRU1q0aEHg1f2rsS369+svC+YvoNZ969Zt5t8D\n5InbzwcxPMYZGjZoyPEO7COz53TzZs1Zm+z4maDAPvQy9tHIESOpW6O2HP2x\n8NjdzF1XFEVRFEVRlHeEWpTvK83Tct\/Ppn+y1tZeywrsc74h2\/cUGi1iGkdQ\nRwtN7n1BLxj0e3V3u0S97+zZc3Ly5En2hD148CC1WfTHXfXfapk9azZjAHgH\nL1y4UObNmyezZ8+hpzB650JjhG47dYo9U2XK5Ck2Jk+abGPKJPP5qXwf3ztl\nij\/wvokTJjJGG2Fc9w8aNIj1vIi94Nnc6JdG7H\/73XffSY0aNaRSpUpSqmQp\nKVSoMPvoZM+WnbED6naDQ5ZMWYzP5GAecp5ceehvVCB\/ASmYvyBv8Zj9gLNk\no06cNk1aSZUilSRNYtF8AwO9jeDzjD5I0HZzZM9JfbeksZzQeNGrqE7tOlLv\n5\/pcH\/TyDRZNmtKPuk3rtuxZPOCPAdR7Z86cyTxn+F6jxzF6\/aI++szps3L2\ndZw5S58ucO7cOerDly5dZr42PKEfsw7Ymxqvedw74mviY3e+hOR5KnbnnI+f\nNZ\/DktPh4+P7yhNAdWNFURRFURRFUZQvBsSeGI9BXnnd2nXpuwUtEp5cObLn\noGbs7uYuT58+FduEz74hbwDjL0ePukrXLl0ld67c1I2R0434Hjnq6FGFcRvk\nTsOTGjoo6ptjxYwt2bJmp8aKuuGQHCdyCr6vagaeP\/MytqMnvcIANF7Pp8\/4\nvLe1nuClNU73F6NbQc73zL9mSo3q30jUKNEkfLgIzIn\/3\/++4jjPsaPH6C0X\nvP0unD\/6YGEMCLn36JkF\/zPUaTt9uymKoiiKoiifBoHEBcibND2QLfWw9rWz\nfgH7GtvNy\/5z9j659t7KlprIF8ED8\/LyFi8vL2q7rq7HxNWIU44eOSpHjhwh\ne\/fslXVr1rHfzfq16y333wLzM6v+W0WNEXrwP\/\/MlilTpsqoUaNlyOCh7KkL\n7+Sff\/yZtbW5c+eWQgULUfPMkD6jpEieUhK5JGatK3rlwovJrI+NED4iiWgQ\nKUIkPod4DbmfJpEjReFreB88mBF\/meAxCf+hiMB+PI7EjR1XkiVJZsSAqanx\noh8PYg+sd4niJaVs6bJSrmz5YFO+XAVqwzWq12C\/nRbNf2UN8NgxY9m\/d+P6\njcyHvux+We7fe8D97tR4MqQn8\/wKJFYMLqZvWJDnsta6KIqiKIqiKIqifNFA\nZzx\/7oL07tVbMmXIRD0SYxT58+WXIYOHyO7du6kZY2zmbWLuO3fusD\/xD9\/X\n4vxMH7CMGTPS6+zE8RPyzPOZnDp5iv2noBlDr8Z7CxcqImvWrOXYjt8HWOeP\njTnO5WOOc1k9w0zfMB+7Wgr2K\/PzC3S9X6cbt2rZSo4fO0EdOjjLhP5lqIf4\nrdtvHJ9CnXfRokVl5MiRr3plKYqiKIqiKIqJBO991Hdf+rKWEtec0H+p\/fo6\nXOfaTfa9eS15rX6v6o2tNZbwVYZ3LzTe1atWy\/x5C4LFjOkzZPTI0dKvbz\/W\nkbZp3Ya1qKhLLVu2LCldqjR9lt4X+Peg9wu0YMRT0Ehz5MhJvRT1tMihhf8S\n6mZjx44tcePGJdGjx5AoUaJKpEiRDSy6cMSIEW29g+AzBMKi7274CPRZxmt4\nH\/ruJnJJJF+n\/FrSp8sgWTJnlbx58nF5ypUrb6znt+yJU7tWbdYSo4cQ\/It+\nadhIGjdqzFrbpk2bSbNmzVhv27RJU4LXUK+LXjt4f4P6DaR+vfr0bEbf4Nq1\n63Ce5nzxOj4P\/2mA+7179pYxo8awBnr2P7Nl6ZKlsmb1WvZHQt31tq3b2J\/n\nbdixfQdzkPft2Ue\/JcSVqOlFnTd6JiN\/GTGu6ZPlzHjS166XN\/F9fZ+nYKO6\nrqIoiqIoiqIoivKBuH\/vvhGvb+f4AXo5IT8d9b6tW7WhNzX66+J9pldWcGNU\naJL\/\/fuflChewuZRjTEQ1LQiDx+5\/o8fPaG2jDEJs68UdOMihYvI5k2bnb5t\nQoQQmry94ft9h+Nd+fMVYH0BagagHydPnpxe1+iDhRru4O33B+yp9fNPP0uk\niJE5HoXtPvzP4drfWFEURVEURQmIBO991H19fHn9imtT1voat7zvban7hZ7s\n6ekp9+\/fFw8PD\/Z5PXjgoOzatUu2bN4iGzZskHXr1vEWccG2bdtlyeIlMnbM\nOGq\/0DqhhQaHKpWrSvFixanfZsmShT7L0G1Ry+uvv21gfPUVr5MjRozE98eI\nHoP+TPBKRv9c6MAZjflhnlkyZ6HnMvRi5MEGS2suVkyKFy8uJUqUkJIlSkrJ\nklaM+3gOsRRex\/vM98I3umzZclKxQkWuG3oDQwdv3rS5tG3dVjp36sKc4MGD\nhrC\/7vRpM2T2P3Nk3rz5smjhYtZDr1i+Ulau+Ff+XfmfEbOtYnzmD+M5xHJ4\nfeXKf9krZ8XyFbJ82QpjPyzlfBYuWGgDXtuY59o1a2X9ug0E97FP4c989cpV\neknBc+lt85E\/ZQLoxj5+\/nMk3rZe+C2\/38xfNr\/zbXH29lOC3qfOXg5FURRF\nURRFUT5fkJONsYNqVatZxkXChjPuV+d4wI0bN2w+Vm8bN6Kf06QJk+hR\/T\/r\nuEuihImYi+5+0V1eeL2Qe3fvybIly+T7mt\/b6pHhU40eWPB6+yzyqN93ss7n\n3r17cmD\/ASlfrrzFdy5seO6rJImTSt06Pxr7cLk8efQkeP2gje3qccWDtRdl\nypRhf2RQoEABGTRwEHuxOX27KYqiKIqiKKELCeJ5+96nDhPqheGZgxrQWzdv\n8\/ofuZDXr92Qy5cuU1dcasQif\/T\/Q5o2aUZfnaJFi1F\/zZolq+QyYgn01i1X\nthxrd9HXFvotam5t3svBAPW5YcOGpQbM+l3EHtb4IzDM2AQ1vqjpRW5r6lSp\nqQ\/DY7lateryQ80fpEmjJtL99+7Ss0dPrsO4seNZVwuNde3qtbIuKM9rqx\/2\nhvUbZNOmzay7RR0t8joB7kMr37J5q2zeuFk2bthIDR3vB6izRX9d9tg9c471\nthfPX2Rf5cuXrshV41r\/msd1uXH9Brc7coVRg4v+OKgDt9SCe9H\/6enjp\/L4\n0WPmCwPcf\/L4qfX9z\/le1O4ifnvp\/dLYnw6g104QIDax1I2\/6tnr9OM4NGBq\ns479g0Nw\/mKdv60H0rvwOcTjnxnsQ21fR6\/7SFEURVEURVGUEAY53ydPnmTP\n4WTJknNcpGiRYjJyxEjWndrnQwcXfAbjIFUqVWEuvzn+Ao0THmeoNcYYEubf\npnVbyZwpM8dtwoQJS0+3USNHybmz55y+bUITGGPbv2+\/lC5dhuNY8KfGLeoc\n4B+Hsadg5e5b9yV0fdRq5MyRUyJEiCAJE7pI48ZNWN+B73L2+iqKonwwjOnM\n6TOsXwPQLTg5e7kURVFCI2+YfHx8GE9Ap4Rf8BH2DD4qR48elVWrVsuUyVOk\nZ49e7KnSsMEv9DxuUL+h1PupntStU1e++cbiFZ07dx5Jny494xHU8qZMkZLe\nzvny5WdsgrpbxAm4doV2i165Jjmy55CihYtKhfIVmI\/aqFEj6dKlq\/Tr15+g\nD8vUKVPfmenTZ8g\/s\/6h5\/WihYtYe7t+\/XrZtHGT7Ni+kxruoUOH2C\/59KnT\nzMG8cuUqdVvEPa8Duu7NGzeZy3v71m1q6sS4fwsYz+N1vM8e6MDY7q94Kk+f\nWLReT89n1IOh+T5\/\/px13tDuHfVbS\/3rq37Rjnove+n4+PqrV3X68fgpYk7m\nY1ufYfGn0XJfWOG+8gmqVtlOfw9ssvseP7Ofsa\/FH\/5tCXT5PwBm73Icpzhu\nkQ\/98MEj5pvcu3ufteo4D\/A7g55K8Ku\/eOEicyVQz468iXPnznEMAXGuJafi\njHE+WsB9cBZ5FsEE7z954qTs2rGL9fTotfX7b7\/Twx1+Bybwdx\/wxwD6JnyM\n4wn7BecnzvXgeo0piqIoiqIoiqK8DS9fWsZ65syZQx83+Kuh9hjarbub+zvl\nhOMzGFtBXj50aNQxQzfG2E+3rr\/J3bt35cmTJ7J9+3b2\/6JH3FdfUTdGfyzE\nfVgmZ28bp+IwLoM4edOmzVK8eAmbXx5049Rfp5Ye3XvIvr37gj1v1BBAK6le\nrQZ15yiRo7AX2oA\/BsrtW3foJej09VcURfkAYBwd43p\/zfhLOnboSObOmctx\nRoxTOnv5FEVRQh0OE67h4UmE63XoM8ePHzeuK7cY1\/6zZeiQoTJo4GD6I+M+\n9JXSpcrQyzlB\/AQSJ3ZcSeySWJIlSUZdOG3qtJIubTpJlw6kZ\/\/frFmzSoH8\nBaRyxcrSuFET9iLu0L6jtG\/XXtq1axco0HKGDhkmkyZOprYLTfeY6zHmBQGz\n746ifGyQK+3rExA\/Bw0YIAeDer2dZh+QgHXbrOl\/8YI5AojzqLXeu8ecA4+r\n1xjTX758Wa5cuSKXLl0SNzer5mpwgVx4xflXnD9\/nq9fvHiRn8F8Qgz3S7zF\nMpw8flIOHzos+\/btk127drP2HjX1a1avoUc6emIvnL9Q5syeK39N\/4u5KBMn\nTJQJ4yfI+HHjWeM\/dsxYGTN6DIG+O2rEKBlJRsqI4SN5i+cwxhFc8JlhQ4dJ\n1y5dpU7tOpLf+F1KnDgxY3HTrwtEixaNYxqbNm3i9g3R7WTFzbqtcL2K\/JwD\nBw4wnnc96sp9Db3d2ce6oiiKoiiKoiifD+w\/ZsSa6Dm1YcNG6denn0yaOIme\nyA8fPHy3+RrTtGnT6QUXxs7\/DTUF8MR++vQpx5hGGjEcxpHg\/2a+D\/UBiHux\nTM7eNqEJjM3NmDFD8ubJ6887L1euXKx5uOZxLdj7BrUQQwYPldRfp6FmHDVK\nVI7TjTTiY4xXqH+coiifK+5u7tSMa1SvISmSpyCoYYPmcOXyFacvn6IoSqjG\nmFB\/t2D+Avoyd+ncRVq1aiWVKlZi7ilyRpMmSSpfp\/xa0qZJR604WtToEili\nZIlv3M+UMbNUKFdBan1fS5o2bsrf3r59+kq\/vv3kj\/4DqNX8PfNv+Xflv8yJ\nvHr5KnMnUWv4Ou7euSv37z+Qhw8fMfcUdXjIgzRrZ6G3OX3bKV8ciKksfuDP\nxQv+4M+8bP2+X77woQbM99pP5ueDOSFmxvxRf454\/sjhI\/Q5h4cUvNJn\/jVT\nhv85XMaPHc8YH5oqcjr++GMA6d\/\/D+nfrz\/Bedi3d1\/Sp3cf6dOrj\/H8H+xj\nNGTwEPlz2J8yYvgIzu+dGTbcmM9wzgfzQ51u82Yt2KO7ovE7Ur5seSlTuoxx\nbVZSChUsTJ\/6DOky0CMe12z4fUnkkkgSJkjI3xcT\/L7g9ycwgvMee+LFi\/eK\nuPEkduzY1IYjRYok4cKF86cZAywXfgOxLqNHjXm\/7RME0K8xf\/xmIp+merXq\nUqpEKeM3uCvzdtQvTFEURVEURVGUD8EzI968fv2G7N29V465Hpc7d+6It\/fb\n152ilgu9uH799ddXPcOsHtS9jdgT3m0Y\/8F4008\/\/mTEb\/GZsxs5cmQpWrQo\n84ZVtwzIrp27jJi6OeuLTR0ecW3N72rKiRMnOT72pnlgjAIx5bhx46WcEZPH\njBGTPZIRe7du1Ya905y9noqiKB8S1LO0\/LWlZM+WnV4XAP0UqlapSj9CZy+f\noihKaAO1j7gOhZcQavvatm5r\/GZWk\/x580vuXLnpJwRfaegyuKZELmKpkqWk\nfr36\/L3t0L6DdOrYWXr27EXtY8a0GbJ08VLZuGGT7N2zl3VzBw8epNfz8WPH\nWefocdWDOhiuXfH9fqa+piifEPAE93z6TB4\/ekLfZc8nnryPPIeTJ04Z59Vu\n2bJlK3tXr169WubPm8\/ctsmTJsvkyVNYVzt58uQgmThxIutshwwZKn1696WG\n2KRxU3rA\/1j3J+bIwQO+cOEiUrx4cSlZoiTj7cKFilCTLQwKBaSI8ToI8Lwx\nn\/eG8zVuixTlPOEtgN8M9C13cXERl4QgEX9L8JsSO1ZsiRwpsl0\/8wi870j4\n8NY+5tZeTqamG1T\/8jfylSVP24a1Lzry4tErnf3S4f9lgGVMkzqNFCxYSIoV\nLWZs78IkRLaXFWwr+PTny5uPvd\/x2wsvB\/RUP3z4iDx6+Njpx7uiKIqiKIqi\nKJ8ZVk9k6LXeXi+Yl\/+u88IYD+IXxDWIo8yYC\/14Efuihhm6NPqcZbOO24cz\nYryECRNK9+49ZPeuPTo2FAio086dMzfjUsSyiIPRA65tm3asszD7ZAW1f+FH\nfv36deaew488ZsxYjHURh+fJnYd1HfAyC3IeiqIonzD4f0MN2n\/\/\/ifFihWX\nxImSSMQIEW3kyZWHnqbOXk5FURRng3pI5BnCgxoeqNBzf+v2m5QtU1ZyZMsh\nSRMnlZgxYhHoxenSpme\/YWgb3337HeuIUZ+IWseDBw7KuXPn6a\/q7uZOXwf0\n5n36+GnA\/qy4b+3HijpMs+cubn01Nvh42HriWpDAcPYyvidmb2ccX8hNQL0u\ncnCfPHn6WkwPaMRMV69eZY9dnCeowcc1hCswzhkTeDyhbh7xLdi3dz+14vXr\nNsiE8ROl++89pF3b9syvQN\/vKpWrUHfMkzsv9UGQN2\/eIIF+mDVLVkmTOq0k\nS5rcWt+PutjIRowXhdom+0U5+CojRofGCr0V10DoK0Wsn4sSOapEjWLJrYse\nNbpEj\/bhiRE9hsQy4tM4seMwNxq6MfL64GtPLdnFhY+TG+uZKmUq6rQ20qS1\n3UddMl5PmTKlP1KlSkWfM+RgvwnMJ60xz7RpQTr+xqGnU4b0GalxwzeBZMjE\n5\/H7lyVLFsmcObOFTJZbeDBg\/yC3hmTL\/l7kyJGD3mP4ra1SuSpzcpYsXio3\nb9wSL+0zpSiKoiiKoijKB8Cxv9K71vzevnWbdbGI1xxzdqdMmcJ+aIsXL6F2\nGduIC8Mb8SrqXnNkzyHTp82QixfcnL4tQiPIPTc19gC68a07ge8zMx\/Az49j\nHOgRBQ8wxMyoM8Z80qfPQG+w06dP0x\/c2eupKIryIYDusH\/ffvouoqYlWrTo\n1roVCzlz5lLdWFEUxcDdzV0WL1os337zLbWKrNZ6YuQuxooRy7iOTC3Zs2Yn\n8EudMnmqrPpvFXuTnj17lr1Q0T\/l\/v378vTJU4tH73Mv8fKy+POiD2cA32ir\nHkmt0sei6eE9Pi99xfelr+aUfmjk1X3GFD52IL74DLRie3BMwT\/6\/t37rG1H\nbgN0XvRpeh07tu8wjvXVMnXKVOnbp5+0aN5CvvvmO3oq586Vh\/Gsvc4HbxP4\nLOfOnYf1oXl4m0dy5sglGTJkZI9vaKHQReHBhXMM+mlU+KFEezNRo0ZlvyHo\nrug9hLjaUgMbhreWutjwjPvMHke2Gtyv7GpqwwQE10bIL8a5D70U5zv0bPT4\nzZcvv03XflfyG\/PIb50P8s2hl5cvV14qV6rMOukfvq8lP\/74kzRs0FCaNW0m\nrVq2kvbtO0i3Lt2kZ\/ee9NJGf63+fS0e2\/BwtvhpD6UHNvy4x4wZw3rscWPH\n0dMMddwYb3gd8EOYMX0GY++ZM\/+Wv2fOkll\/\/yOzZ82WObPnyNw5c2Xe3Hmy\nYN4CgufWrV3Ha0zkBOzYvpPHya4du+jjdmD\/QTly6Ii4HnH1l1PwLuA6FZ4M\nu3ftlq1bt7HP8c2bt6w9vvycfl4piqIoiqIoivIZwrEaP9vjd9GNMS6EnGvU\nGsSNE9emGaP\/UOlSpWXpkqWsWWjTug3jaPhJIVZNmTKV1Kz5vaw1Yi74djl9\nW4RCMD5hr8Mj5sf4Q68evajVc1wtkLEd5B7Dc3z50uXS8tdW1EuiRIlCX\/BU\nqb6WJo2bME9ZeyIpivI5g5oi9IJv9EsjiR49umVsFR6D9BkMJzmy51TdWFGU\nLwPrNT+0M\/w2vvB+Kdc8rrMuEhpIr569eC0PLQvXnNCQ0L+zYIFC1JK7\/9ad\nOgxATuK5s+d5\/f78uZcEmMzvDGxyWB5HvdLUjm3apbO32+eKwz7hdn\/5SrP3\nte0LP2pTvu+RXxzSYDlwDMPPCvrvmdNnGWtCv9u5Y2cAoOfBewl5DtD+xo+b\nwL7a8FGHLgl98nWgJrhO7TpSvnwFap7I4U2UMBF7eIez02bt86bNul7EvRZP\nZYvPCa5DwlnzeB375frzWP4q6Nf5HuN1e+9k6r1GnIfaXZy3WTJnlQL5Lbos\nfKpLFC9Bz+rixYrzfokSJaRkyZLsKVyubDmpUKECgXZb7+d60v337jJyxEjj\nfEd\/5MmMSemfPWmKxU\/bAH2T\/TPZ9toUq9\/265g6ZRp1Wvz+YL8sXLCQ4wYr\njOu2VatWyfp162XTxk2ydetW7sc9u\/fw9wpaLTV90+v+0GE5cuQotdWTJ0\/K\nqVOnDE4zP\/rMmTP8rYL3wZtxYy25u5u7wSW55H5JLl+6TL8EcuUqjzePKx5y\n5dIV5mcjH+b5My\/27PI0wLiI93NvW391vxDMvfD09OR34juQF+ns81BRFEVR\nFEVRlC+A94hpUPe6ZdMWxqCRI0exxczQNydOmCQb12+UWX\/PkqxG\/IraWca5\nYcIylu3Xtz\/9q595Pnf+NghFYDwEMSF6Er\/SjC3jB5UqVpIpRsx+5\/ZdjvnZ\na8cYY0Ndh4eHh+zcvpO52vDowthfhAgROI7www+1jLh8kdy\/94CfDy1jQIqi\nKCENxvNQKwLNI1y4cNb+CZZedbiPXCZXV1enL6eiKMoHxa6m99nTZ8wbvHrF\nQ1avXsP+w\/mNa\/J4cePxtzFGjBjMA4X3LXTkgQMHMf8GuklILpO5PEHymXgj\nhzqCmOw9wl++8AmUD+Ub7uPjK97e3tTeHj16zP5HyElAT57AuHH9JvW8\/fsO\nGMfmv6x9hw7cuVMX6di+I3187Wnftr20aNZC6tSqw96w2bJmt\/WtwDH\/zr1w\nX4M\/f2iHaw+z5tdW+2vEadR+0avXIGLEiKwnxrkYK1YsiR07tsSNG1fixYtv\nEM8GfJ2R55EsSTIjxktJPyn4GdeoVoM10YizR44YRW9s9Chn3seYcdSCUYcL\nrXf61Okya+Ys1tMC+MxDn4WvPHuM25+DZu4JjxVf9kOyHC+WY8YSk\/q+X2wZ\nnOlN7zV\/Y\/wc3v85YL+O+vuoKIqiKIqiKEpoxYhXjrsel1FGTIp+PvaxN2qN\n4dME3yj4TyHuteReR6QfV9MmzRjv37t3n+MFTl+XUAQ0Y+RTt23TNkB+eb++\n\/Zj\/jPeY\/d\/gSY3PQTM+fOgIxwJ++P4H9mfCuAPy3NGXqX69+rJ06TLmVMPb\nSjVjRVE+O+zG0fA7t2D+AqlVqzZ\/B+nLaAd146OqGyuK8uVw4fxFWbZ0uXTq\n2EkqV6oimTNlkYQJXdjbFDoVcg779ukrf\/T\/QzZu2Mhrxlu3bvO6M0SXxaGf\nriOqiXwkrBNDCWsOKvJK4edsqaN8Tj0XIO4I6e\/Hd0InPnP6DGtL\/5oxUwYO\nGCSdO3eR9u3aszePI9BEEdNUr1ZDihcrQR0YvWhTpfyaPZMcgS80vJcSuSSW\nuHHi0RMafX0ZtzrWCoegbmxqwoh\/2U84UmRrL+HI9JdGT2HkXGN50NeXfXq\/\nTs3+uMWKFOM64jzt0b2HDB0yVMaMHkMf5lEjR1v9mMdSE0YtMDyWZ\/8zWxYt\nWkz\/ZHgao\/727OmzcuHcBeO8vyDnz4Hz\/A2w1NVekquXr8q1q9fk+rXrcv36\ndeNcvyUPHjxgTGnGl+b5+sF143eZHI4lH\/rc+1hyIF6+5OPPxcvZz\/SJ099G\nRVEURVEURVE+Afbu2UsvK8S59vEy642NWLZ6teqsWaA\/tRGfx40bT76p8Y38\nM2s2\/cU+xBjEJ40RCz5++JixP7aTvR8Zxh7g68WY2Aq2H8ZyoCVv2bKFYy3V\njG2eOHFi1ndjXCJe3Pjy80\/1ZM4\/c1gvgverZqwoymeHg9bAemPjtxQ1c9CN\nOT5sYvxPZcuWTXVjRVG+CJ4+fUr\/VfTybFC\/oeTIkdO4dk\/D\/iVZs2STihUq\nSru27eTflf\/S8\/fw4cP0RP2gy+X7GkLBNvtssfcIx2P7yXgMzQ3\/n95eL9j7\nBhoiMPNVWRf88JGt9peaowOoBz596rTs2rlL\/vv3P9ayTp82nRqnPYhrhv85\nnLFkkyZNpGrValKwYCFqpxnSZ6AntCPotY3+u9CA0RMYfScCeEV\/AMJ8FZbX\nElGiRGUONOLbRIkSs1exPUmSJGFcnCFDBvpFF8xfUMqVKSc1v6sp9es1kKZN\nmkrTxk2liZXmTZtL29ZtpXOnzqR3rz4yetQYWb5suWzftp25xOhpe+7cOTl7\n5hz7Q507e44a8MWLbowBr1y5wv7i6Ht77949efz4sTx\/bu0xDp7ZYTyGlzL2\nL3IELJqvj0XzDXBA+D9X\/enGL3z8HRO3jO\/Gvrfp0G\/L9eusc8Z6XDbi1fPn\nz3M9sd5YV\/RRhwf1kcNHLB7VBw5a\/Kr3Wdi3d7\/s3bNP9uzeK7t37SEYp9hv\nvAe\/aUEBH+u3WU7UwjvDJ1p1Y0VRFEVRFEVRPhUQu+zYsVM6dujEcSf7nG30\nV8I4FLzuEMtHCBeBsXamjJlkyeIljAs52c9Tx4q4Te\/duUf9t2DBgv48zrAN\nMeZiTr6+vvLs2TP2Wlq8aLE0b9ZcsmfLITGNbY\/PIKc9YQIX5uHDh+z2rTvW\ncQFLvB+SPZcURfmA6Lj6O20fby9v+vpXKF+R9T6O\/QfVp1pRlC8BaIDQl+C\/\nUKF8BYkaJZpEjxaD1+SVKlWWZk2b04va2cv5RWFOH\/t7HbQ\/UytETOHj40Of\njqCA3vj40RO5euUqdczdO3fLpg2bZN2adQFYsmgJfZFRG1yiWAlJmjgpa24\/\ntLb79lqwxUPa7BFMwgeEenHkKIxrU6ZIJTmy55CiRYpaegMb55Q9lY1zCj2C\nWzT\/lTXTw4YMk3lz5nF7Xb50hZo7aqzRMwhAf7\/ucd3ST\/fyFbl187Z4PvW0\naJOvm\/xe\/zIm7lPmAHhbtGID7EfUkj+31ZI\/p58A9WTjfdzf3o68tNx6vbDO\nw5ufe\/rkKW8R1yNHYMOGjbJm9VpZv3a9rAOBHBtBYrx\/w\/oNsnrValm6eCl7\nHzO\/YOo05rugtzJqrnv37iNdu3STbt1+k65duxn3uxL4lKM+u1OHTla\/8o7U\n4bsZ7+nRo0eQILZ+m+WEjo\/19lW\/NEVRFEVRFEVRlAAgZkRvNPRLKlSwMPOu\n7eNwxNcxY8akFxdicdTK5s6dR34zYrxTJ08F9LtTDYRgLAe9i\/v3+0Py58v\/\nSjcOE5aeatOnzxBzQh7\/4sWLZeyYsfLzTz\/T34x+4OHDUxNBHjz0EuTyY3zn\n+XMveoq9d+8pRVE+Lqobv3n7GLdmv0z6E3q\/5LjemNFj2TcB\/0P2\/1FRo0aV\nYsWKyckTJ52\/\/IqiKB8IaD0z\/5opDeo3MK7XC4mLi4vEiRNHCuQrIH1696U3\nMOrzrly+qrVsHxNzctL3QzdGvannE0\/2uz5z6oxs2bxV5s6dJ3\/P\/Ju+x\/ZA\nW4MOPHDAQGndqrXU+qGWlCldVkoULyHFihYLAI61XDlzMTZBPALN1bGXsEWz\nDWetF\/4wfYaDxKoXx4kdh3X3iLkQM31f83uuW+1atW3UqV1Hfqz7E9e7X59+\nMnnSZFm6ZCnPnW1bt7Em2JGdO3ay9hW1sfDght\/T3bt3xdPTk7os+jl7Q8\/1\nttR0Iy6GVozXod\/a+hCJub8suj5AjS\/0XWi++KxPUHXC+Kg1J4D4+IfzM74H\n33v71m3Gils2b5GFCxbKP7P+4e8GPFvmzZvH5xbMWyDz586XeWSeTJo4mf2T\n4KP9a4tfqZeXKllKihYtKsWLFTeOg+KBHhuvA5+DHo\/jB72a8+TOYyFPHsmd\nO7fkyJFDMmXKxFp01HOzJj19+lc41KbjdfRqQo5MUOB73mYZcTzgnEAc7vTf\nEUVRFEVRFEVRlNCCdTwJMSb6JnXp3JU+yPQAdYjHoRVjrD5mjJhGbJdROnTo\naMTYm+lP7Wc3L4CxKrN\/1pesaWIcB3XBfY04PF\/efDbdGL2vMmbMKHNmz6GP\n147tO9jHuOWvraRK5SqSNk1ajn9EiBCRtd7o4wVPtAF\/DGQPK+S22\/ohf8Hb\nV1E+NV71e7T0HST0lxT1DDAJRDdGbcyTx09l8MDBUiB\/gQC6ceLESdgHHh6I\nTl9+RVGUDwD8XteuWSs1v61J\/xnodF+n+lqqVKki\/fv1Zw9U1A2ihtB2faj\/\nKx8Hc3rP+UAPtHgRe9v1mn3J\/0DEVMhFhccvPH2hcW7etJl654b1G2XVf6tl\n2ZJljC1GDB8hnTp2lrp16rJPTtUqVW1Uq1pNalT\/RsqVLS\/58xWgBzPyhQPr\nD4z\/2qhRojJuiR4tOuNDR73YXjcOFzY8gXb8vjpwuHDh+d0uCV0YF0G3hv4Y\nmPYHvRu6N3ThNq3b0OcJejB0c9Tl2wPNdPGiJYxhoQOj3vrx4ydB1pviPDJr\nd00\/cLOeGzouYO9d5PL6+vo7HhAf43l8FvvR\/A5fa99ey759YdONUTeMx5be\nvj7MEX748KHcvn2bnspnjWucI0eOyN69e2XXrl2yY8cO3u7evUf27NlLfXvN\n6jXUh4cOHirt2ranLopjAL2mvv32W14r4blaP9SWWt\/XMh5bQG01tjE8xRF3\nIjfAvNaib\/hXFm8X7H\/0T0etNvYN3psubTp+DpqwuU+KFvG\/j\/AYGjIoEkzM\n9xd9S71adWNFURRFURRFUZT3g5qFn6VPGsYg4I3MuDCQHG5zrABjVN26\/ibb\nt+9gHI1+SNBH\/c3XiHfhtwy+ZA9ljAugP1TfPv51Y+Trt\/y1JX0EV\/23SipW\nqMQ671w5c3NsBhp92LDIm49Lr2rE+MgDP3LoCMcDnz19xpoC2\/iEoiihGwet\n2DJm6PvKV9JOQ\/7ix\/kd6rDN7YL\/G3hcZEiXIcC4NTyq4WmIHoxOX35FUZQP\nwIrlKyR\/3vwSL248W\/\/XJo2b0AsWOZzO6NH5xfEu01t8DrWr0Ajv3r4rjx89\ntvHo4WPxuOIhO3fskrFj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0c\/3X6ciuKoigfBse4wNSJrb0gGI+g1vKlWWvpy+eo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\nlYvrS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pqgqaikZCWJOrgCi7+qpr3IFmJciI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\nwKe6YSO+yte7eqwcmicckFdW4S\/inZEvveD8C+RN54hr36GK5eyzz9aeaR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fyf\/lwLuWLvAiOIA9AaQCWPltC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mNvsrzUonrIef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\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4WAWLf2Pg3xs1pz5ze2JurFHC5s416+p3n9pwNFUkMXKz+poy6\/z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\ngtfnsWuir0MOPiS7xq9euSrOJQBY41zMWalOsSPd4d4n2Zy8Cln4N7Lpk0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\"Text\",ExpressionUUID->\"9ee36698-3e39-4186-81e5-9cede7485734\"],\nCell[CellGroupData[{\nCell[915465, 15641, 1699, 43, 127, \"Input\",ExpressionUUID->\"3107ff02-60ca-4dfd-bdc3-2413a0a020d0\"],\nCell[917167, 15686, 11411, 289, 175, \"Output\",ExpressionUUID->\"1d90d958-d619-4bd9-8bd7-e1f6d871fb4a\"]\n}, Open ]],\nCell[CellGroupData[{\nCell[928615, 15980, 209, 4, 30, \"Input\",ExpressionUUID->\"7f3e15ca-a520-46e0-ac65-40cdea0ac3ea\"],\nCell[928827, 15986, 4377, 129, 293, \"Output\",ExpressionUUID->\"a5e53f1a-14b4-4126-baa9-12b0432e9d6b\"]\n}, Open ]],\nCell[CellGroupData[{\nCell[933241, 16120, 225, 4, 30, \"Input\",ExpressionUUID->\"e3576a1e-f25f-4132-bf57-203b9ec51989\"],\nCell[933469, 16126, 3806, 85, 124, \"Output\",ExpressionUUID->\"03a4ab12-a0f9-43fb-ae16-b6474d625326\"]\n}, Open ]],\nCell[CellGroupData[{\nCell[937312, 16216, 219, 4, 30, \"Input\",ExpressionUUID->\"adab58b0-0be2-481e-94df-78ad2e71b12a\"],\nCell[937534, 16222, 156, 3, 34, \"Output\",ExpressionUUID->\"0800a5c6-0668-414a-9652-b1e441eb69ce\"]\n}, Open ]],\nCell[CellGroupData[{\nCell[937727, 16230, 223, 4, 30, \"Input\",ExpressionUUID->\"8bf54867-f4c6-40ca-9202-17d8790fc3f0\"],\nCell[937953, 16236, 156, 3, 34, \"Output\",ExpressionUUID->\"54e9628e-aa27-4ed0-9f7a-bc959ac999d8\"]\n}, Open ]]\n}\n]\n*)\n\n","avg_line_length":57.7258814887,"max_line_length":144,"alphanum_fraction":0.9044760925} {"size":2168,"ext":"nb","lang":"Mathematica","max_stars_count":2.0,"content":"Beat 0 2\nBeat 245 0\nBeat 490 1\nBeat 735 0\nBeat 1015 4\nBeat 1260 0\nBeat 1505 1\nBeat 1750 0\nBeat 1995 2\nBeat 2240 0\nBeat 2485 1\nBeat 2730 0\nBeat 3010 2\nBeat 3255 0\nBeat 3500 1\nBeat 3745 0\nBeat 3990 3\nBeat 4235 0\nBeat 4480 1\nBeat 4725 0\nBeat 5005 2\nBeat 5250 0\nBeat 5495 1\nBeat 5740 0\nBeat 5985 2\nBeat 6230 0\nBeat 6475 1\nBeat 6720 0\nBeat 7000 4\nBeat 7245 0\nBeat 7490 1\nBeat 7735 0\nBeat 7980 2\nBeat 8225 0\nBeat 8505 1\nBeat 8750 0\nBeat 8995 2\nBeat 9240 0\nBeat 9485 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\"cutIdentifier\" \"200904080023-749524\";\nfileInfo \"osv\" \"Microsoft Windows XP Service Pack 3 (Build 2600)\\n\";\ncreateNode transform -s -n \"persp\";\n\tsetAttr \".v\" no;\n\tsetAttr \".t\" -type \"double3\" 0.3590068434916317 -0.13018510677949491 0.5179956954831082 ;\n\tsetAttr \".r\" -type \"double3\" 12.261647270393317 34.599999999999753 -4.8299328079840907e-016 ;\n\tsetAttr \".rp\" -type \"double3\" 8.6736173798840355e-019 4.3368086899420177e-018 5.5511151231257827e-017 ;\n\tsetAttr \".rpt\" -type \"double3\" 8.2148641947088195e-018 1.3979643254912973e-017 -3.7128028282776475e-018 ;\ncreateNode camera -s -n \"perspShape\" -p \"persp\";\n\tsetAttr -k off \".v\" no;\n\tsetAttr \".fl\" 34.999999999999979;\n\tsetAttr \".coi\" 0.63980608897413904;\n\tsetAttr \".imn\" -type \"string\" \"persp\";\n\tsetAttr \".den\" -type \"string\" \"persp_depth\";\n\tsetAttr \".man\" -type \"string\" \"persp_mask\";\n\tsetAttr \".tp\" -type \"double3\" 0.0039847996044182626 0.0056945574807425736 0.0033619454403620019 ;\n\tsetAttr \".hc\" -type \"string\" \"viewSet -p %camera\";\ncreateNode transform -s -n \"top\";\n\tsetAttr \".v\" no;\n\tsetAttr \".t\" -type \"double3\" 0 100.1 0 ;\n\tsetAttr \".r\" -type \"double3\" -89.999999999999986 0 0 ;\ncreateNode camera -s -n \"topShape\" -p \"top\";\n\tsetAttr -k off \".v\" no;\n\tsetAttr \".rnd\" no;\n\tsetAttr \".coi\" 100.1;\n\tsetAttr \".ow\" 30;\n\tsetAttr \".imn\" -type \"string\" \"top\";\n\tsetAttr \".den\" -type \"string\" \"top_depth\";\n\tsetAttr \".man\" -type \"string\" \"top_mask\";\n\tsetAttr \".hc\" -type \"string\" \"viewSet -t %camera\";\n\tsetAttr \".o\" yes;\ncreateNode transform -s -n \"front\";\n\tsetAttr \".v\" no;\n\tsetAttr \".t\" -type \"double3\" 0 0 100.1 ;\ncreateNode camera -s -n \"frontShape\" -p \"front\";\n\tsetAttr -k off \".v\" no;\n\tsetAttr \".rnd\" no;\n\tsetAttr \".coi\" 100.1;\n\tsetAttr \".ow\" 30;\n\tsetAttr \".imn\" -type \"string\" \"front\";\n\tsetAttr \".den\" -type \"string\" \"front_depth\";\n\tsetAttr \".man\" -type \"string\" \"front_mask\";\n\tsetAttr \".hc\" -type \"string\" \"viewSet -f %camera\";\n\tsetAttr \".o\" yes;\ncreateNode transform -s -n \"side\";\n\tsetAttr \".v\" no;\n\tsetAttr \".t\" -type \"double3\" 100.1 0 0 ;\n\tsetAttr \".r\" -type \"double3\" 0 89.999999999999986 0 ;\ncreateNode camera -s -n \"sideShape\" -p \"side\";\n\tsetAttr -k off \".v\" no;\n\tsetAttr \".rnd\" no;\n\tsetAttr \".coi\" 100.1;\n\tsetAttr \".ow\" 30;\n\tsetAttr \".imn\" -type \"string\" \"side\";\n\tsetAttr \".den\" -type \"string\" \"side_depth\";\n\tsetAttr \".man\" -type \"string\" \"side_mask\";\n\tsetAttr \".hc\" -type \"string\" \"viewSet -s %camera\";\n\tsetAttr \".o\" yes;\ncreateNode transform -n \"m_particle\";\n\tsetAttr \".s\" -type \"double3\" 0.5 0.5 0.5 ;\ncreateNode mesh -n \"m_particleShape\" -p \"m_particle\";\n\taddAttr -ci true -sn \"mso\" -ln \"miShadingSamplesOverride\" -min 0 -max 1 -at \"bool\";\n\taddAttr -ci true -sn \"msh\" -ln \"miShadingSamples\" -min 0 -smx 8 -at \"float\";\n\taddAttr -ci true -sn \"mdo\" -ln \"miMaxDisplaceOverride\" -min 0 -max 1 -at \"bool\";\n\taddAttr -ci true -sn \"mmd\" -ln \"miMaxDisplace\" -min 0 -smx 1 -at \"float\";\n\taddAttr -ci true -sn \"rgvtx\" -ln \"rgvtx\" -dt \"vectorArray\";\n\taddAttr -ci true -sn \"rgf\" -ln \"rgf\" -dt \"string\";\n\taddAttr -ci true -sn \"rgn\" -ln \"rgn\" -dt \"vectorArray\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\n\tsetAttr \".rgvtx\" -type \"vectorArray\" 8 -0.04330126941204071 -0.049999997019767761\n\t\t -0.075000010430812836 -0.043301276862621307 -0.049999997019767761 0.075000002980232239 0.086602546274662018\n\t\t -0.049999997019767761 0 -0.04330126941204071 0.049999997019767761 -0.075000010430812836 -0.043301276862621307\n\t\t 0.049999997019767761 0.075000002980232239 0.086602546274662018 0.049999997019767761\n\t\t 0 0 -0.10000000149011612 0 0 0.10000000149011612 0 ;\n\tsetAttr \".rgf\" -type \"string\" \"[[0,1,4,3],[1,2,5,4],[2,0,3,5],[1,0,6],[2,1,6],[0,2,6],[3,4,7],[4,5,7],[5,3,7]]\";\n\tsetAttr \".rgn\" -type \"vectorArray\" 30 -1 0 -4.9670532575873949e-008 -1 0 -4.9670532575873949e-008 -1\n\t\t 0 -4.9670532575873949e-008 -1 0 -4.9670532575873949e-008 0.49999997019767761 0 0.86602544784545898 0.49999997019767761\n\t\t 0 0.86602544784545898 0.49999997019767761 0 0.86602544784545898 0.49999997019767761\n\t\t 0 0.86602544784545898 0.49999997019767761 0 -0.86602532863616943 0.49999997019767761\n\t\t 0 -0.86602532863616943 0.49999997019767761 0 -0.86602532863616943 0.49999997019767761\n\t\t 0 -0.86602532863616943 -0.75592899322509766 -0.65465366840362549 0 -0.75592899322509766\n\t\t -0.65465366840362549 0 -0.75592899322509766 -0.65465366840362549 0 0.37796443700790405\n\t\t -0.65465360879898071 0.65465372800827026 0.37796443700790405 -0.65465360879898071\n\t\t 0.65465372800827026 0.37796443700790405 -0.65465360879898071 0.65465372800827026 0.37796446681022644\n\t\t -0.65465366840362549 -0.65465366840362549 0.37796446681022644 -0.65465366840362549\n\t\t -0.65465366840362549 0.37796446681022644 -0.65465366840362549 -0.65465366840362549 -0.75592893362045288\n\t\t 0.65465366840362549 0 -0.75592893362045288 0.65465366840362549 0 -0.75592893362045288\n\t\t 0.65465366840362549 0 0.37796443700790405 0.65465360879898071 0.65465372800827026 0.37796443700790405\n\t\t 0.65465360879898071 0.65465372800827026 0.37796443700790405 0.65465360879898071 0.65465372800827026 0.37796446681022644\n\t\t 0.65465366840362549 -0.65465366840362549 0.37796446681022644 0.65465366840362549\n\t\t -0.65465366840362549 0.37796446681022644 0.65465366840362549 -0.65465366840362549 ;\ncreateNode transform -n \"phys_particle\" -p \"m_particle\";\ncreateNode mesh -n \"phys_particleShape\" -p \"phys_particle\";\n\taddAttr -ci true -sn \"mso\" -ln \"miShadingSamplesOverride\" -min 0 -max 1 -at \"bool\";\n\taddAttr -ci true -sn \"msh\" -ln \"miShadingSamples\" -min 0 -smx 8 -at \"float\";\n\taddAttr -ci true -sn \"mdo\" -ln \"miMaxDisplaceOverride\" -min 0 -max 1 -at \"bool\";\n\taddAttr -ci true -sn \"mmd\" -ln \"miMaxDisplace\" -min 0 -smx 1 -at \"float\";\n\tsetAttr -k off \".v\";\n\tsetAttr \".vir\" yes;\n\tsetAttr \".vif\" yes;\n\tsetAttr \".uvst[0].uvsn\" -type \"string\" \"map1\";\n\tsetAttr \".cuvs\" -type \"string\" \"map1\";\n\tsetAttr \".dcc\" -type \"string\" \"Ambient+Diffuse\";\n\tsetAttr \".covm[0]\" 0 1 1;\n\tsetAttr \".cdvm[0]\" 0 1 1;\ncreateNode lightLinker -n \"lightLinker1\";\n\tsetAttr -s 4 \".lnk\";\n\tsetAttr -s 4 \".slnk\";\ncreateNode displayLayerManager -n \"layerManager\";\ncreateNode displayLayer -n \"defaultLayer\";\ncreateNode renderLayerManager -n \"renderLayerManager\";\ncreateNode renderLayer -n \"defaultRenderLayer\";\n\tsetAttr \".g\" yes;\ncreateNode polySphere -n \"polySphere1\";\n\tsetAttr \".r\" 0.1;\n\tsetAttr \".sa\" 3;\n\tsetAttr \".sh\" 3;\ncreateNode phong -n \"mat_mud\";\n\tsetAttr \".c\" -type \"float3\" 0.090899996 0.058918346 0 ;\n\tsetAttr \".sc\" -type \"float3\" 0 0 0 ;\n\tsetAttr \".rfl\" 0;\n\tsetAttr \".cp\" 2;\ncreateNode shadingEngine -n \"phong1SG\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo1\";\ncreateNode polySphere -n \"polySphere2\";\n\tsetAttr \".r\" 0.1;\ncreateNode phong -n \"mat_phys\";\n\tsetAttr \".c\" -type \"float3\" 1 0.45999998 0.64810002 ;\n\tsetAttr \".it\" -type \"float3\" 0.47933999 0.47933999 0.47933999 ;\ncreateNode shadingEngine -n \"phong2SG\";\n\tsetAttr \".ihi\" 0;\n\tsetAttr \".ro\" yes;\ncreateNode materialInfo -n \"materialInfo2\";\ncreateNode script -n \"uiConfigurationScriptNode\";\n\tsetAttr \".b\" -type \"string\" (\n\t\t\"\/\/ Maya Mel UI Configuration File.\\n\/\/\\n\/\/ This script is machine generated. Edit at your own risk.\\n\/\/\\n\/\/\\n\\nglobal string $gMainPane;\\nif (`paneLayout -exists $gMainPane`) {\\n\\n\\tglobal int $gUseScenePanelConfig;\\n\\tint $useSceneConfig = $gUseScenePanelConfig;\\n\\tint $menusOkayInPanels = `optionVar -q allowMenusInPanels`;\\tint $nVisPanes = `paneLayout -q -nvp $gMainPane`;\\n\\tint $nPanes = 0;\\n\\tstring $editorName;\\n\\tstring $panelName;\\n\\tstring $itemFilterName;\\n\\tstring $panelConfig;\\n\\n\\t\/\/\\n\\t\/\/ get current state of the UI\\n\\t\/\/\\n\\tsceneUIReplacement -update $gMainPane;\\n\\n\\t$panelName = `sceneUIReplacement -getNextPanel \\\"modelPanel\\\" (localizedPanelLabel(\\\"Top View\\\")) `;\\n\\tif (\\\"\\\" == $panelName) {\\n\\t\\tif ($useSceneConfig) {\\n\\t\\t\\t$panelName = `modelPanel -unParent -l (localizedPanelLabel(\\\"Top View\\\")) -mbv $menusOkayInPanels `;\\n\\t\\t\\t$editorName = $panelName;\\n modelEditor -e \\n -camera \\\"top\\\" \\n -useInteractiveMode 0\\n -displayLights \\\"default\\\" \\n -displayAppearance \\\"wireframe\\\" \\n\"\n\t\t+ \" -activeOnly 0\\n -wireframeOnShaded 0\\n -headsUpDisplay 1\\n -selectionHiliteDisplay 1\\n -useDefaultMaterial 0\\n -bufferMode \\\"double\\\" \\n -twoSidedLighting 1\\n -backfaceCulling 0\\n -xray 0\\n -jointXray 0\\n -activeComponentsXray 0\\n -displayTextures 0\\n -smoothWireframe 0\\n -lineWidth 1\\n -textureAnisotropic 0\\n -textureHilight 1\\n -textureSampling 2\\n -textureDisplay \\\"modulate\\\" \\n -textureMaxSize 8192\\n -fogging 0\\n -fogSource \\\"fragment\\\" \\n -fogMode \\\"linear\\\" \\n -fogStart 0\\n -fogEnd 100\\n -fogDensity 0.1\\n -fogColor 0.5 0.5 0.5 1 \\n -maxConstantTransparency 1\\n -rendererName \\\"base_OpenGL_Renderer\\\" \\n -colorResolution 256 256 \\n\"\n\t\t+ \" -bumpResolution 512 512 \\n -textureCompression 0\\n -transparencyAlgorithm \\\"frontAndBackCull\\\" \\n -transpInShadows 0\\n -cullingOverride \\\"none\\\" \\n -lowQualityLighting 0\\n -maximumNumHardwareLights 1\\n -occlusionCulling 0\\n -shadingModel 0\\n -useBaseRenderer 0\\n -useReducedRenderer 0\\n -smallObjectCulling 0\\n -smallObjectThreshold -1 \\n -interactiveDisableShadows 0\\n -interactiveBackFaceCull 0\\n -sortTransparent 1\\n -nurbsCurves 1\\n -nurbsSurfaces 1\\n -polymeshes 1\\n -subdivSurfaces 1\\n -planes 1\\n -lights 1\\n -cameras 1\\n -controlVertices 1\\n -hulls 1\\n -grid 1\\n -joints 1\\n -ikHandles 1\\n -deformers 1\\n -dynamics 1\\n\"\n\t\t+ \" -fluids 1\\n -hairSystems 1\\n -follicles 1\\n -nCloths 1\\n -nParticles 1\\n -nRigids 1\\n -dynamicConstraints 1\\n -locators 1\\n -manipulators 1\\n -dimensions 1\\n -handles 1\\n -pivots 1\\n -textures 1\\n -strokes 1\\n -shadows 0\\n $editorName;\\nmodelEditor -e -viewSelected 0 $editorName;\\n\\t\\t}\\n\\t} else {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tmodelPanel -edit -l (localizedPanelLabel(\\\"Top View\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\t$editorName = $panelName;\\n modelEditor -e \\n -camera \\\"top\\\" \\n -useInteractiveMode 0\\n -displayLights \\\"default\\\" \\n -displayAppearance \\\"wireframe\\\" \\n -activeOnly 0\\n -wireframeOnShaded 0\\n -headsUpDisplay 1\\n -selectionHiliteDisplay 1\\n -useDefaultMaterial 0\\n -bufferMode \\\"double\\\" \\n\"\n\t\t+ \" -twoSidedLighting 1\\n -backfaceCulling 0\\n -xray 0\\n -jointXray 0\\n -activeComponentsXray 0\\n -displayTextures 0\\n -smoothWireframe 0\\n -lineWidth 1\\n -textureAnisotropic 0\\n -textureHilight 1\\n -textureSampling 2\\n -textureDisplay \\\"modulate\\\" \\n -textureMaxSize 8192\\n -fogging 0\\n -fogSource \\\"fragment\\\" \\n -fogMode \\\"linear\\\" \\n -fogStart 0\\n -fogEnd 100\\n -fogDensity 0.1\\n -fogColor 0.5 0.5 0.5 1 \\n -maxConstantTransparency 1\\n -rendererName \\\"base_OpenGL_Renderer\\\" \\n -colorResolution 256 256 \\n -bumpResolution 512 512 \\n -textureCompression 0\\n -transparencyAlgorithm \\\"frontAndBackCull\\\" \\n -transpInShadows 0\\n -cullingOverride \\\"none\\\" \\n -lowQualityLighting 0\\n -maximumNumHardwareLights 1\\n -occlusionCulling 0\\n\"\n\t\t+ \" -shadingModel 0\\n -useBaseRenderer 0\\n -useReducedRenderer 0\\n -smallObjectCulling 0\\n -smallObjectThreshold -1 \\n -interactiveDisableShadows 0\\n -interactiveBackFaceCull 0\\n -sortTransparent 1\\n -nurbsCurves 1\\n -nurbsSurfaces 1\\n -polymeshes 1\\n -subdivSurfaces 1\\n -planes 1\\n -lights 1\\n -cameras 1\\n -controlVertices 1\\n -hulls 1\\n -grid 1\\n -joints 1\\n -ikHandles 1\\n -deformers 1\\n -dynamics 1\\n -fluids 1\\n -hairSystems 1\\n -follicles 1\\n -nCloths 1\\n -nParticles 1\\n -nRigids 1\\n -dynamicConstraints 1\\n -locators 1\\n -manipulators 1\\n -dimensions 1\\n -handles 1\\n -pivots 1\\n -textures 1\\n -strokes 1\\n -shadows 0\\n $editorName;\\nmodelEditor -e -viewSelected 0 $editorName;\\n\"\n\t\t+ \"\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextPanel \\\"modelPanel\\\" (localizedPanelLabel(\\\"Side View\\\")) `;\\n\\tif (\\\"\\\" == $panelName) {\\n\\t\\tif ($useSceneConfig) {\\n\\t\\t\\t$panelName = `modelPanel -unParent -l (localizedPanelLabel(\\\"Side View\\\")) -mbv $menusOkayInPanels `;\\n\\t\\t\\t$editorName = $panelName;\\n modelEditor -e \\n -camera \\\"side\\\" \\n -useInteractiveMode 0\\n -displayLights \\\"default\\\" \\n -displayAppearance \\\"wireframe\\\" \\n -activeOnly 0\\n -wireframeOnShaded 0\\n -headsUpDisplay 1\\n -selectionHiliteDisplay 1\\n -useDefaultMaterial 0\\n -bufferMode \\\"double\\\" \\n -twoSidedLighting 1\\n -backfaceCulling 0\\n -xray 0\\n -jointXray 0\\n -activeComponentsXray 0\\n -displayTextures 0\\n -smoothWireframe 0\\n -lineWidth 1\\n -textureAnisotropic 0\\n\"\n\t\t+ \" -textureHilight 1\\n -textureSampling 2\\n -textureDisplay \\\"modulate\\\" \\n -textureMaxSize 8192\\n -fogging 0\\n -fogSource \\\"fragment\\\" \\n -fogMode \\\"linear\\\" \\n -fogStart 0\\n -fogEnd 100\\n -fogDensity 0.1\\n -fogColor 0.5 0.5 0.5 1 \\n -maxConstantTransparency 1\\n -rendererName \\\"base_OpenGL_Renderer\\\" \\n -colorResolution 256 256 \\n -bumpResolution 512 512 \\n -textureCompression 0\\n -transparencyAlgorithm \\\"frontAndBackCull\\\" \\n -transpInShadows 0\\n -cullingOverride \\\"none\\\" \\n -lowQualityLighting 0\\n -maximumNumHardwareLights 1\\n -occlusionCulling 0\\n -shadingModel 0\\n -useBaseRenderer 0\\n -useReducedRenderer 0\\n -smallObjectCulling 0\\n -smallObjectThreshold -1 \\n\"\n\t\t+ \" -interactiveDisableShadows 0\\n -interactiveBackFaceCull 0\\n -sortTransparent 1\\n -nurbsCurves 1\\n -nurbsSurfaces 1\\n -polymeshes 1\\n -subdivSurfaces 1\\n -planes 1\\n -lights 1\\n -cameras 1\\n -controlVertices 1\\n -hulls 1\\n -grid 1\\n -joints 1\\n -ikHandles 1\\n -deformers 1\\n -dynamics 1\\n -fluids 1\\n -hairSystems 1\\n -follicles 1\\n -nCloths 1\\n -nParticles 1\\n -nRigids 1\\n -dynamicConstraints 1\\n -locators 1\\n -manipulators 1\\n -dimensions 1\\n -handles 1\\n -pivots 1\\n -textures 1\\n -strokes 1\\n -shadows 0\\n $editorName;\\nmodelEditor -e -viewSelected 0 $editorName;\\n\"\n\t\t+ \"\\t\\t}\\n\\t} else {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tmodelPanel -edit -l (localizedPanelLabel(\\\"Side View\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\t$editorName = $panelName;\\n modelEditor -e \\n -camera \\\"side\\\" \\n -useInteractiveMode 0\\n -displayLights \\\"default\\\" \\n -displayAppearance \\\"wireframe\\\" \\n -activeOnly 0\\n -wireframeOnShaded 0\\n -headsUpDisplay 1\\n -selectionHiliteDisplay 1\\n -useDefaultMaterial 0\\n -bufferMode \\\"double\\\" \\n -twoSidedLighting 1\\n -backfaceCulling 0\\n -xray 0\\n -jointXray 0\\n -activeComponentsXray 0\\n -displayTextures 0\\n -smoothWireframe 0\\n -lineWidth 1\\n -textureAnisotropic 0\\n -textureHilight 1\\n -textureSampling 2\\n -textureDisplay \\\"modulate\\\" \\n -textureMaxSize 8192\\n -fogging 0\\n -fogSource \\\"fragment\\\" \\n -fogMode \\\"linear\\\" \\n\"\n\t\t+ \" -fogStart 0\\n -fogEnd 100\\n -fogDensity 0.1\\n -fogColor 0.5 0.5 0.5 1 \\n -maxConstantTransparency 1\\n -rendererName \\\"base_OpenGL_Renderer\\\" \\n -colorResolution 256 256 \\n -bumpResolution 512 512 \\n -textureCompression 0\\n -transparencyAlgorithm \\\"frontAndBackCull\\\" \\n -transpInShadows 0\\n -cullingOverride \\\"none\\\" \\n -lowQualityLighting 0\\n -maximumNumHardwareLights 1\\n -occlusionCulling 0\\n -shadingModel 0\\n -useBaseRenderer 0\\n -useReducedRenderer 0\\n -smallObjectCulling 0\\n -smallObjectThreshold -1 \\n -interactiveDisableShadows 0\\n -interactiveBackFaceCull 0\\n -sortTransparent 1\\n -nurbsCurves 1\\n -nurbsSurfaces 1\\n -polymeshes 1\\n -subdivSurfaces 1\\n -planes 1\\n -lights 1\\n -cameras 1\\n -controlVertices 1\\n\"\n\t\t+ \" -hulls 1\\n -grid 1\\n -joints 1\\n -ikHandles 1\\n -deformers 1\\n -dynamics 1\\n -fluids 1\\n -hairSystems 1\\n -follicles 1\\n -nCloths 1\\n -nParticles 1\\n -nRigids 1\\n -dynamicConstraints 1\\n -locators 1\\n -manipulators 1\\n -dimensions 1\\n -handles 1\\n -pivots 1\\n -textures 1\\n -strokes 1\\n -shadows 0\\n $editorName;\\nmodelEditor -e -viewSelected 0 $editorName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextPanel \\\"modelPanel\\\" (localizedPanelLabel(\\\"Front View\\\")) `;\\n\\tif (\\\"\\\" == $panelName) {\\n\\t\\tif ($useSceneConfig) {\\n\\t\\t\\t$panelName = `modelPanel -unParent -l (localizedPanelLabel(\\\"Front View\\\")) -mbv $menusOkayInPanels `;\\n\\t\\t\\t$editorName = $panelName;\\n modelEditor -e \\n -camera \\\"front\\\" \\n -useInteractiveMode 0\\n\"\n\t\t+ \" -displayLights \\\"default\\\" \\n -displayAppearance \\\"wireframe\\\" \\n -activeOnly 0\\n -wireframeOnShaded 0\\n -headsUpDisplay 1\\n -selectionHiliteDisplay 1\\n -useDefaultMaterial 0\\n -bufferMode \\\"double\\\" \\n -twoSidedLighting 1\\n -backfaceCulling 0\\n -xray 0\\n -jointXray 0\\n -activeComponentsXray 0\\n -displayTextures 0\\n -smoothWireframe 0\\n -lineWidth 1\\n -textureAnisotropic 0\\n -textureHilight 1\\n -textureSampling 2\\n -textureDisplay \\\"modulate\\\" \\n -textureMaxSize 8192\\n -fogging 0\\n -fogSource \\\"fragment\\\" \\n -fogMode \\\"linear\\\" \\n -fogStart 0\\n -fogEnd 100\\n -fogDensity 0.1\\n -fogColor 0.5 0.5 0.5 1 \\n -maxConstantTransparency 1\\n\"\n\t\t+ \" -rendererName \\\"base_OpenGL_Renderer\\\" \\n -colorResolution 256 256 \\n -bumpResolution 512 512 \\n -textureCompression 0\\n -transparencyAlgorithm \\\"frontAndBackCull\\\" \\n -transpInShadows 0\\n -cullingOverride \\\"none\\\" \\n -lowQualityLighting 0\\n -maximumNumHardwareLights 1\\n -occlusionCulling 0\\n -shadingModel 0\\n -useBaseRenderer 0\\n -useReducedRenderer 0\\n -smallObjectCulling 0\\n -smallObjectThreshold -1 \\n -interactiveDisableShadows 0\\n -interactiveBackFaceCull 0\\n -sortTransparent 1\\n -nurbsCurves 1\\n -nurbsSurfaces 1\\n -polymeshes 1\\n -subdivSurfaces 1\\n -planes 1\\n -lights 1\\n -cameras 1\\n -controlVertices 1\\n -hulls 1\\n -grid 1\\n\"\n\t\t+ \" -joints 1\\n -ikHandles 1\\n -deformers 1\\n -dynamics 1\\n -fluids 1\\n -hairSystems 1\\n -follicles 1\\n -nCloths 1\\n -nParticles 1\\n -nRigids 1\\n -dynamicConstraints 1\\n -locators 1\\n -manipulators 1\\n -dimensions 1\\n -handles 1\\n -pivots 1\\n -textures 1\\n -strokes 1\\n -shadows 0\\n $editorName;\\nmodelEditor -e -viewSelected 0 $editorName;\\n\\t\\t}\\n\\t} else {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tmodelPanel -edit -l (localizedPanelLabel(\\\"Front View\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\t$editorName = $panelName;\\n modelEditor -e \\n -camera \\\"front\\\" \\n -useInteractiveMode 0\\n -displayLights \\\"default\\\" \\n -displayAppearance \\\"wireframe\\\" \\n -activeOnly 0\\n -wireframeOnShaded 0\\n -headsUpDisplay 1\\n\"\n\t\t+ \" -selectionHiliteDisplay 1\\n -useDefaultMaterial 0\\n -bufferMode \\\"double\\\" \\n -twoSidedLighting 1\\n -backfaceCulling 0\\n -xray 0\\n -jointXray 0\\n -activeComponentsXray 0\\n -displayTextures 0\\n -smoothWireframe 0\\n -lineWidth 1\\n -textureAnisotropic 0\\n -textureHilight 1\\n -textureSampling 2\\n -textureDisplay \\\"modulate\\\" \\n -textureMaxSize 8192\\n -fogging 0\\n -fogSource \\\"fragment\\\" \\n -fogMode \\\"linear\\\" \\n -fogStart 0\\n -fogEnd 100\\n -fogDensity 0.1\\n -fogColor 0.5 0.5 0.5 1 \\n -maxConstantTransparency 1\\n -rendererName \\\"base_OpenGL_Renderer\\\" \\n -colorResolution 256 256 \\n -bumpResolution 512 512 \\n -textureCompression 0\\n -transparencyAlgorithm \\\"frontAndBackCull\\\" \\n -transpInShadows 0\\n -cullingOverride \\\"none\\\" \\n\"\n\t\t+ \" -lowQualityLighting 0\\n -maximumNumHardwareLights 1\\n -occlusionCulling 0\\n -shadingModel 0\\n -useBaseRenderer 0\\n -useReducedRenderer 0\\n -smallObjectCulling 0\\n -smallObjectThreshold -1 \\n -interactiveDisableShadows 0\\n -interactiveBackFaceCull 0\\n -sortTransparent 1\\n -nurbsCurves 1\\n -nurbsSurfaces 1\\n -polymeshes 1\\n -subdivSurfaces 1\\n -planes 1\\n -lights 1\\n -cameras 1\\n -controlVertices 1\\n -hulls 1\\n -grid 1\\n -joints 1\\n -ikHandles 1\\n -deformers 1\\n -dynamics 1\\n -fluids 1\\n -hairSystems 1\\n -follicles 1\\n -nCloths 1\\n -nParticles 1\\n -nRigids 1\\n -dynamicConstraints 1\\n -locators 1\\n -manipulators 1\\n -dimensions 1\\n -handles 1\\n -pivots 1\\n\"\n\t\t+ \" -textures 1\\n -strokes 1\\n -shadows 0\\n $editorName;\\nmodelEditor -e -viewSelected 0 $editorName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextPanel \\\"modelPanel\\\" (localizedPanelLabel(\\\"Persp View\\\")) `;\\n\\tif (\\\"\\\" == $panelName) {\\n\\t\\tif ($useSceneConfig) {\\n\\t\\t\\t$panelName = `modelPanel -unParent -l (localizedPanelLabel(\\\"Persp View\\\")) -mbv $menusOkayInPanels `;\\n\\t\\t\\t$editorName = $panelName;\\n modelEditor -e \\n -camera \\\"persp\\\" \\n -useInteractiveMode 0\\n -displayLights \\\"default\\\" \\n -displayAppearance \\\"smoothShaded\\\" \\n -activeOnly 0\\n -wireframeOnShaded 0\\n -headsUpDisplay 1\\n -selectionHiliteDisplay 1\\n -useDefaultMaterial 0\\n -bufferMode \\\"double\\\" \\n -twoSidedLighting 1\\n -backfaceCulling 0\\n -xray 0\\n -jointXray 0\\n\"\n\t\t+ \" -activeComponentsXray 0\\n -displayTextures 0\\n -smoothWireframe 0\\n -lineWidth 1\\n -textureAnisotropic 0\\n -textureHilight 1\\n -textureSampling 2\\n -textureDisplay \\\"modulate\\\" \\n -textureMaxSize 8192\\n -fogging 0\\n -fogSource \\\"fragment\\\" \\n -fogMode \\\"linear\\\" \\n -fogStart 0\\n -fogEnd 100\\n -fogDensity 0.1\\n -fogColor 0.5 0.5 0.5 1 \\n -maxConstantTransparency 1\\n -rendererName \\\"base_OpenGL_Renderer\\\" \\n -colorResolution 256 256 \\n -bumpResolution 512 512 \\n -textureCompression 0\\n -transparencyAlgorithm \\\"frontAndBackCull\\\" \\n -transpInShadows 0\\n -cullingOverride \\\"none\\\" \\n -lowQualityLighting 0\\n -maximumNumHardwareLights 1\\n -occlusionCulling 0\\n\"\n\t\t+ \" -shadingModel 0\\n -useBaseRenderer 0\\n -useReducedRenderer 0\\n -smallObjectCulling 0\\n -smallObjectThreshold -1 \\n -interactiveDisableShadows 0\\n -interactiveBackFaceCull 0\\n -sortTransparent 1\\n -nurbsCurves 1\\n -nurbsSurfaces 1\\n -polymeshes 1\\n -subdivSurfaces 1\\n -planes 1\\n -lights 1\\n -cameras 1\\n -controlVertices 1\\n -hulls 1\\n -grid 1\\n -joints 1\\n -ikHandles 1\\n -deformers 1\\n -dynamics 1\\n -fluids 1\\n -hairSystems 1\\n -follicles 1\\n -nCloths 1\\n -nParticles 1\\n -nRigids 1\\n -dynamicConstraints 1\\n -locators 1\\n -manipulators 1\\n -dimensions 1\\n -handles 1\\n\"\n\t\t+ \" -pivots 1\\n -textures 1\\n -strokes 1\\n -shadows 0\\n $editorName;\\nmodelEditor -e -viewSelected 0 $editorName;\\n\\t\\t}\\n\\t} else {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tmodelPanel -edit -l (localizedPanelLabel(\\\"Persp View\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\t$editorName = $panelName;\\n modelEditor -e \\n -camera \\\"persp\\\" \\n -useInteractiveMode 0\\n -displayLights \\\"default\\\" \\n -displayAppearance \\\"smoothShaded\\\" \\n -activeOnly 0\\n -wireframeOnShaded 0\\n -headsUpDisplay 1\\n -selectionHiliteDisplay 1\\n -useDefaultMaterial 0\\n -bufferMode \\\"double\\\" \\n -twoSidedLighting 1\\n -backfaceCulling 0\\n -xray 0\\n -jointXray 0\\n -activeComponentsXray 0\\n -displayTextures 0\\n -smoothWireframe 0\\n -lineWidth 1\\n -textureAnisotropic 0\\n -textureHilight 1\\n -textureSampling 2\\n\"\n\t\t+ \" -textureDisplay \\\"modulate\\\" \\n -textureMaxSize 8192\\n -fogging 0\\n -fogSource \\\"fragment\\\" \\n -fogMode \\\"linear\\\" \\n -fogStart 0\\n -fogEnd 100\\n -fogDensity 0.1\\n -fogColor 0.5 0.5 0.5 1 \\n -maxConstantTransparency 1\\n -rendererName \\\"base_OpenGL_Renderer\\\" \\n -colorResolution 256 256 \\n -bumpResolution 512 512 \\n -textureCompression 0\\n -transparencyAlgorithm \\\"frontAndBackCull\\\" \\n -transpInShadows 0\\n -cullingOverride \\\"none\\\" \\n -lowQualityLighting 0\\n -maximumNumHardwareLights 1\\n -occlusionCulling 0\\n -shadingModel 0\\n -useBaseRenderer 0\\n -useReducedRenderer 0\\n -smallObjectCulling 0\\n -smallObjectThreshold -1 \\n -interactiveDisableShadows 0\\n -interactiveBackFaceCull 0\\n -sortTransparent 1\\n -nurbsCurves 1\\n -nurbsSurfaces 1\\n\"\n\t\t+ \" -polymeshes 1\\n -subdivSurfaces 1\\n -planes 1\\n -lights 1\\n -cameras 1\\n -controlVertices 1\\n -hulls 1\\n -grid 1\\n -joints 1\\n -ikHandles 1\\n -deformers 1\\n -dynamics 1\\n -fluids 1\\n -hairSystems 1\\n -follicles 1\\n -nCloths 1\\n -nParticles 1\\n -nRigids 1\\n -dynamicConstraints 1\\n -locators 1\\n -manipulators 1\\n -dimensions 1\\n -handles 1\\n -pivots 1\\n -textures 1\\n -strokes 1\\n -shadows 0\\n $editorName;\\nmodelEditor -e -viewSelected 0 $editorName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextPanel \\\"outlinerPanel\\\" (localizedPanelLabel(\\\"Outliner\\\")) `;\\n\\tif (\\\"\\\" == $panelName) {\\n\\t\\tif ($useSceneConfig) {\\n\\t\\t\\t$panelName = `outlinerPanel -unParent -l (localizedPanelLabel(\\\"Outliner\\\")) -mbv $menusOkayInPanels `;\\n\"\n\t\t+ \"\\t\\t\\t$editorName = $panelName;\\n outlinerEditor -e \\n -showShapes 0\\n -showAttributes 0\\n -showConnected 0\\n -showAnimCurvesOnly 0\\n -showMuteInfo 0\\n -organizeByLayer 1\\n -showAnimLayerWeight 1\\n -autoExpandLayers 1\\n -autoExpand 0\\n -showDagOnly 1\\n -showAssets 1\\n -showContainedOnly 1\\n -showPublishedAsConnected 0\\n -showContainerContents 1\\n -ignoreDagHierarchy 0\\n -expandConnections 0\\n -showUnitlessCurves 1\\n -showCompounds 1\\n -showLeafs 1\\n -showNumericAttrsOnly 0\\n -highlightActive 1\\n -autoSelectNewObjects 0\\n -doNotSelectNewObjects 0\\n -dropIsParent 1\\n -transmitFilters 0\\n -setFilter \\\"defaultSetFilter\\\" \\n -showSetMembers 1\\n\"\n\t\t+ \" -allowMultiSelection 1\\n -alwaysToggleSelect 0\\n -directSelect 0\\n -displayMode \\\"DAG\\\" \\n -expandObjects 0\\n -setsIgnoreFilters 1\\n -containersIgnoreFilters 0\\n -editAttrName 0\\n -showAttrValues 0\\n -highlightSecondary 0\\n -showUVAttrsOnly 0\\n -showTextureNodesOnly 0\\n -attrAlphaOrder \\\"default\\\" \\n -animLayerFilterOptions \\\"allAffecting\\\" \\n -sortOrder \\\"none\\\" \\n -longNames 0\\n -niceNames 1\\n -showNamespace 1\\n $editorName;\\n\\t\\t}\\n\\t} else {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\toutlinerPanel -edit -l (localizedPanelLabel(\\\"Outliner\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\t$editorName = $panelName;\\n outlinerEditor -e \\n -showShapes 0\\n -showAttributes 0\\n -showConnected 0\\n -showAnimCurvesOnly 0\\n -showMuteInfo 0\\n\"\n\t\t+ \" -organizeByLayer 1\\n -showAnimLayerWeight 1\\n -autoExpandLayers 1\\n -autoExpand 0\\n -showDagOnly 1\\n -showAssets 1\\n -showContainedOnly 1\\n -showPublishedAsConnected 0\\n -showContainerContents 1\\n -ignoreDagHierarchy 0\\n -expandConnections 0\\n -showUnitlessCurves 1\\n -showCompounds 1\\n -showLeafs 1\\n -showNumericAttrsOnly 0\\n -highlightActive 1\\n -autoSelectNewObjects 0\\n -doNotSelectNewObjects 0\\n -dropIsParent 1\\n -transmitFilters 0\\n -setFilter \\\"defaultSetFilter\\\" \\n -showSetMembers 1\\n -allowMultiSelection 1\\n -alwaysToggleSelect 0\\n -directSelect 0\\n -displayMode \\\"DAG\\\" \\n -expandObjects 0\\n -setsIgnoreFilters 1\\n -containersIgnoreFilters 0\\n -editAttrName 0\\n -showAttrValues 0\\n -highlightSecondary 0\\n\"\n\t\t+ \" -showUVAttrsOnly 0\\n -showTextureNodesOnly 0\\n -attrAlphaOrder \\\"default\\\" \\n -animLayerFilterOptions \\\"allAffecting\\\" \\n -sortOrder \\\"none\\\" \\n -longNames 0\\n -niceNames 1\\n -showNamespace 1\\n $editorName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"graphEditor\\\" (localizedPanelLabel(\\\"Graph Editor\\\")) `;\\n\\tif (\\\"\\\" == $panelName) {\\n\\t\\tif ($useSceneConfig) {\\n\\t\\t\\t$panelName = `scriptedPanel -unParent -type \\\"graphEditor\\\" -l (localizedPanelLabel(\\\"Graph Editor\\\")) -mbv $menusOkayInPanels `;\\n\\n\\t\\t\\t$editorName = ($panelName+\\\"OutlineEd\\\");\\n outlinerEditor -e \\n -showShapes 1\\n -showAttributes 1\\n -showConnected 1\\n -showAnimCurvesOnly 1\\n -showMuteInfo 0\\n -organizeByLayer 1\\n -showAnimLayerWeight 1\\n -autoExpandLayers 1\\n -autoExpand 1\\n\"\n\t\t+ \" -showDagOnly 0\\n -showAssets 1\\n -showContainedOnly 0\\n -showPublishedAsConnected 0\\n -showContainerContents 0\\n -ignoreDagHierarchy 0\\n -expandConnections 1\\n -showUnitlessCurves 1\\n -showCompounds 0\\n -showLeafs 1\\n -showNumericAttrsOnly 1\\n -highlightActive 0\\n -autoSelectNewObjects 1\\n -doNotSelectNewObjects 0\\n -dropIsParent 1\\n -transmitFilters 1\\n -setFilter \\\"0\\\" \\n -showSetMembers 0\\n -allowMultiSelection 1\\n -alwaysToggleSelect 0\\n -directSelect 0\\n -displayMode \\\"DAG\\\" \\n -expandObjects 0\\n -setsIgnoreFilters 1\\n -containersIgnoreFilters 0\\n -editAttrName 0\\n -showAttrValues 0\\n -highlightSecondary 0\\n -showUVAttrsOnly 0\\n\"\n\t\t+ \" -showTextureNodesOnly 0\\n -attrAlphaOrder \\\"default\\\" \\n -animLayerFilterOptions \\\"allAffecting\\\" \\n -sortOrder \\\"none\\\" \\n -longNames 0\\n -niceNames 1\\n -showNamespace 1\\n $editorName;\\n\\n\\t\\t\\t$editorName = ($panelName+\\\"GraphEd\\\");\\n animCurveEditor -e \\n -displayKeys 1\\n -displayTangents 0\\n -displayActiveKeys 0\\n -displayActiveKeyTangents 1\\n -displayInfinities 0\\n -autoFit 0\\n -snapTime \\\"integer\\\" \\n -snapValue \\\"none\\\" \\n -showResults \\\"off\\\" \\n -showBufferCurves \\\"off\\\" \\n -smoothness \\\"fine\\\" \\n -resultSamples 1\\n -resultScreenSamples 0\\n -resultUpdate \\\"delayed\\\" \\n -constrainDrag 0\\n $editorName;\\n\\t\\t}\\n\\t} else {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Graph Editor\\\")) -mbv $menusOkayInPanels $panelName;\\n\"\n\t\t+ \"\\t\\t\\t$editorName = ($panelName+\\\"OutlineEd\\\");\\n outlinerEditor -e \\n -showShapes 1\\n -showAttributes 1\\n -showConnected 1\\n -showAnimCurvesOnly 1\\n -showMuteInfo 0\\n -organizeByLayer 1\\n -showAnimLayerWeight 1\\n -autoExpandLayers 1\\n -autoExpand 1\\n -showDagOnly 0\\n -showAssets 1\\n -showContainedOnly 0\\n -showPublishedAsConnected 0\\n -showContainerContents 0\\n -ignoreDagHierarchy 0\\n -expandConnections 1\\n -showUnitlessCurves 1\\n -showCompounds 0\\n -showLeafs 1\\n -showNumericAttrsOnly 1\\n -highlightActive 0\\n -autoSelectNewObjects 1\\n -doNotSelectNewObjects 0\\n -dropIsParent 1\\n -transmitFilters 1\\n -setFilter \\\"0\\\" \\n -showSetMembers 0\\n\"\n\t\t+ \" -allowMultiSelection 1\\n -alwaysToggleSelect 0\\n -directSelect 0\\n -displayMode \\\"DAG\\\" \\n -expandObjects 0\\n -setsIgnoreFilters 1\\n -containersIgnoreFilters 0\\n -editAttrName 0\\n -showAttrValues 0\\n -highlightSecondary 0\\n -showUVAttrsOnly 0\\n -showTextureNodesOnly 0\\n -attrAlphaOrder \\\"default\\\" \\n -animLayerFilterOptions \\\"allAffecting\\\" \\n -sortOrder \\\"none\\\" \\n -longNames 0\\n -niceNames 1\\n -showNamespace 1\\n $editorName;\\n\\n\\t\\t\\t$editorName = ($panelName+\\\"GraphEd\\\");\\n animCurveEditor -e \\n -displayKeys 1\\n -displayTangents 0\\n -displayActiveKeys 0\\n -displayActiveKeyTangents 1\\n -displayInfinities 0\\n -autoFit 0\\n -snapTime \\\"integer\\\" \\n -snapValue \\\"none\\\" \\n\"\n\t\t+ \" -showResults \\\"off\\\" \\n -showBufferCurves \\\"off\\\" \\n -smoothness \\\"fine\\\" \\n -resultSamples 1\\n -resultScreenSamples 0\\n -resultUpdate \\\"delayed\\\" \\n -constrainDrag 0\\n $editorName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"dopeSheetPanel\\\" (localizedPanelLabel(\\\"Dope Sheet\\\")) `;\\n\\tif (\\\"\\\" == $panelName) {\\n\\t\\tif ($useSceneConfig) {\\n\\t\\t\\t$panelName = `scriptedPanel -unParent -type \\\"dopeSheetPanel\\\" -l (localizedPanelLabel(\\\"Dope Sheet\\\")) -mbv $menusOkayInPanels `;\\n\\n\\t\\t\\t$editorName = ($panelName+\\\"OutlineEd\\\");\\n outlinerEditor -e \\n -showShapes 1\\n -showAttributes 1\\n -showConnected 1\\n -showAnimCurvesOnly 1\\n -showMuteInfo 0\\n -organizeByLayer 1\\n -showAnimLayerWeight 1\\n -autoExpandLayers 1\\n -autoExpand 0\\n\"\n\t\t+ \" -showDagOnly 0\\n -showAssets 1\\n -showContainedOnly 0\\n -showPublishedAsConnected 0\\n -showContainerContents 0\\n -ignoreDagHierarchy 0\\n -expandConnections 1\\n -showUnitlessCurves 0\\n -showCompounds 1\\n -showLeafs 1\\n -showNumericAttrsOnly 1\\n -highlightActive 0\\n -autoSelectNewObjects 0\\n -doNotSelectNewObjects 1\\n -dropIsParent 1\\n -transmitFilters 0\\n -setFilter \\\"0\\\" \\n -showSetMembers 0\\n -allowMultiSelection 1\\n -alwaysToggleSelect 0\\n -directSelect 0\\n -displayMode \\\"DAG\\\" \\n -expandObjects 0\\n -setsIgnoreFilters 1\\n -containersIgnoreFilters 0\\n -editAttrName 0\\n -showAttrValues 0\\n -highlightSecondary 0\\n -showUVAttrsOnly 0\\n\"\n\t\t+ \" -showTextureNodesOnly 0\\n -attrAlphaOrder \\\"default\\\" \\n -animLayerFilterOptions \\\"allAffecting\\\" \\n -sortOrder \\\"none\\\" \\n -longNames 0\\n -niceNames 1\\n -showNamespace 1\\n $editorName;\\n\\n\\t\\t\\t$editorName = ($panelName+\\\"DopeSheetEd\\\");\\n dopeSheetEditor -e \\n -displayKeys 1\\n -displayTangents 0\\n -displayActiveKeys 0\\n -displayActiveKeyTangents 0\\n -displayInfinities 0\\n -autoFit 0\\n -snapTime \\\"integer\\\" \\n -snapValue \\\"none\\\" \\n -outliner \\\"dopeSheetPanel1OutlineEd\\\" \\n -showSummary 1\\n -showScene 0\\n -hierarchyBelow 0\\n -showTicks 1\\n -selectionWindow 0 0 0 0 \\n $editorName;\\n\\t\\t}\\n\\t} else {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Dope Sheet\\\")) -mbv $menusOkayInPanels $panelName;\\n\"\n\t\t+ \"\\t\\t\\t$editorName = ($panelName+\\\"OutlineEd\\\");\\n outlinerEditor -e \\n -showShapes 1\\n -showAttributes 1\\n -showConnected 1\\n -showAnimCurvesOnly 1\\n -showMuteInfo 0\\n -organizeByLayer 1\\n -showAnimLayerWeight 1\\n -autoExpandLayers 1\\n -autoExpand 0\\n -showDagOnly 0\\n -showAssets 1\\n -showContainedOnly 0\\n -showPublishedAsConnected 0\\n -showContainerContents 0\\n -ignoreDagHierarchy 0\\n -expandConnections 1\\n -showUnitlessCurves 0\\n -showCompounds 1\\n -showLeafs 1\\n -showNumericAttrsOnly 1\\n -highlightActive 0\\n -autoSelectNewObjects 0\\n -doNotSelectNewObjects 1\\n -dropIsParent 1\\n -transmitFilters 0\\n -setFilter \\\"0\\\" \\n -showSetMembers 0\\n\"\n\t\t+ \" -allowMultiSelection 1\\n -alwaysToggleSelect 0\\n -directSelect 0\\n -displayMode \\\"DAG\\\" \\n -expandObjects 0\\n -setsIgnoreFilters 1\\n -containersIgnoreFilters 0\\n -editAttrName 0\\n -showAttrValues 0\\n -highlightSecondary 0\\n -showUVAttrsOnly 0\\n -showTextureNodesOnly 0\\n -attrAlphaOrder \\\"default\\\" \\n -animLayerFilterOptions \\\"allAffecting\\\" \\n -sortOrder \\\"none\\\" \\n -longNames 0\\n -niceNames 1\\n -showNamespace 1\\n $editorName;\\n\\n\\t\\t\\t$editorName = ($panelName+\\\"DopeSheetEd\\\");\\n dopeSheetEditor -e \\n -displayKeys 1\\n -displayTangents 0\\n -displayActiveKeys 0\\n -displayActiveKeyTangents 0\\n -displayInfinities 0\\n -autoFit 0\\n -snapTime \\\"integer\\\" \\n -snapValue \\\"none\\\" \\n\"\n\t\t+ \" -outliner \\\"dopeSheetPanel1OutlineEd\\\" \\n -showSummary 1\\n -showScene 0\\n -hierarchyBelow 0\\n -showTicks 1\\n -selectionWindow 0 0 0 0 \\n $editorName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"clipEditorPanel\\\" (localizedPanelLabel(\\\"Trax Editor\\\")) `;\\n\\tif (\\\"\\\" == $panelName) {\\n\\t\\tif ($useSceneConfig) {\\n\\t\\t\\t$panelName = `scriptedPanel -unParent -type \\\"clipEditorPanel\\\" -l (localizedPanelLabel(\\\"Trax Editor\\\")) -mbv $menusOkayInPanels `;\\n\\n\\t\\t\\t$editorName = clipEditorNameFromPanel($panelName);\\n clipEditor -e \\n -displayKeys 0\\n -displayTangents 0\\n -displayActiveKeys 0\\n -displayActiveKeyTangents 0\\n -displayInfinities 0\\n -autoFit 0\\n -snapTime \\\"none\\\" \\n -snapValue \\\"none\\\" \\n $editorName;\\n\\t\\t}\\n\\t} else {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\"\n\t\t+ \"\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Trax Editor\\\")) -mbv $menusOkayInPanels $panelName;\\n\\n\\t\\t\\t$editorName = clipEditorNameFromPanel($panelName);\\n clipEditor -e \\n -displayKeys 0\\n -displayTangents 0\\n -displayActiveKeys 0\\n -displayActiveKeyTangents 0\\n -displayInfinities 0\\n -autoFit 0\\n -snapTime \\\"none\\\" \\n -snapValue \\\"none\\\" \\n $editorName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"hyperGraphPanel\\\" (localizedPanelLabel(\\\"Hypergraph Hierarchy\\\")) `;\\n\\tif (\\\"\\\" == $panelName) {\\n\\t\\tif ($useSceneConfig) {\\n\\t\\t\\t$panelName = `scriptedPanel -unParent -type \\\"hyperGraphPanel\\\" -l (localizedPanelLabel(\\\"Hypergraph Hierarchy\\\")) -mbv $menusOkayInPanels `;\\n\\n\\t\\t\\t$editorName = ($panelName+\\\"HyperGraphEd\\\");\\n hyperGraph -e \\n -graphLayoutStyle \\\"hierarchicalLayout\\\" \\n -orientation \\\"horiz\\\" \\n\"\n\t\t+ \" -mergeConnections 1\\n -zoom 0.8425\\n -animateTransition 0\\n -showRelationships 1\\n -showShapes 0\\n -showDeformers 0\\n -showExpressions 0\\n -showConstraints 0\\n -showUnderworld 0\\n -showInvisible 0\\n -transitionFrames 5\\n -currentNode \\\"m_particle\\\" \\n -opaqueContainers 0\\n -freeform 1\\n -imagePosition 0 0 \\n -imageScale 1\\n -imageEnabled 0\\n -graphType \\\"DAG\\\" \\n -heatMapDisplay 0\\n -updateSelection 1\\n -updateNodeAdded 1\\n -useDrawOverrideColor 0\\n -limitGraphTraversal -1\\n -range 0 0 \\n -iconSize \\\"largeIcons\\\" \\n -showCachedConnections 0\\n $editorName;\\n\\t\\t}\\n\\t} else {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Hypergraph Hierarchy\\\")) -mbv $menusOkayInPanels $panelName;\\n\"\n\t\t+ \"\\t\\t\\t$editorName = ($panelName+\\\"HyperGraphEd\\\");\\n hyperGraph -e \\n -graphLayoutStyle \\\"hierarchicalLayout\\\" \\n -orientation \\\"horiz\\\" \\n -mergeConnections 1\\n -zoom 0.8425\\n -animateTransition 0\\n -showRelationships 1\\n -showShapes 0\\n -showDeformers 0\\n -showExpressions 0\\n -showConstraints 0\\n -showUnderworld 0\\n -showInvisible 0\\n -transitionFrames 5\\n -currentNode \\\"m_particle\\\" \\n -opaqueContainers 0\\n -freeform 1\\n -imagePosition 0 0 \\n -imageScale 1\\n -imageEnabled 0\\n -graphType \\\"DAG\\\" \\n -heatMapDisplay 0\\n -updateSelection 1\\n -updateNodeAdded 1\\n -useDrawOverrideColor 0\\n -limitGraphTraversal -1\\n -range 0 0 \\n -iconSize \\\"largeIcons\\\" \\n\"\n\t\t+ \" -showCachedConnections 0\\n $editorName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"hyperShadePanel\\\" (localizedPanelLabel(\\\"Hypershade\\\")) `;\\n\\tif (\\\"\\\" == $panelName) {\\n\\t\\tif ($useSceneConfig) {\\n\\t\\t\\t$panelName = `scriptedPanel -unParent -type \\\"hyperShadePanel\\\" -l (localizedPanelLabel(\\\"Hypershade\\\")) -mbv $menusOkayInPanels `;\\n\\t\\t}\\n\\t} else {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Hypershade\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"visorPanel\\\" (localizedPanelLabel(\\\"Visor\\\")) `;\\n\\tif (\\\"\\\" == $panelName) {\\n\\t\\tif ($useSceneConfig) {\\n\\t\\t\\t$panelName = `scriptedPanel -unParent -type \\\"visorPanel\\\" -l (localizedPanelLabel(\\\"Visor\\\")) -mbv $menusOkayInPanels `;\\n\\t\\t}\\n\\t} else {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Visor\\\")) -mbv $menusOkayInPanels $panelName;\\n\"\n\t\t+ \"\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"polyTexturePlacementPanel\\\" (localizedPanelLabel(\\\"UV Texture Editor\\\")) `;\\n\\tif (\\\"\\\" == $panelName) {\\n\\t\\tif ($useSceneConfig) {\\n\\t\\t\\t$panelName = `scriptedPanel -unParent -type \\\"polyTexturePlacementPanel\\\" -l (localizedPanelLabel(\\\"UV Texture Editor\\\")) -mbv $menusOkayInPanels `;\\n\\t\\t}\\n\\t} else {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"UV Texture Editor\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"multiListerPanel\\\" (localizedPanelLabel(\\\"Multilister\\\")) `;\\n\\tif (\\\"\\\" == $panelName) {\\n\\t\\tif ($useSceneConfig) {\\n\\t\\t\\t$panelName = `scriptedPanel -unParent -type \\\"multiListerPanel\\\" -l (localizedPanelLabel(\\\"Multilister\\\")) -mbv $menusOkayInPanels `;\\n\\t\\t}\\n\\t} else {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Multilister\\\")) -mbv $menusOkayInPanels $panelName;\\n\"\n\t\t+ \"\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"renderWindowPanel\\\" (localizedPanelLabel(\\\"Render View\\\")) `;\\n\\tif (\\\"\\\" == $panelName) {\\n\\t\\tif ($useSceneConfig) {\\n\\t\\t\\t$panelName = `scriptedPanel -unParent -type \\\"renderWindowPanel\\\" -l (localizedPanelLabel(\\\"Render View\\\")) -mbv $menusOkayInPanels `;\\n\\t\\t}\\n\\t} else {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Render View\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextPanel \\\"blendShapePanel\\\" (localizedPanelLabel(\\\"Blend Shape\\\")) `;\\n\\tif (\\\"\\\" == $panelName) {\\n\\t\\tif ($useSceneConfig) {\\n\\t\\t\\tblendShapePanel -unParent -l (localizedPanelLabel(\\\"Blend Shape\\\")) -mbv $menusOkayInPanels ;\\n\\t\\t}\\n\\t} else {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tblendShapePanel -edit -l (localizedPanelLabel(\\\"Blend Shape\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\"\n\t\t+ \"\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"dynRelEdPanel\\\" (localizedPanelLabel(\\\"Dynamic Relationships\\\")) `;\\n\\tif (\\\"\\\" == $panelName) {\\n\\t\\tif ($useSceneConfig) {\\n\\t\\t\\t$panelName = `scriptedPanel -unParent -type \\\"dynRelEdPanel\\\" -l (localizedPanelLabel(\\\"Dynamic Relationships\\\")) -mbv $menusOkayInPanels `;\\n\\t\\t}\\n\\t} else {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Dynamic Relationships\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextPanel \\\"devicePanel\\\" (localizedPanelLabel(\\\"Devices\\\")) `;\\n\\tif (\\\"\\\" == $panelName) {\\n\\t\\tif ($useSceneConfig) {\\n\\t\\t\\tdevicePanel -unParent -l (localizedPanelLabel(\\\"Devices\\\")) -mbv $menusOkayInPanels ;\\n\\t\\t}\\n\\t} else {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tdevicePanel -edit -l (localizedPanelLabel(\\\"Devices\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\"\n\t\t+ \"\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"relationshipPanel\\\" (localizedPanelLabel(\\\"Relationship Editor\\\")) `;\\n\\tif (\\\"\\\" == $panelName) {\\n\\t\\tif ($useSceneConfig) {\\n\\t\\t\\t$panelName = `scriptedPanel -unParent -type \\\"relationshipPanel\\\" -l (localizedPanelLabel(\\\"Relationship Editor\\\")) -mbv $menusOkayInPanels `;\\n\\t\\t}\\n\\t} else {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Relationship Editor\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"referenceEditorPanel\\\" (localizedPanelLabel(\\\"Reference Editor\\\")) `;\\n\\tif (\\\"\\\" == $panelName) {\\n\\t\\tif ($useSceneConfig) {\\n\\t\\t\\t$panelName = `scriptedPanel -unParent -type \\\"referenceEditorPanel\\\" -l (localizedPanelLabel(\\\"Reference Editor\\\")) -mbv $menusOkayInPanels `;\\n\\t\\t}\\n\\t} else {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Reference Editor\\\")) -mbv $menusOkayInPanels $panelName;\\n\"\n\t\t+ \"\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"componentEditorPanel\\\" (localizedPanelLabel(\\\"Component Editor\\\")) `;\\n\\tif (\\\"\\\" == $panelName) {\\n\\t\\tif ($useSceneConfig) {\\n\\t\\t\\t$panelName = `scriptedPanel -unParent -type \\\"componentEditorPanel\\\" -l (localizedPanelLabel(\\\"Component Editor\\\")) -mbv $menusOkayInPanels `;\\n\\t\\t}\\n\\t} else {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Component Editor\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"dynPaintScriptedPanelType\\\" (localizedPanelLabel(\\\"Paint Effects\\\")) `;\\n\\tif (\\\"\\\" == $panelName) {\\n\\t\\tif ($useSceneConfig) {\\n\\t\\t\\t$panelName = `scriptedPanel -unParent -type \\\"dynPaintScriptedPanelType\\\" -l (localizedPanelLabel(\\\"Paint Effects\\\")) -mbv $menusOkayInPanels `;\\n\\t\\t}\\n\\t} else {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Paint Effects\\\")) -mbv $menusOkayInPanels $panelName;\\n\"\n\t\t+ \"\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"webBrowserPanel\\\" (localizedPanelLabel(\\\"Web Browser\\\")) `;\\n\\tif (\\\"\\\" == $panelName) {\\n\\t\\tif ($useSceneConfig) {\\n\\t\\t\\t$panelName = `scriptedPanel -unParent -type \\\"webBrowserPanel\\\" -l (localizedPanelLabel(\\\"Web Browser\\\")) -mbv $menusOkayInPanels `;\\n\\t\\t}\\n\\t} else {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Web Browser\\\")) -mbv $menusOkayInPanels $panelName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"scriptEditorPanel\\\" (localizedPanelLabel(\\\"Script Editor\\\")) `;\\n\\tif (\\\"\\\" == $panelName) {\\n\\t\\tif ($useSceneConfig) {\\n\\t\\t\\t$panelName = `scriptedPanel -unParent -type \\\"scriptEditorPanel\\\" -l (localizedPanelLabel(\\\"Script Editor\\\")) -mbv $menusOkayInPanels `;\\n\\t\\t}\\n\\t} else {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Script Editor\\\")) -mbv $menusOkayInPanels $panelName;\\n\"\n\t\t+ \"\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\\t\\t}\\n\\t}\\n\\n\\n\\t$panelName = `sceneUIReplacement -getNextScriptedPanel \\\"Stereo\\\" (localizedPanelLabel(\\\"Stereo\\\")) `;\\n\\tif (\\\"\\\" == $panelName) {\\n\\t\\tif ($useSceneConfig) {\\n\\t\\t\\t$panelName = `scriptedPanel -unParent -type \\\"Stereo\\\" -l (localizedPanelLabel(\\\"Stereo\\\")) -mbv $menusOkayInPanels `;\\nstring $editorName = ($panelName+\\\"Editor\\\");\\n stereoCameraView -e \\n -camera \\\"persp\\\" \\n -useInteractiveMode 0\\n -displayLights \\\"default\\\" \\n -displayAppearance \\\"wireframe\\\" \\n -activeOnly 0\\n -wireframeOnShaded 0\\n -headsUpDisplay 1\\n -selectionHiliteDisplay 1\\n -useDefaultMaterial 0\\n -bufferMode \\\"double\\\" \\n -twoSidedLighting 1\\n -backfaceCulling 0\\n -xray 0\\n -jointXray 0\\n -activeComponentsXray 0\\n -displayTextures 0\\n -smoothWireframe 0\\n\"\n\t\t+ \" -lineWidth 1\\n -textureAnisotropic 0\\n -textureHilight 1\\n -textureSampling 2\\n -textureDisplay \\\"modulate\\\" \\n -textureMaxSize 8192\\n -fogging 0\\n -fogSource \\\"fragment\\\" \\n -fogMode \\\"linear\\\" \\n -fogStart 0\\n -fogEnd 100\\n -fogDensity 0.1\\n -fogColor 0.5 0.5 0.5 1 \\n -maxConstantTransparency 1\\n -colorResolution 4 4 \\n -bumpResolution 4 4 \\n -textureCompression 0\\n -transparencyAlgorithm \\\"frontAndBackCull\\\" \\n -transpInShadows 0\\n -cullingOverride \\\"none\\\" \\n -lowQualityLighting 0\\n -maximumNumHardwareLights 0\\n -occlusionCulling 0\\n -shadingModel 0\\n -useBaseRenderer 0\\n -useReducedRenderer 0\\n -smallObjectCulling 0\\n -smallObjectThreshold -1 \\n\"\n\t\t+ \" -interactiveDisableShadows 0\\n -interactiveBackFaceCull 0\\n -sortTransparent 1\\n -nurbsCurves 1\\n -nurbsSurfaces 1\\n -polymeshes 1\\n -subdivSurfaces 1\\n -planes 1\\n -lights 1\\n -cameras 1\\n -controlVertices 1\\n -hulls 1\\n -grid 1\\n -joints 1\\n -ikHandles 1\\n -deformers 1\\n -dynamics 1\\n -fluids 1\\n -hairSystems 1\\n -follicles 1\\n -nCloths 1\\n -nParticles 1\\n -nRigids 1\\n -dynamicConstraints 1\\n -locators 1\\n -manipulators 1\\n -dimensions 1\\n -handles 1\\n -pivots 1\\n -textures 1\\n -strokes 1\\n -shadows 0\\n -displayMode \\\"centerEye\\\" \\n -viewColor 0 0 0 1 \\n\"\n\t\t+ \" $editorName;\\nstereoCameraView -e -viewSelected 0 $editorName;\\n\\t\\t}\\n\\t} else {\\n\\t\\t$label = `panel -q -label $panelName`;\\n\\t\\tscriptedPanel -edit -l (localizedPanelLabel(\\\"Stereo\\\")) -mbv $menusOkayInPanels $panelName;\\nstring $editorName = ($panelName+\\\"Editor\\\");\\n stereoCameraView -e \\n -camera \\\"persp\\\" \\n -useInteractiveMode 0\\n -displayLights \\\"default\\\" \\n -displayAppearance \\\"wireframe\\\" \\n -activeOnly 0\\n -wireframeOnShaded 0\\n -headsUpDisplay 1\\n -selectionHiliteDisplay 1\\n -useDefaultMaterial 0\\n -bufferMode \\\"double\\\" \\n -twoSidedLighting 1\\n -backfaceCulling 0\\n -xray 0\\n -jointXray 0\\n -activeComponentsXray 0\\n -displayTextures 0\\n -smoothWireframe 0\\n -lineWidth 1\\n -textureAnisotropic 0\\n -textureHilight 1\\n -textureSampling 2\\n\"\n\t\t+ \" -textureDisplay \\\"modulate\\\" \\n -textureMaxSize 8192\\n -fogging 0\\n -fogSource \\\"fragment\\\" \\n -fogMode \\\"linear\\\" \\n -fogStart 0\\n -fogEnd 100\\n -fogDensity 0.1\\n -fogColor 0.5 0.5 0.5 1 \\n -maxConstantTransparency 1\\n -colorResolution 4 4 \\n -bumpResolution 4 4 \\n -textureCompression 0\\n -transparencyAlgorithm \\\"frontAndBackCull\\\" \\n -transpInShadows 0\\n -cullingOverride \\\"none\\\" \\n -lowQualityLighting 0\\n -maximumNumHardwareLights 0\\n -occlusionCulling 0\\n -shadingModel 0\\n -useBaseRenderer 0\\n -useReducedRenderer 0\\n -smallObjectCulling 0\\n -smallObjectThreshold -1 \\n -interactiveDisableShadows 0\\n -interactiveBackFaceCull 0\\n -sortTransparent 1\\n\"\n\t\t+ \" -nurbsCurves 1\\n -nurbsSurfaces 1\\n -polymeshes 1\\n -subdivSurfaces 1\\n -planes 1\\n -lights 1\\n -cameras 1\\n -controlVertices 1\\n -hulls 1\\n -grid 1\\n -joints 1\\n -ikHandles 1\\n -deformers 1\\n -dynamics 1\\n -fluids 1\\n -hairSystems 1\\n -follicles 1\\n -nCloths 1\\n -nParticles 1\\n -nRigids 1\\n -dynamicConstraints 1\\n -locators 1\\n -manipulators 1\\n -dimensions 1\\n -handles 1\\n -pivots 1\\n -textures 1\\n -strokes 1\\n -shadows 0\\n -displayMode \\\"centerEye\\\" \\n -viewColor 0 0 0 1 \\n $editorName;\\nstereoCameraView -e -viewSelected 0 $editorName;\\n\\t\\tif (!$useSceneConfig) {\\n\\t\\t\\tpanel -e -l $label $panelName;\\n\"\n\t\t+ \"\\t\\t}\\n\\t}\\n\\n\\n\\tif ($useSceneConfig) {\\n string $configName = `getPanel -cwl (localizedPanelLabel(\\\"Current Layout\\\"))`;\\n if (\\\"\\\" != $configName) {\\n\\t\\t\\tpanelConfiguration -edit -label (localizedPanelLabel(\\\"Current Layout\\\")) \\n\\t\\t\\t\\t-defaultImage \\\"\\\"\\n\\t\\t\\t\\t-image \\\"\\\"\\n\\t\\t\\t\\t-sc false\\n\\t\\t\\t\\t-configString \\\"global string $gMainPane; paneLayout -e -cn \\\\\\\"horizontal2\\\\\\\" -ps 1 100 46 -ps 2 100 54 $gMainPane;\\\"\\n\\t\\t\\t\\t-removeAllPanels\\n\\t\\t\\t\\t-ap false\\n\\t\\t\\t\\t\\t(localizedPanelLabel(\\\"Persp View\\\")) \\n\\t\\t\\t\\t\\t\\\"modelPanel\\\"\\n\"\n\t\t+ \"\\t\\t\\t\\t\\t\\\"$panelName = `modelPanel -unParent -l (localizedPanelLabel(\\\\\\\"Persp View\\\\\\\")) -mbv $menusOkayInPanels `;\\\\n$editorName = $panelName;\\\\nmodelEditor -e \\\\n -cam `findStartUpCamera persp` \\\\n -useInteractiveMode 0\\\\n -displayLights \\\\\\\"default\\\\\\\" \\\\n -displayAppearance \\\\\\\"smoothShaded\\\\\\\" \\\\n -activeOnly 0\\\\n -wireframeOnShaded 0\\\\n -headsUpDisplay 1\\\\n -selectionHiliteDisplay 1\\\\n -useDefaultMaterial 0\\\\n -bufferMode \\\\\\\"double\\\\\\\" \\\\n -twoSidedLighting 1\\\\n -backfaceCulling 0\\\\n -xray 0\\\\n -jointXray 0\\\\n -activeComponentsXray 0\\\\n -displayTextures 0\\\\n -smoothWireframe 0\\\\n -lineWidth 1\\\\n -textureAnisotropic 0\\\\n -textureHilight 1\\\\n -textureSampling 2\\\\n -textureDisplay \\\\\\\"modulate\\\\\\\" \\\\n -textureMaxSize 8192\\\\n -fogging 0\\\\n -fogSource \\\\\\\"fragment\\\\\\\" \\\\n -fogMode \\\\\\\"linear\\\\\\\" \\\\n -fogStart 0\\\\n -fogEnd 100\\\\n -fogDensity 0.1\\\\n -fogColor 0.5 0.5 0.5 1 \\\\n -maxConstantTransparency 1\\\\n -rendererName \\\\\\\"base_OpenGL_Renderer\\\\\\\" \\\\n -colorResolution 256 256 \\\\n -bumpResolution 512 512 \\\\n -textureCompression 0\\\\n -transparencyAlgorithm \\\\\\\"frontAndBackCull\\\\\\\" \\\\n -transpInShadows 0\\\\n -cullingOverride \\\\\\\"none\\\\\\\" \\\\n -lowQualityLighting 0\\\\n -maximumNumHardwareLights 1\\\\n -occlusionCulling 0\\\\n -shadingModel 0\\\\n -useBaseRenderer 0\\\\n -useReducedRenderer 0\\\\n -smallObjectCulling 0\\\\n -smallObjectThreshold -1 \\\\n -interactiveDisableShadows 0\\\\n -interactiveBackFaceCull 0\\\\n -sortTransparent 1\\\\n -nurbsCurves 1\\\\n -nurbsSurfaces 1\\\\n -polymeshes 1\\\\n -subdivSurfaces 1\\\\n -planes 1\\\\n -lights 1\\\\n -cameras 1\\\\n -controlVertices 1\\\\n -hulls 1\\\\n -grid 1\\\\n -joints 1\\\\n -ikHandles 1\\\\n -deformers 1\\\\n -dynamics 1\\\\n -fluids 1\\\\n -hairSystems 1\\\\n -follicles 1\\\\n -nCloths 1\\\\n -nParticles 1\\\\n -nRigids 1\\\\n -dynamicConstraints 1\\\\n -locators 1\\\\n -manipulators 1\\\\n -dimensions 1\\\\n -handles 1\\\\n -pivots 1\\\\n -textures 1\\\\n -strokes 1\\\\n -shadows 0\\\\n $editorName;\\\\nmodelEditor -e -viewSelected 0 $editorName\\\"\\n\"\n\t\t+ \"\\t\\t\\t\\t\\t\\\"modelPanel -edit -l (localizedPanelLabel(\\\\\\\"Persp View\\\\\\\")) -mbv $menusOkayInPanels $panelName;\\\\n$editorName = $panelName;\\\\nmodelEditor -e \\\\n -cam `findStartUpCamera persp` \\\\n -useInteractiveMode 0\\\\n -displayLights \\\\\\\"default\\\\\\\" \\\\n -displayAppearance \\\\\\\"smoothShaded\\\\\\\" \\\\n -activeOnly 0\\\\n -wireframeOnShaded 0\\\\n -headsUpDisplay 1\\\\n -selectionHiliteDisplay 1\\\\n -useDefaultMaterial 0\\\\n -bufferMode \\\\\\\"double\\\\\\\" \\\\n -twoSidedLighting 1\\\\n -backfaceCulling 0\\\\n -xray 0\\\\n -jointXray 0\\\\n -activeComponentsXray 0\\\\n -displayTextures 0\\\\n -smoothWireframe 0\\\\n -lineWidth 1\\\\n -textureAnisotropic 0\\\\n -textureHilight 1\\\\n -textureSampling 2\\\\n -textureDisplay \\\\\\\"modulate\\\\\\\" \\\\n -textureMaxSize 8192\\\\n -fogging 0\\\\n -fogSource \\\\\\\"fragment\\\\\\\" \\\\n -fogMode \\\\\\\"linear\\\\\\\" \\\\n -fogStart 0\\\\n -fogEnd 100\\\\n -fogDensity 0.1\\\\n -fogColor 0.5 0.5 0.5 1 \\\\n -maxConstantTransparency 1\\\\n -rendererName \\\\\\\"base_OpenGL_Renderer\\\\\\\" \\\\n -colorResolution 256 256 \\\\n -bumpResolution 512 512 \\\\n -textureCompression 0\\\\n -transparencyAlgorithm \\\\\\\"frontAndBackCull\\\\\\\" \\\\n -transpInShadows 0\\\\n -cullingOverride \\\\\\\"none\\\\\\\" \\\\n -lowQualityLighting 0\\\\n -maximumNumHardwareLights 1\\\\n -occlusionCulling 0\\\\n -shadingModel 0\\\\n -useBaseRenderer 0\\\\n -useReducedRenderer 0\\\\n -smallObjectCulling 0\\\\n -smallObjectThreshold -1 \\\\n -interactiveDisableShadows 0\\\\n -interactiveBackFaceCull 0\\\\n -sortTransparent 1\\\\n -nurbsCurves 1\\\\n -nurbsSurfaces 1\\\\n -polymeshes 1\\\\n -subdivSurfaces 1\\\\n -planes 1\\\\n -lights 1\\\\n -cameras 1\\\\n -controlVertices 1\\\\n -hulls 1\\\\n -grid 1\\\\n -joints 1\\\\n -ikHandles 1\\\\n -deformers 1\\\\n -dynamics 1\\\\n -fluids 1\\\\n -hairSystems 1\\\\n -follicles 1\\\\n -nCloths 1\\\\n -nParticles 1\\\\n -nRigids 1\\\\n -dynamicConstraints 1\\\\n -locators 1\\\\n -manipulators 1\\\\n -dimensions 1\\\\n -handles 1\\\\n -pivots 1\\\\n -textures 1\\\\n -strokes 1\\\\n -shadows 0\\\\n $editorName;\\\\nmodelEditor -e -viewSelected 0 $editorName\\\"\\n\"\n\t\t+ \"\\t\\t\\t\\t-ap false\\n\\t\\t\\t\\t\\t(localizedPanelLabel(\\\"Hypergraph Hierarchy\\\")) \\n\\t\\t\\t\\t\\t\\\"scriptedPanel\\\"\\n\\t\\t\\t\\t\\t\\\"$panelName = `scriptedPanel -unParent -type \\\\\\\"hyperGraphPanel\\\\\\\" -l (localizedPanelLabel(\\\\\\\"Hypergraph Hierarchy\\\\\\\")) -mbv $menusOkayInPanels `;\\\\n\\\\n\\\\t\\\\t\\\\t$editorName = ($panelName+\\\\\\\"HyperGraphEd\\\\\\\");\\\\n hyperGraph -e \\\\n -graphLayoutStyle \\\\\\\"hierarchicalLayout\\\\\\\" \\\\n -orientation \\\\\\\"horiz\\\\\\\" \\\\n -mergeConnections 1\\\\n -zoom 0.8425\\\\n -animateTransition 0\\\\n -showRelationships 1\\\\n -showShapes 0\\\\n -showDeformers 0\\\\n -showExpressions 0\\\\n -showConstraints 0\\\\n -showUnderworld 0\\\\n -showInvisible 0\\\\n -transitionFrames 5\\\\n -currentNode \\\\\\\"m_particle\\\\\\\" \\\\n -opaqueContainers 0\\\\n -freeform 1\\\\n -imagePosition 0 0 \\\\n -imageScale 1\\\\n -imageEnabled 0\\\\n -graphType \\\\\\\"DAG\\\\\\\" \\\\n -heatMapDisplay 0\\\\n -updateSelection 1\\\\n -updateNodeAdded 1\\\\n -useDrawOverrideColor 0\\\\n -limitGraphTraversal -1\\\\n -range 0 0 \\\\n -iconSize \\\\\\\"largeIcons\\\\\\\" \\\\n -showCachedConnections 0\\\\n $editorName\\\"\\n\"\n\t\t+ \"\\t\\t\\t\\t\\t\\\"scriptedPanel -edit -l (localizedPanelLabel(\\\\\\\"Hypergraph Hierarchy\\\\\\\")) -mbv $menusOkayInPanels $panelName;\\\\n\\\\n\\\\t\\\\t\\\\t$editorName = ($panelName+\\\\\\\"HyperGraphEd\\\\\\\");\\\\n hyperGraph -e \\\\n -graphLayoutStyle \\\\\\\"hierarchicalLayout\\\\\\\" \\\\n -orientation \\\\\\\"horiz\\\\\\\" \\\\n -mergeConnections 1\\\\n -zoom 0.8425\\\\n -animateTransition 0\\\\n -showRelationships 1\\\\n -showShapes 0\\\\n -showDeformers 0\\\\n -showExpressions 0\\\\n -showConstraints 0\\\\n -showUnderworld 0\\\\n -showInvisible 0\\\\n -transitionFrames 5\\\\n -currentNode \\\\\\\"m_particle\\\\\\\" \\\\n -opaqueContainers 0\\\\n -freeform 1\\\\n -imagePosition 0 0 \\\\n -imageScale 1\\\\n -imageEnabled 0\\\\n -graphType \\\\\\\"DAG\\\\\\\" \\\\n -heatMapDisplay 0\\\\n -updateSelection 1\\\\n -updateNodeAdded 1\\\\n -useDrawOverrideColor 0\\\\n -limitGraphTraversal -1\\\\n -range 0 0 \\\\n -iconSize \\\\\\\"largeIcons\\\\\\\" \\\\n -showCachedConnections 0\\\\n $editorName\\\"\\n\"\n\t\t+ \"\\t\\t\\t\\t$configName;\\n\\n setNamedPanelLayout (localizedPanelLabel(\\\"Current Layout\\\"));\\n }\\n\\n panelHistory -e -clear mainPanelHistory;\\n setFocus `paneLayout -q -p1 $gMainPane`;\\n sceneUIReplacement -deleteRemaining;\\n sceneUIReplacement -clear;\\n\\t}\\n\\n\\ngrid -spacing 5 -size 12 -divisions 5 -displayAxes yes -displayGridLines yes -displayDivisionLines yes -displayPerspectiveLabels no -displayOrthographicLabels no -displayAxesBold yes -perspectiveLabelPosition axis -orthographicLabelPosition edge;\\nviewManip -drawCompass 0 -compassAngle 0 -frontParameters \\\"\\\" -homeParameters \\\"\\\" -selectionLockParameters \\\"\\\";\\n}\\n\");\n\tsetAttr \".st\" 3;\ncreateNode script -n \"sceneConfigurationScriptNode\";\n\tsetAttr \".b\" -type \"string\" \"playbackOptions -min 1 -max 24 -ast 1 -aet 48 \";\n\tsetAttr \".st\" 6;\ncreateNode script -n \"rg_export\";\n\taddAttr -ci true -sn \"time\" -ln \"time\" -dt \"string\";\n\tsetAttr \".time\" -type \"string\" \"2012-01-01T23:14:52.485000\";\nselect -ne :time1;\n\tsetAttr \".o\" 1;\nselect -ne :renderPartition;\n\tsetAttr -s 4 \".st\";\nselect -ne :renderGlobalsList1;\nselect -ne :defaultShaderList1;\n\tsetAttr -s 4 \".s\";\nselect -ne :postProcessList1;\n\tsetAttr -s 2 \".p\";\nselect -ne :lightList1;\nselect -ne :initialShadingGroup;\n\tsetAttr \".ro\" yes;\nselect -ne :initialParticleSE;\n\tsetAttr \".ro\" yes;\nselect -ne :hardwareRenderGlobals;\n\tsetAttr \".ctrs\" 256;\n\tsetAttr \".btrs\" 512;\nselect -ne :defaultHardwareRenderGlobals;\n\tsetAttr \".fn\" -type \"string\" \"im\";\n\tsetAttr \".res\" -type \"string\" \"ntsc_4d 646 485 1.333\";\nconnectAttr \"polySphere1.out\" \"m_particleShape.i\";\nconnectAttr \"polySphere2.out\" \"phys_particleShape.i\";\nconnectAttr \":defaultLightSet.msg\" \"lightLinker1.lnk[0].llnk\";\nconnectAttr \":initialShadingGroup.msg\" \"lightLinker1.lnk[0].olnk\";\nconnectAttr \":defaultLightSet.msg\" \"lightLinker1.lnk[1].llnk\";\nconnectAttr \":initialParticleSE.msg\" \"lightLinker1.lnk[1].olnk\";\nconnectAttr \":defaultLightSet.msg\" \"lightLinker1.lnk[2].llnk\";\nconnectAttr \"phong1SG.msg\" \"lightLinker1.lnk[2].olnk\";\nconnectAttr \":defaultLightSet.msg\" \"lightLinker1.lnk[3].llnk\";\nconnectAttr \"phong2SG.msg\" \"lightLinker1.lnk[3].olnk\";\nconnectAttr \":defaultLightSet.msg\" \"lightLinker1.slnk[0].sllk\";\nconnectAttr \":initialShadingGroup.msg\" \"lightLinker1.slnk[0].solk\";\nconnectAttr \":defaultLightSet.msg\" \"lightLinker1.slnk[1].sllk\";\nconnectAttr \":initialParticleSE.msg\" \"lightLinker1.slnk[1].solk\";\nconnectAttr \":defaultLightSet.msg\" \"lightLinker1.slnk[2].sllk\";\nconnectAttr \"phong1SG.msg\" \"lightLinker1.slnk[2].solk\";\nconnectAttr \":defaultLightSet.msg\" \"lightLinker1.slnk[3].sllk\";\nconnectAttr \"phong2SG.msg\" \"lightLinker1.slnk[3].solk\";\nconnectAttr \"layerManager.dli[0]\" \"defaultLayer.id\";\nconnectAttr \"renderLayerManager.rlmi[0]\" \"defaultRenderLayer.rlid\";\nconnectAttr \"mat_mud.oc\" \"phong1SG.ss\";\nconnectAttr \"m_particleShape.iog\" \"phong1SG.dsm\" -na;\nconnectAttr \"phong1SG.msg\" \"materialInfo1.sg\";\nconnectAttr \"mat_mud.msg\" \"materialInfo1.m\";\nconnectAttr \"mat_phys.oc\" \"phong2SG.ss\";\nconnectAttr \"phys_particleShape.iog\" \"phong2SG.dsm\" -na;\nconnectAttr \"phong2SG.msg\" \"materialInfo2.sg\";\nconnectAttr \"mat_phys.msg\" \"materialInfo2.m\";\nconnectAttr \"phong1SG.pa\" \":renderPartition.st\" -na;\nconnectAttr \"phong2SG.pa\" \":renderPartition.st\" -na;\nconnectAttr \"mat_mud.msg\" \":defaultShaderList1.s\" -na;\nconnectAttr \"mat_phys.msg\" \":defaultShaderList1.s\" -na;\nconnectAttr \"lightLinker1.msg\" \":lightList1.ln\" -na;\n\/\/ End of mud_particle_01.ma\n","avg_line_length":281.0690909091,"max_line_length":2206,"alphanum_fraction":0.5591766502} {"size":10435,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"(* Content-type: 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Sin[x])^3 Cos[x]^9 + 10 (I Sin[x])^9 Cos[x]^3 + 1 (I Sin[x])^1 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^1) + Exp[9 I y] (2 (I Sin[x])^8 Cos[x]^4 + 2 (I Sin[x])^4 Cos[x]^8 + 8 (I Sin[x])^6 Cos[x]^6 + 5 (I Sin[x])^5 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^5) + Exp[11 I y] (1 (I Sin[x])^3 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^3))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-11 I y] (1 (I Sin[x])^5 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^5) + Exp[-9 I y] (3 (I Sin[x])^4 Cos[x]^8 + 3 (I Sin[x])^8 Cos[x]^4 + 6 (I Sin[x])^6 Cos[x]^6 + 5 (I Sin[x])^5 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^5) + Exp[-7 I y] (40 (I Sin[x])^6 Cos[x]^6 + 10 (I Sin[x])^4 Cos[x]^8 + 10 (I Sin[x])^8 Cos[x]^4 + 24 (I Sin[x])^5 Cos[x]^7 + 24 (I Sin[x])^7 Cos[x]^5 + 1 (I Sin[x])^3 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^3) + Exp[-5 I y] (16 (I Sin[x])^3 Cos[x]^9 + 16 (I Sin[x])^9 Cos[x]^3 + 69 (I Sin[x])^5 Cos[x]^7 + 69 (I Sin[x])^7 Cos[x]^5 + 84 (I Sin[x])^6 Cos[x]^6 + 36 (I Sin[x])^4 Cos[x]^8 + 36 (I Sin[x])^8 Cos[x]^4 + 2 (I Sin[x])^2 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^2) + Exp[-3 I y] (141 (I Sin[x])^7 Cos[x]^5 + 141 (I Sin[x])^5 Cos[x]^7 + 152 (I Sin[x])^6 Cos[x]^6 + 80 (I Sin[x])^8 Cos[x]^4 + 80 (I Sin[x])^4 Cos[x]^8 + 29 (I Sin[x])^3 Cos[x]^9 + 29 (I Sin[x])^9 Cos[x]^3 + 4 (I Sin[x])^2 Cos[x]^10 + 4 (I Sin[x])^10 Cos[x]^2) + Exp[-1 I y] (122 (I Sin[x])^4 Cos[x]^8 + 122 (I Sin[x])^8 Cos[x]^4 + 20 (I Sin[x])^2 Cos[x]^10 + 20 (I Sin[x])^10 Cos[x]^2 + 188 (I Sin[x])^6 Cos[x]^6 + 169 (I Sin[x])^5 Cos[x]^7 + 169 (I Sin[x])^7 Cos[x]^5 + 54 (I Sin[x])^3 Cos[x]^9 + 54 (I Sin[x])^9 Cos[x]^3 + 3 (I Sin[x])^1 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^1) + Exp[1 I y] (228 (I Sin[x])^6 Cos[x]^6 + 108 (I Sin[x])^4 Cos[x]^8 + 108 (I Sin[x])^8 Cos[x]^4 + 179 (I Sin[x])^5 Cos[x]^7 + 179 (I Sin[x])^7 Cos[x]^5 + 45 (I Sin[x])^3 Cos[x]^9 + 45 (I Sin[x])^9 Cos[x]^3 + 14 (I Sin[x])^10 Cos[x]^2 + 14 (I Sin[x])^2 Cos[x]^10 + 2 (I Sin[x])^1 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^1) + Exp[3 I y] (49 (I Sin[x])^3 Cos[x]^9 + 49 (I Sin[x])^9 Cos[x]^3 + 115 (I Sin[x])^5 Cos[x]^7 + 115 (I Sin[x])^7 Cos[x]^5 + 132 (I Sin[x])^6 Cos[x]^6 + 75 (I Sin[x])^4 Cos[x]^8 + 75 (I Sin[x])^8 Cos[x]^4 + 18 (I Sin[x])^2 Cos[x]^10 + 18 (I Sin[x])^10 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^11 + 6 (I Sin[x])^11 Cos[x]^1 + 1 Cos[x]^12 + 1 (I Sin[x])^12) + Exp[5 I y] (70 (I Sin[x])^7 Cos[x]^5 + 70 (I Sin[x])^5 Cos[x]^7 + 76 (I Sin[x])^6 Cos[x]^6 + 40 (I Sin[x])^8 Cos[x]^4 + 40 (I Sin[x])^4 Cos[x]^8 + 15 (I Sin[x])^3 Cos[x]^9 + 15 (I Sin[x])^9 Cos[x]^3 + 2 (I Sin[x])^2 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^2) + Exp[7 I y] (19 (I Sin[x])^4 Cos[x]^8 + 19 (I Sin[x])^8 Cos[x]^4 + 10 (I Sin[x])^6 Cos[x]^6 + 14 (I Sin[x])^7 Cos[x]^5 + 14 (I Sin[x])^5 Cos[x]^7 + 6 (I Sin[x])^2 Cos[x]^10 + 6 (I Sin[x])^10 Cos[x]^2 + 10 (I Sin[x])^3 Cos[x]^9 + 10 (I Sin[x])^9 Cos[x]^3 + 1 (I Sin[x])^1 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^1) + Exp[9 I y] (2 (I Sin[x])^8 Cos[x]^4 + 2 (I Sin[x])^4 Cos[x]^8 + 8 (I Sin[x])^6 Cos[x]^6 + 5 (I Sin[x])^5 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^5) + Exp[11 I y] (1 (I Sin[x])^3 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Cos[x]^8 + 44 (I Sin[x])^8 Cos[x]^4 + 49 (I Sin[x])^5 Cos[x]^7 + 49 (I Sin[x])^7 Cos[x]^5 + 30 (I Sin[x])^3 Cos[x]^9 + 30 (I Sin[x])^9 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^10 + 12 (I Sin[x])^10 Cos[x]^2 + 1 (I Sin[x])^11 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^11) + Exp[-3 I y] (80 (I Sin[x])^4 Cos[x]^8 + 80 (I Sin[x])^8 Cos[x]^4 + 50 (I Sin[x])^3 Cos[x]^9 + 50 (I Sin[x])^9 Cos[x]^3 + 132 (I Sin[x])^6 Cos[x]^6 + 103 (I Sin[x])^7 Cos[x]^5 + 103 (I Sin[x])^5 Cos[x]^7 + 24 (I Sin[x])^2 Cos[x]^10 + 24 (I Sin[x])^10 Cos[x]^2 + 7 (I Sin[x])^1 Cos[x]^11 + 7 (I Sin[x])^11 Cos[x]^1) + Exp[-1 I y] (189 (I Sin[x])^5 Cos[x]^7 + 189 (I Sin[x])^7 Cos[x]^5 + 47 (I Sin[x])^3 Cos[x]^9 + 47 (I Sin[x])^9 Cos[x]^3 + 120 (I Sin[x])^4 Cos[x]^8 + 120 (I Sin[x])^8 Cos[x]^4 + 200 (I Sin[x])^6 Cos[x]^6 + 6 (I Sin[x])^10 Cos[x]^2 + 6 (I Sin[x])^2 Cos[x]^10) + Exp[1 I y] (57 (I Sin[x])^3 Cos[x]^9 + 57 (I Sin[x])^9 Cos[x]^3 + 179 (I Sin[x])^7 Cos[x]^5 + 179 (I Sin[x])^5 Cos[x]^7 + 16 (I Sin[x])^2 Cos[x]^10 + 16 (I Sin[x])^10 Cos[x]^2 + 118 (I Sin[x])^8 Cos[x]^4 + 118 (I Sin[x])^4 Cos[x]^8 + 184 (I Sin[x])^6 Cos[x]^6) + Exp[3 I y] (68 (I Sin[x])^4 Cos[x]^8 + 68 (I Sin[x])^8 Cos[x]^4 + 204 (I Sin[x])^6 Cos[x]^6 + 149 (I Sin[x])^5 Cos[x]^7 + 149 (I Sin[x])^7 Cos[x]^5 + 11 (I Sin[x])^9 Cos[x]^3 + 11 (I Sin[x])^3 Cos[x]^9) + Exp[5 I y] (40 (I Sin[x])^4 Cos[x]^8 + 40 (I Sin[x])^8 Cos[x]^4 + 90 (I Sin[x])^6 Cos[x]^6 + 13 (I Sin[x])^3 Cos[x]^9 + 13 (I Sin[x])^9 Cos[x]^3 + 67 (I Sin[x])^7 Cos[x]^5 + 67 (I Sin[x])^5 Cos[x]^7) + Exp[7 I y] (30 (I Sin[x])^5 Cos[x]^7 + 30 (I Sin[x])^7 Cos[x]^5 + 38 (I Sin[x])^6 Cos[x]^6 + 6 (I Sin[x])^8 Cos[x]^4 + 6 (I Sin[x])^4 Cos[x]^8) + Exp[9 I y] (6 (I Sin[x])^5 Cos[x]^7 + 6 (I Sin[x])^7 Cos[x]^5 + 3 (I Sin[x])^4 Cos[x]^8 + 3 (I Sin[x])^8 Cos[x]^4 + 4 (I Sin[x])^6 Cos[x]^6) + Exp[11 I y] (2 (I Sin[x])^6 Cos[x]^6))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-11 I y] (2 (I Sin[x])^6 Cos[x]^6) + Exp[-9 I y] (3 (I Sin[x])^7 Cos[x]^5 + 3 (I Sin[x])^5 Cos[x]^7 + 2 (I Sin[x])^6 Cos[x]^6 + 2 (I Sin[x])^4 Cos[x]^8 + 2 (I Sin[x])^8 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^9 + 2 (I Sin[x])^9 Cos[x]^3 + 2 (I Sin[x])^2 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^1) + Exp[-7 I y] (17 (I Sin[x])^5 Cos[x]^7 + 17 (I Sin[x])^7 Cos[x]^5 + 14 (I Sin[x])^4 Cos[x]^8 + 14 (I Sin[x])^8 Cos[x]^4 + 10 (I Sin[x])^3 Cos[x]^9 + 10 (I Sin[x])^9 Cos[x]^3 + 6 (I Sin[x])^2 Cos[x]^10 + 6 (I Sin[x])^10 Cos[x]^2 + 8 (I Sin[x])^6 Cos[x]^6 + 3 (I Sin[x])^1 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^1 + 1 Cos[x]^12 + 1 (I Sin[x])^12) + Exp[-5 I y] (58 (I Sin[x])^6 Cos[x]^6 + 44 (I Sin[x])^4 Cos[x]^8 + 44 (I Sin[x])^8 Cos[x]^4 + 49 (I Sin[x])^5 Cos[x]^7 + 49 (I Sin[x])^7 Cos[x]^5 + 30 (I Sin[x])^3 Cos[x]^9 + 30 (I Sin[x])^9 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^10 + 12 (I Sin[x])^10 Cos[x]^2 + 1 (I Sin[x])^11 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^11) + Exp[-3 I y] (80 (I Sin[x])^4 Cos[x]^8 + 80 (I Sin[x])^8 Cos[x]^4 + 50 (I Sin[x])^3 Cos[x]^9 + 50 (I Sin[x])^9 Cos[x]^3 + 132 (I Sin[x])^6 Cos[x]^6 + 103 (I Sin[x])^7 Cos[x]^5 + 103 (I Sin[x])^5 Cos[x]^7 + 24 (I Sin[x])^2 Cos[x]^10 + 24 (I Sin[x])^10 Cos[x]^2 + 7 (I Sin[x])^1 Cos[x]^11 + 7 (I Sin[x])^11 Cos[x]^1) + Exp[-1 I y] (189 (I Sin[x])^5 Cos[x]^7 + 189 (I Sin[x])^7 Cos[x]^5 + 47 (I Sin[x])^3 Cos[x]^9 + 47 (I Sin[x])^9 Cos[x]^3 + 120 (I Sin[x])^4 Cos[x]^8 + 120 (I Sin[x])^8 Cos[x]^4 + 200 (I Sin[x])^6 Cos[x]^6 + 6 (I Sin[x])^10 Cos[x]^2 + 6 (I Sin[x])^2 Cos[x]^10) + Exp[1 I y] (57 (I Sin[x])^3 Cos[x]^9 + 57 (I Sin[x])^9 Cos[x]^3 + 179 (I Sin[x])^7 Cos[x]^5 + 179 (I Sin[x])^5 Cos[x]^7 + 16 (I Sin[x])^2 Cos[x]^10 + 16 (I Sin[x])^10 Cos[x]^2 + 118 (I Sin[x])^8 Cos[x]^4 + 118 (I Sin[x])^4 Cos[x]^8 + 184 (I Sin[x])^6 Cos[x]^6) + Exp[3 I y] (68 (I Sin[x])^4 Cos[x]^8 + 68 (I Sin[x])^8 Cos[x]^4 + 204 (I Sin[x])^6 Cos[x]^6 + 149 (I Sin[x])^5 Cos[x]^7 + 149 (I Sin[x])^7 Cos[x]^5 + 11 (I Sin[x])^9 Cos[x]^3 + 11 (I Sin[x])^3 Cos[x]^9) + Exp[5 I y] (40 (I Sin[x])^4 Cos[x]^8 + 40 (I Sin[x])^8 Cos[x]^4 + 90 (I Sin[x])^6 Cos[x]^6 + 13 (I Sin[x])^3 Cos[x]^9 + 13 (I Sin[x])^9 Cos[x]^3 + 67 (I Sin[x])^7 Cos[x]^5 + 67 (I Sin[x])^5 Cos[x]^7) + Exp[7 I y] (30 (I Sin[x])^5 Cos[x]^7 + 30 (I Sin[x])^7 Cos[x]^5 + 38 (I Sin[x])^6 Cos[x]^6 + 6 (I Sin[x])^8 Cos[x]^4 + 6 (I Sin[x])^4 Cos[x]^8) + Exp[9 I y] (6 (I Sin[x])^5 Cos[x]^7 + 6 (I Sin[x])^7 Cos[x]^5 + 3 (I Sin[x])^4 Cos[x]^8 + 3 (I Sin[x])^8 Cos[x]^4 + 4 (I Sin[x])^6 Cos[x]^6) + Exp[11 I y] (2 (I Sin[x])^6 Cos[x]^6));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":377.4,"max_line_length":2613,"alphanum_fraction":0.4910793146} {"size":10259,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 16;\nname = \"16v5 3 5 1 2\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4) + Exp[-13 I y] (3 (I Sin[x])^5 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^6 Cos[x]^10 + 4 (I Sin[x])^10 Cos[x]^6 + 5 (I Sin[x])^9 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^9 + 6 (I Sin[x])^8 Cos[x]^8) + Exp[-11 I y] (22 (I Sin[x])^5 Cos[x]^11 + 22 (I Sin[x])^11 Cos[x]^5 + 9 (I Sin[x])^3 Cos[x]^13 + 9 (I Sin[x])^13 Cos[x]^3 + 10 (I Sin[x])^4 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^4 + 23 (I Sin[x])^6 Cos[x]^10 + 23 (I Sin[x])^10 Cos[x]^6 + 24 (I Sin[x])^7 Cos[x]^9 + 24 (I Sin[x])^9 Cos[x]^7 + 24 (I Sin[x])^8 Cos[x]^8 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[-9 I y] (40 (I Sin[x])^4 Cos[x]^12 + 40 (I Sin[x])^12 Cos[x]^4 + 110 (I Sin[x])^10 Cos[x]^6 + 110 (I Sin[x])^6 Cos[x]^10 + 146 (I Sin[x])^7 Cos[x]^9 + 146 (I Sin[x])^9 Cos[x]^7 + 63 (I Sin[x])^5 Cos[x]^11 + 63 (I Sin[x])^11 Cos[x]^5 + 156 (I Sin[x])^8 Cos[x]^8 + 15 (I Sin[x])^13 Cos[x]^3 + 15 (I Sin[x])^3 Cos[x]^13 + 3 (I Sin[x])^14 Cos[x]^2 + 3 (I Sin[x])^2 Cos[x]^14) + Exp[-7 I y] (315 (I Sin[x])^6 Cos[x]^10 + 315 (I Sin[x])^10 Cos[x]^6 + 159 (I Sin[x])^4 Cos[x]^12 + 159 (I Sin[x])^12 Cos[x]^4 + 227 (I Sin[x])^5 Cos[x]^11 + 227 (I Sin[x])^11 Cos[x]^5 + 364 (I Sin[x])^7 Cos[x]^9 + 364 (I Sin[x])^9 Cos[x]^7 + 382 (I Sin[x])^8 Cos[x]^8 + 75 (I Sin[x])^3 Cos[x]^13 + 75 (I Sin[x])^13 Cos[x]^3 + 27 (I Sin[x])^2 Cos[x]^14 + 27 (I Sin[x])^14 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^15 + 6 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[-5 I y] (472 (I Sin[x])^5 Cos[x]^11 + 472 (I Sin[x])^11 Cos[x]^5 + 977 (I Sin[x])^9 Cos[x]^7 + 977 (I Sin[x])^7 Cos[x]^9 + 1082 (I Sin[x])^8 Cos[x]^8 + 738 (I Sin[x])^10 Cos[x]^6 + 738 (I Sin[x])^6 Cos[x]^10 + 200 (I Sin[x])^12 Cos[x]^4 + 200 (I Sin[x])^4 Cos[x]^12 + 61 (I Sin[x])^13 Cos[x]^3 + 61 (I Sin[x])^3 Cos[x]^13 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[-3 I y] (1524 (I Sin[x])^7 Cos[x]^9 + 1524 (I Sin[x])^9 Cos[x]^7 + 819 (I Sin[x])^5 Cos[x]^11 + 819 (I Sin[x])^11 Cos[x]^5 + 1201 (I Sin[x])^6 Cos[x]^10 + 1201 (I Sin[x])^10 Cos[x]^6 + 1640 (I Sin[x])^8 Cos[x]^8 + 420 (I Sin[x])^4 Cos[x]^12 + 420 (I Sin[x])^12 Cos[x]^4 + 170 (I Sin[x])^3 Cos[x]^13 + 170 (I Sin[x])^13 Cos[x]^3 + 44 (I Sin[x])^2 Cos[x]^14 + 44 (I Sin[x])^14 Cos[x]^2 + 7 (I Sin[x])^1 Cos[x]^15 + 7 (I Sin[x])^15 Cos[x]^1) + Exp[-1 I y] (1618 (I Sin[x])^6 Cos[x]^10 + 1618 (I Sin[x])^10 Cos[x]^6 + 302 (I Sin[x])^12 Cos[x]^4 + 302 (I Sin[x])^4 Cos[x]^12 + 2604 (I Sin[x])^8 Cos[x]^8 + 2330 (I Sin[x])^9 Cos[x]^7 + 2330 (I Sin[x])^7 Cos[x]^9 + 793 (I Sin[x])^11 Cos[x]^5 + 793 (I Sin[x])^5 Cos[x]^11 + 77 (I Sin[x])^3 Cos[x]^13 + 77 (I Sin[x])^13 Cos[x]^3 + 13 (I Sin[x])^2 Cos[x]^14 + 13 (I Sin[x])^14 Cos[x]^2) + Exp[1 I y] (2404 (I Sin[x])^8 Cos[x]^8 + 397 (I Sin[x])^4 Cos[x]^12 + 397 (I Sin[x])^12 Cos[x]^4 + 1619 (I Sin[x])^6 Cos[x]^10 + 1619 (I Sin[x])^10 Cos[x]^6 + 919 (I Sin[x])^5 Cos[x]^11 + 919 (I Sin[x])^11 Cos[x]^5 + 2174 (I Sin[x])^7 Cos[x]^9 + 2174 (I Sin[x])^9 Cos[x]^7 + 107 (I Sin[x])^3 Cos[x]^13 + 107 (I Sin[x])^13 Cos[x]^3 + 17 (I Sin[x])^2 Cos[x]^14 + 17 (I Sin[x])^14 Cos[x]^2) + Exp[3 I y] (546 (I Sin[x])^5 Cos[x]^11 + 546 (I Sin[x])^11 Cos[x]^5 + 1945 (I Sin[x])^9 Cos[x]^7 + 1945 (I Sin[x])^7 Cos[x]^9 + 2298 (I Sin[x])^8 Cos[x]^8 + 1176 (I Sin[x])^10 Cos[x]^6 + 1176 (I Sin[x])^6 Cos[x]^10 + 160 (I Sin[x])^4 Cos[x]^12 + 160 (I Sin[x])^12 Cos[x]^4 + 29 (I Sin[x])^3 Cos[x]^13 + 29 (I Sin[x])^13 Cos[x]^3) + Exp[5 I y] (1149 (I Sin[x])^7 Cos[x]^9 + 1149 (I Sin[x])^9 Cos[x]^7 + 346 (I Sin[x])^5 Cos[x]^11 + 346 (I Sin[x])^11 Cos[x]^5 + 17 (I Sin[x])^3 Cos[x]^13 + 17 (I Sin[x])^13 Cos[x]^3 + 98 (I Sin[x])^4 Cos[x]^12 + 98 (I Sin[x])^12 Cos[x]^4 + 1304 (I Sin[x])^8 Cos[x]^8 + 741 (I Sin[x])^6 Cos[x]^10 + 741 (I Sin[x])^10 Cos[x]^6) + Exp[7 I y] (26 (I Sin[x])^4 Cos[x]^12 + 26 (I Sin[x])^12 Cos[x]^4 + 664 (I Sin[x])^8 Cos[x]^8 + 335 (I Sin[x])^6 Cos[x]^10 + 335 (I Sin[x])^10 Cos[x]^6 + 556 (I Sin[x])^9 Cos[x]^7 + 556 (I Sin[x])^7 Cos[x]^9 + 116 (I Sin[x])^5 Cos[x]^11 + 116 (I Sin[x])^11 Cos[x]^5) + Exp[9 I y] (244 (I Sin[x])^8 Cos[x]^8 + 102 (I Sin[x])^6 Cos[x]^10 + 102 (I Sin[x])^10 Cos[x]^6 + 7 (I Sin[x])^4 Cos[x]^12 + 7 (I Sin[x])^12 Cos[x]^4 + 32 (I Sin[x])^5 Cos[x]^11 + 32 (I Sin[x])^11 Cos[x]^5 + 192 (I Sin[x])^9 Cos[x]^7 + 192 (I Sin[x])^7 Cos[x]^9) + Exp[11 I y] (9 (I Sin[x])^5 Cos[x]^11 + 9 (I Sin[x])^11 Cos[x]^5 + 47 (I Sin[x])^7 Cos[x]^9 + 47 (I Sin[x])^9 Cos[x]^7 + 22 (I Sin[x])^10 Cos[x]^6 + 22 (I Sin[x])^6 Cos[x]^10 + 54 (I Sin[x])^8 Cos[x]^8) + Exp[13 I y] (7 (I Sin[x])^9 Cos[x]^7 + 7 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^5 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^5 + 3 (I Sin[x])^6 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^6 + 8 (I Sin[x])^8 Cos[x]^8) + Exp[15 I y] (1 (I Sin[x])^6 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^6))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4) + Exp[-13 I y] (3 (I Sin[x])^5 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^6 Cos[x]^10 + 4 (I Sin[x])^10 Cos[x]^6 + 5 (I Sin[x])^9 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^9 + 6 (I Sin[x])^8 Cos[x]^8) + Exp[-11 I y] (22 (I Sin[x])^5 Cos[x]^11 + 22 (I Sin[x])^11 Cos[x]^5 + 9 (I Sin[x])^3 Cos[x]^13 + 9 (I Sin[x])^13 Cos[x]^3 + 10 (I Sin[x])^4 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^4 + 23 (I Sin[x])^6 Cos[x]^10 + 23 (I Sin[x])^10 Cos[x]^6 + 24 (I Sin[x])^7 Cos[x]^9 + 24 (I Sin[x])^9 Cos[x]^7 + 24 (I Sin[x])^8 Cos[x]^8 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[-9 I y] (40 (I Sin[x])^4 Cos[x]^12 + 40 (I Sin[x])^12 Cos[x]^4 + 110 (I Sin[x])^10 Cos[x]^6 + 110 (I Sin[x])^6 Cos[x]^10 + 146 (I Sin[x])^7 Cos[x]^9 + 146 (I Sin[x])^9 Cos[x]^7 + 63 (I Sin[x])^5 Cos[x]^11 + 63 (I Sin[x])^11 Cos[x]^5 + 156 (I Sin[x])^8 Cos[x]^8 + 15 (I Sin[x])^13 Cos[x]^3 + 15 (I Sin[x])^3 Cos[x]^13 + 3 (I Sin[x])^14 Cos[x]^2 + 3 (I Sin[x])^2 Cos[x]^14) + Exp[-7 I y] (315 (I Sin[x])^6 Cos[x]^10 + 315 (I Sin[x])^10 Cos[x]^6 + 159 (I Sin[x])^4 Cos[x]^12 + 159 (I Sin[x])^12 Cos[x]^4 + 227 (I Sin[x])^5 Cos[x]^11 + 227 (I Sin[x])^11 Cos[x]^5 + 364 (I Sin[x])^7 Cos[x]^9 + 364 (I Sin[x])^9 Cos[x]^7 + 382 (I Sin[x])^8 Cos[x]^8 + 75 (I Sin[x])^3 Cos[x]^13 + 75 (I Sin[x])^13 Cos[x]^3 + 27 (I Sin[x])^2 Cos[x]^14 + 27 (I Sin[x])^14 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^15 + 6 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[-5 I y] (472 (I Sin[x])^5 Cos[x]^11 + 472 (I Sin[x])^11 Cos[x]^5 + 977 (I Sin[x])^9 Cos[x]^7 + 977 (I Sin[x])^7 Cos[x]^9 + 1082 (I Sin[x])^8 Cos[x]^8 + 738 (I Sin[x])^10 Cos[x]^6 + 738 (I Sin[x])^6 Cos[x]^10 + 200 (I Sin[x])^12 Cos[x]^4 + 200 (I Sin[x])^4 Cos[x]^12 + 61 (I Sin[x])^13 Cos[x]^3 + 61 (I Sin[x])^3 Cos[x]^13 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[-3 I y] (1524 (I Sin[x])^7 Cos[x]^9 + 1524 (I Sin[x])^9 Cos[x]^7 + 819 (I Sin[x])^5 Cos[x]^11 + 819 (I Sin[x])^11 Cos[x]^5 + 1201 (I Sin[x])^6 Cos[x]^10 + 1201 (I Sin[x])^10 Cos[x]^6 + 1640 (I Sin[x])^8 Cos[x]^8 + 420 (I Sin[x])^4 Cos[x]^12 + 420 (I Sin[x])^12 Cos[x]^4 + 170 (I Sin[x])^3 Cos[x]^13 + 170 (I Sin[x])^13 Cos[x]^3 + 44 (I Sin[x])^2 Cos[x]^14 + 44 (I Sin[x])^14 Cos[x]^2 + 7 (I Sin[x])^1 Cos[x]^15 + 7 (I Sin[x])^15 Cos[x]^1) + Exp[-1 I y] (1618 (I Sin[x])^6 Cos[x]^10 + 1618 (I Sin[x])^10 Cos[x]^6 + 302 (I Sin[x])^12 Cos[x]^4 + 302 (I Sin[x])^4 Cos[x]^12 + 2604 (I Sin[x])^8 Cos[x]^8 + 2330 (I Sin[x])^9 Cos[x]^7 + 2330 (I Sin[x])^7 Cos[x]^9 + 793 (I Sin[x])^11 Cos[x]^5 + 793 (I Sin[x])^5 Cos[x]^11 + 77 (I Sin[x])^3 Cos[x]^13 + 77 (I Sin[x])^13 Cos[x]^3 + 13 (I Sin[x])^2 Cos[x]^14 + 13 (I Sin[x])^14 Cos[x]^2) + Exp[1 I y] (2404 (I Sin[x])^8 Cos[x]^8 + 397 (I Sin[x])^4 Cos[x]^12 + 397 (I Sin[x])^12 Cos[x]^4 + 1619 (I Sin[x])^6 Cos[x]^10 + 1619 (I Sin[x])^10 Cos[x]^6 + 919 (I Sin[x])^5 Cos[x]^11 + 919 (I Sin[x])^11 Cos[x]^5 + 2174 (I Sin[x])^7 Cos[x]^9 + 2174 (I Sin[x])^9 Cos[x]^7 + 107 (I Sin[x])^3 Cos[x]^13 + 107 (I Sin[x])^13 Cos[x]^3 + 17 (I Sin[x])^2 Cos[x]^14 + 17 (I Sin[x])^14 Cos[x]^2) + Exp[3 I y] (546 (I Sin[x])^5 Cos[x]^11 + 546 (I Sin[x])^11 Cos[x]^5 + 1945 (I Sin[x])^9 Cos[x]^7 + 1945 (I Sin[x])^7 Cos[x]^9 + 2298 (I Sin[x])^8 Cos[x]^8 + 1176 (I Sin[x])^10 Cos[x]^6 + 1176 (I Sin[x])^6 Cos[x]^10 + 160 (I Sin[x])^4 Cos[x]^12 + 160 (I Sin[x])^12 Cos[x]^4 + 29 (I Sin[x])^3 Cos[x]^13 + 29 (I Sin[x])^13 Cos[x]^3) + Exp[5 I y] (1149 (I Sin[x])^7 Cos[x]^9 + 1149 (I Sin[x])^9 Cos[x]^7 + 346 (I Sin[x])^5 Cos[x]^11 + 346 (I Sin[x])^11 Cos[x]^5 + 17 (I Sin[x])^3 Cos[x]^13 + 17 (I Sin[x])^13 Cos[x]^3 + 98 (I Sin[x])^4 Cos[x]^12 + 98 (I Sin[x])^12 Cos[x]^4 + 1304 (I Sin[x])^8 Cos[x]^8 + 741 (I Sin[x])^6 Cos[x]^10 + 741 (I Sin[x])^10 Cos[x]^6) + Exp[7 I y] (26 (I Sin[x])^4 Cos[x]^12 + 26 (I Sin[x])^12 Cos[x]^4 + 664 (I Sin[x])^8 Cos[x]^8 + 335 (I Sin[x])^6 Cos[x]^10 + 335 (I Sin[x])^10 Cos[x]^6 + 556 (I Sin[x])^9 Cos[x]^7 + 556 (I Sin[x])^7 Cos[x]^9 + 116 (I Sin[x])^5 Cos[x]^11 + 116 (I Sin[x])^11 Cos[x]^5) + Exp[9 I y] (244 (I Sin[x])^8 Cos[x]^8 + 102 (I Sin[x])^6 Cos[x]^10 + 102 (I Sin[x])^10 Cos[x]^6 + 7 (I Sin[x])^4 Cos[x]^12 + 7 (I Sin[x])^12 Cos[x]^4 + 32 (I Sin[x])^5 Cos[x]^11 + 32 (I Sin[x])^11 Cos[x]^5 + 192 (I Sin[x])^9 Cos[x]^7 + 192 (I Sin[x])^7 Cos[x]^9) + Exp[11 I y] (9 (I Sin[x])^5 Cos[x]^11 + 9 (I Sin[x])^11 Cos[x]^5 + 47 (I Sin[x])^7 Cos[x]^9 + 47 (I Sin[x])^9 Cos[x]^7 + 22 (I Sin[x])^10 Cos[x]^6 + 22 (I Sin[x])^6 Cos[x]^10 + 54 (I Sin[x])^8 Cos[x]^8) + Exp[13 I y] (7 (I Sin[x])^9 Cos[x]^7 + 7 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^5 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^5 + 3 (I Sin[x])^6 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^6 + 8 (I Sin[x])^8 Cos[x]^8) + Exp[15 I y] (1 (I Sin[x])^6 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^6));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":683.9333333333,"max_line_length":4910,"alphanum_fraction":0.5057023102} {"size":7975,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 14;\nname = \"14v1 1 1 4 1 1 1 1 2 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-13 I y] (1 (I Sin[x])^8 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^8) + Exp[-11 I y] (4 (I Sin[x])^7 Cos[x]^7 + 5 (I Sin[x])^5 Cos[x]^9 + 5 (I Sin[x])^9 Cos[x]^5 + 6 (I Sin[x])^8 Cos[x]^6 + 6 (I Sin[x])^6 Cos[x]^8) + Exp[-9 I y] (25 (I Sin[x])^9 Cos[x]^5 + 25 (I Sin[x])^5 Cos[x]^9 + 34 (I Sin[x])^7 Cos[x]^7 + 9 (I Sin[x])^10 Cos[x]^4 + 9 (I Sin[x])^4 Cos[x]^10 + 27 (I Sin[x])^8 Cos[x]^6 + 27 (I Sin[x])^6 Cos[x]^8) + Exp[-7 I y] (112 (I Sin[x])^8 Cos[x]^6 + 112 (I Sin[x])^6 Cos[x]^8 + 34 (I Sin[x])^4 Cos[x]^10 + 34 (I Sin[x])^10 Cos[x]^4 + 142 (I Sin[x])^7 Cos[x]^7 + 63 (I Sin[x])^5 Cos[x]^9 + 63 (I Sin[x])^9 Cos[x]^5 + 6 (I Sin[x])^3 Cos[x]^11 + 6 (I Sin[x])^11 Cos[x]^3) + Exp[-5 I y] (302 (I Sin[x])^8 Cos[x]^6 + 302 (I Sin[x])^6 Cos[x]^8 + 63 (I Sin[x])^10 Cos[x]^4 + 63 (I Sin[x])^4 Cos[x]^10 + 18 (I Sin[x])^11 Cos[x]^3 + 18 (I Sin[x])^3 Cos[x]^11 + 346 (I Sin[x])^7 Cos[x]^7 + 159 (I Sin[x])^9 Cos[x]^5 + 159 (I Sin[x])^5 Cos[x]^9) + Exp[-3 I y] (314 (I Sin[x])^9 Cos[x]^5 + 314 (I Sin[x])^5 Cos[x]^9 + 566 (I Sin[x])^7 Cos[x]^7 + 490 (I Sin[x])^6 Cos[x]^8 + 490 (I Sin[x])^8 Cos[x]^6 + 135 (I Sin[x])^10 Cos[x]^4 + 135 (I Sin[x])^4 Cos[x]^10 + 54 (I Sin[x])^11 Cos[x]^3 + 54 (I Sin[x])^3 Cos[x]^11 + 11 (I Sin[x])^2 Cos[x]^12 + 11 (I Sin[x])^12 Cos[x]^2) + Exp[-1 I y] (828 (I Sin[x])^7 Cos[x]^7 + 410 (I Sin[x])^5 Cos[x]^9 + 410 (I Sin[x])^9 Cos[x]^5 + 44 (I Sin[x])^11 Cos[x]^3 + 44 (I Sin[x])^3 Cos[x]^11 + 11 (I Sin[x])^12 Cos[x]^2 + 11 (I Sin[x])^2 Cos[x]^12 + 668 (I Sin[x])^6 Cos[x]^8 + 668 (I Sin[x])^8 Cos[x]^6 + 169 (I Sin[x])^10 Cos[x]^4 + 169 (I Sin[x])^4 Cos[x]^10) + Exp[1 I y] (251 (I Sin[x])^10 Cos[x]^4 + 251 (I Sin[x])^4 Cos[x]^10 + 590 (I Sin[x])^6 Cos[x]^8 + 590 (I Sin[x])^8 Cos[x]^6 + 440 (I Sin[x])^5 Cos[x]^9 + 440 (I Sin[x])^9 Cos[x]^5 + 628 (I Sin[x])^7 Cos[x]^7 + 88 (I Sin[x])^3 Cos[x]^11 + 88 (I Sin[x])^11 Cos[x]^3 + 27 (I Sin[x])^2 Cos[x]^12 + 27 (I Sin[x])^12 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^13 + 6 (I Sin[x])^13 Cos[x]^1) + Exp[3 I y] (493 (I Sin[x])^6 Cos[x]^8 + 493 (I Sin[x])^8 Cos[x]^6 + 150 (I Sin[x])^4 Cos[x]^10 + 150 (I Sin[x])^10 Cos[x]^4 + 52 (I Sin[x])^11 Cos[x]^3 + 52 (I Sin[x])^3 Cos[x]^11 + 316 (I Sin[x])^5 Cos[x]^9 + 316 (I Sin[x])^9 Cos[x]^5 + 532 (I Sin[x])^7 Cos[x]^7 + 8 (I Sin[x])^2 Cos[x]^12 + 8 (I Sin[x])^12 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^1) + Exp[5 I y] (173 (I Sin[x])^9 Cos[x]^5 + 173 (I Sin[x])^5 Cos[x]^9 + 228 (I Sin[x])^7 Cos[x]^7 + 74 (I Sin[x])^3 Cos[x]^11 + 74 (I Sin[x])^11 Cos[x]^3 + 128 (I Sin[x])^4 Cos[x]^10 + 128 (I Sin[x])^10 Cos[x]^4 + 199 (I Sin[x])^6 Cos[x]^8 + 199 (I Sin[x])^8 Cos[x]^6 + 22 (I Sin[x])^2 Cos[x]^12 + 22 (I Sin[x])^12 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^1 + 1 Cos[x]^14 + 1 (I Sin[x])^14) + Exp[7 I y] (77 (I Sin[x])^5 Cos[x]^9 + 77 (I Sin[x])^9 Cos[x]^5 + 106 (I Sin[x])^7 Cos[x]^7 + 16 (I Sin[x])^3 Cos[x]^11 + 16 (I Sin[x])^11 Cos[x]^3 + 46 (I Sin[x])^10 Cos[x]^4 + 46 (I Sin[x])^4 Cos[x]^10 + 89 (I Sin[x])^8 Cos[x]^6 + 89 (I Sin[x])^6 Cos[x]^8 + 5 (I Sin[x])^2 Cos[x]^12 + 5 (I Sin[x])^12 Cos[x]^2) + Exp[9 I y] (22 (I Sin[x])^8 Cos[x]^6 + 22 (I Sin[x])^6 Cos[x]^8 + 13 (I Sin[x])^10 Cos[x]^4 + 13 (I Sin[x])^4 Cos[x]^10 + 7 (I Sin[x])^2 Cos[x]^12 + 7 (I Sin[x])^12 Cos[x]^2 + 17 (I Sin[x])^5 Cos[x]^9 + 17 (I Sin[x])^9 Cos[x]^5 + 10 (I Sin[x])^3 Cos[x]^11 + 10 (I Sin[x])^11 Cos[x]^3 + 14 (I Sin[x])^7 Cos[x]^7 + 2 (I Sin[x])^1 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^1) + Exp[11 I y] (4 (I Sin[x])^6 Cos[x]^8 + 4 (I Sin[x])^8 Cos[x]^6 + 3 (I Sin[x])^4 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^4 + 3 (I Sin[x])^9 Cos[x]^5 + 3 (I Sin[x])^5 Cos[x]^9 + 2 (I Sin[x])^7 Cos[x]^7 + 2 (I Sin[x])^3 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^3) + Exp[13 I y] (2 (I Sin[x])^7 Cos[x]^7))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-13 I y] (1 (I Sin[x])^8 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^8) + Exp[-11 I y] (4 (I Sin[x])^7 Cos[x]^7 + 5 (I Sin[x])^5 Cos[x]^9 + 5 (I Sin[x])^9 Cos[x]^5 + 6 (I Sin[x])^8 Cos[x]^6 + 6 (I Sin[x])^6 Cos[x]^8) + Exp[-9 I y] (25 (I Sin[x])^9 Cos[x]^5 + 25 (I Sin[x])^5 Cos[x]^9 + 34 (I Sin[x])^7 Cos[x]^7 + 9 (I Sin[x])^10 Cos[x]^4 + 9 (I Sin[x])^4 Cos[x]^10 + 27 (I Sin[x])^8 Cos[x]^6 + 27 (I Sin[x])^6 Cos[x]^8) + Exp[-7 I y] (112 (I Sin[x])^8 Cos[x]^6 + 112 (I Sin[x])^6 Cos[x]^8 + 34 (I Sin[x])^4 Cos[x]^10 + 34 (I Sin[x])^10 Cos[x]^4 + 142 (I Sin[x])^7 Cos[x]^7 + 63 (I Sin[x])^5 Cos[x]^9 + 63 (I Sin[x])^9 Cos[x]^5 + 6 (I Sin[x])^3 Cos[x]^11 + 6 (I Sin[x])^11 Cos[x]^3) + Exp[-5 I y] (302 (I Sin[x])^8 Cos[x]^6 + 302 (I Sin[x])^6 Cos[x]^8 + 63 (I Sin[x])^10 Cos[x]^4 + 63 (I Sin[x])^4 Cos[x]^10 + 18 (I Sin[x])^11 Cos[x]^3 + 18 (I Sin[x])^3 Cos[x]^11 + 346 (I Sin[x])^7 Cos[x]^7 + 159 (I Sin[x])^9 Cos[x]^5 + 159 (I Sin[x])^5 Cos[x]^9) + Exp[-3 I y] (314 (I Sin[x])^9 Cos[x]^5 + 314 (I Sin[x])^5 Cos[x]^9 + 566 (I Sin[x])^7 Cos[x]^7 + 490 (I Sin[x])^6 Cos[x]^8 + 490 (I Sin[x])^8 Cos[x]^6 + 135 (I Sin[x])^10 Cos[x]^4 + 135 (I Sin[x])^4 Cos[x]^10 + 54 (I Sin[x])^11 Cos[x]^3 + 54 (I Sin[x])^3 Cos[x]^11 + 11 (I Sin[x])^2 Cos[x]^12 + 11 (I Sin[x])^12 Cos[x]^2) + Exp[-1 I y] (828 (I Sin[x])^7 Cos[x]^7 + 410 (I Sin[x])^5 Cos[x]^9 + 410 (I Sin[x])^9 Cos[x]^5 + 44 (I Sin[x])^11 Cos[x]^3 + 44 (I Sin[x])^3 Cos[x]^11 + 11 (I Sin[x])^12 Cos[x]^2 + 11 (I Sin[x])^2 Cos[x]^12 + 668 (I Sin[x])^6 Cos[x]^8 + 668 (I Sin[x])^8 Cos[x]^6 + 169 (I Sin[x])^10 Cos[x]^4 + 169 (I Sin[x])^4 Cos[x]^10) + Exp[1 I y] (251 (I Sin[x])^10 Cos[x]^4 + 251 (I Sin[x])^4 Cos[x]^10 + 590 (I Sin[x])^6 Cos[x]^8 + 590 (I Sin[x])^8 Cos[x]^6 + 440 (I Sin[x])^5 Cos[x]^9 + 440 (I Sin[x])^9 Cos[x]^5 + 628 (I Sin[x])^7 Cos[x]^7 + 88 (I Sin[x])^3 Cos[x]^11 + 88 (I Sin[x])^11 Cos[x]^3 + 27 (I Sin[x])^2 Cos[x]^12 + 27 (I Sin[x])^12 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^13 + 6 (I Sin[x])^13 Cos[x]^1) + Exp[3 I y] (493 (I Sin[x])^6 Cos[x]^8 + 493 (I Sin[x])^8 Cos[x]^6 + 150 (I Sin[x])^4 Cos[x]^10 + 150 (I Sin[x])^10 Cos[x]^4 + 52 (I Sin[x])^11 Cos[x]^3 + 52 (I Sin[x])^3 Cos[x]^11 + 316 (I Sin[x])^5 Cos[x]^9 + 316 (I Sin[x])^9 Cos[x]^5 + 532 (I Sin[x])^7 Cos[x]^7 + 8 (I Sin[x])^2 Cos[x]^12 + 8 (I Sin[x])^12 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^1) + Exp[5 I y] (173 (I Sin[x])^9 Cos[x]^5 + 173 (I Sin[x])^5 Cos[x]^9 + 228 (I Sin[x])^7 Cos[x]^7 + 74 (I Sin[x])^3 Cos[x]^11 + 74 (I Sin[x])^11 Cos[x]^3 + 128 (I Sin[x])^4 Cos[x]^10 + 128 (I Sin[x])^10 Cos[x]^4 + 199 (I Sin[x])^6 Cos[x]^8 + 199 (I Sin[x])^8 Cos[x]^6 + 22 (I Sin[x])^2 Cos[x]^12 + 22 (I Sin[x])^12 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^1 + 1 Cos[x]^14 + 1 (I Sin[x])^14) + Exp[7 I y] (77 (I Sin[x])^5 Cos[x]^9 + 77 (I Sin[x])^9 Cos[x]^5 + 106 (I Sin[x])^7 Cos[x]^7 + 16 (I Sin[x])^3 Cos[x]^11 + 16 (I Sin[x])^11 Cos[x]^3 + 46 (I Sin[x])^10 Cos[x]^4 + 46 (I Sin[x])^4 Cos[x]^10 + 89 (I Sin[x])^8 Cos[x]^6 + 89 (I Sin[x])^6 Cos[x]^8 + 5 (I Sin[x])^2 Cos[x]^12 + 5 (I Sin[x])^12 Cos[x]^2) + Exp[9 I y] (22 (I Sin[x])^8 Cos[x]^6 + 22 (I Sin[x])^6 Cos[x]^8 + 13 (I Sin[x])^10 Cos[x]^4 + 13 (I Sin[x])^4 Cos[x]^10 + 7 (I Sin[x])^2 Cos[x]^12 + 7 (I Sin[x])^12 Cos[x]^2 + 17 (I Sin[x])^5 Cos[x]^9 + 17 (I Sin[x])^9 Cos[x]^5 + 10 (I Sin[x])^3 Cos[x]^11 + 10 (I Sin[x])^11 Cos[x]^3 + 14 (I Sin[x])^7 Cos[x]^7 + 2 (I Sin[x])^1 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^1) + Exp[11 I y] (4 (I Sin[x])^6 Cos[x]^8 + 4 (I Sin[x])^8 Cos[x]^6 + 3 (I Sin[x])^4 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^4 + 3 (I Sin[x])^9 Cos[x]^5 + 3 (I Sin[x])^5 Cos[x]^9 + 2 (I Sin[x])^7 Cos[x]^7 + 2 (I Sin[x])^3 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^3) + Exp[13 I y] (2 (I Sin[x])^7 Cos[x]^7));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":531.6666666667,"max_line_length":3763,"alphanum_fraction":0.4971786834} {"size":1219,"ext":"nb","lang":"Mathematica","max_stars_count":2.0,"content":"Beat 0 4\nBeat 105 0\nBeat 245 1\nBeat 350 0\nBeat 490 2\nBeat 595 0\nBeat 735 1\nBeat 875 0\nBeat 1015 3\nBeat 1120 0\nBeat 1260 1\nBeat 1365 0\nBeat 1505 2\nBeat 1610 0\nBeat 1750 1\nBeat 1855 0\nBeat 1995 4\nBeat 2100 0\nBeat 2240 1\nBeat 2345 0\nBeat 2485 2\nBeat 2625 0\nBeat 2765 1\nBeat 2870 0\nBeat 3010 3\nBeat 3115 0\nBeat 3255 1\nBeat 3360 0\nBeat 3500 2\nBeat 3605 0\nBeat 3745 1\nBeat 3850 0\nBeat 3990 4\nBeat 4095 0\nBeat 4235 1\nBeat 4340 0\nBeat 4480 2\nBeat 4620 0\nBeat 4760 1\nBeat 4865 0\nBeat 5005 3\nBeat 5110 0\nBeat 5250 1\nBeat 5355 0\nBeat 5495 2\nBeat 5600 0\nBeat 5740 1\nBeat 5845 0\nBeat 5985 4\nBeat 6090 0\nBeat 6230 1\nBeat 6370 0\nBeat 6510 2\nBeat 6615 0\nBeat 6755 1\nBeat 6860 0\nBeat 7000 3\nBeat 7105 0\nBeat 7245 1\nBeat 7350 0\nBeat 7490 2\nNote 0 490 69\nNote 490 1015 69\nNote 1015 1505 69\nNote 1505 1995 71\nNote 1995 2765 69\nNote 2765 3010 67\nNote 3010 3500 66\n|\nNote 3500 3990 71\nNote 3990 4760 69\nNote 4760 5005 67\nNote 5005 5495 66\nNote 5495 5985 69\nNote 5985 7490 66\n|\n\n","avg_line_length":15.6282051282,"max_line_length":22,"alphanum_fraction":0.587366694} {"size":7113,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"$Conjugate[x_] := x \/. Complex[a_, b_] :> a - I b;\nfunction[x_, y_] := $Conjugate[Exp[-14 I y] (1 (I Sin[x])^4 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^4) + Exp[-12 I y] (7 (I Sin[x])^3 Cos[x]^11 + 7 (I Sin[x])^11 Cos[x]^3 + 26 (I Sin[x])^5 Cos[x]^9 + 26 (I Sin[x])^9 Cos[x]^5 + 1 (I Sin[x])^2 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^2 + 12 (I Sin[x])^4 Cos[x]^10 + 12 (I Sin[x])^10 Cos[x]^4 + 29 (I Sin[x])^6 Cos[x]^8 + 29 (I Sin[x])^8 Cos[x]^6 + 32 (I Sin[x])^7 Cos[x]^7) + Exp[-10 I y] (134 (I Sin[x])^4 Cos[x]^10 + 134 (I Sin[x])^10 Cos[x]^4 + 363 (I Sin[x])^6 Cos[x]^8 + 363 (I Sin[x])^8 Cos[x]^6 + 14 (I Sin[x])^2 Cos[x]^12 + 14 (I Sin[x])^12 Cos[x]^2 + 46 (I Sin[x])^3 Cos[x]^11 + 46 (I Sin[x])^11 Cos[x]^3 + 244 (I Sin[x])^5 Cos[x]^9 + 244 (I Sin[x])^9 Cos[x]^5 + 396 (I Sin[x])^7 Cos[x]^7 + 2 (I Sin[x])^1 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^1) + Exp[-8 I y] (154 (I Sin[x])^3 Cos[x]^11 + 154 (I Sin[x])^11 Cos[x]^3 + 732 (I Sin[x])^5 Cos[x]^9 + 732 (I Sin[x])^9 Cos[x]^5 + 1250 (I Sin[x])^7 Cos[x]^7 + 376 (I Sin[x])^4 Cos[x]^10 + 376 (I Sin[x])^10 Cos[x]^4 + 1067 (I Sin[x])^6 Cos[x]^8 + 1067 (I Sin[x])^8 Cos[x]^6 + 40 (I Sin[x])^2 Cos[x]^12 + 40 (I Sin[x])^12 Cos[x]^2 + 8 (I Sin[x])^1 Cos[x]^13 + 8 (I Sin[x])^13 Cos[x]^1 + 1 Cos[x]^14 + 1 (I Sin[x])^14) + Exp[-6 I y] (361 (I Sin[x])^4 Cos[x]^10 + 361 (I Sin[x])^10 Cos[x]^4 + 1126 (I Sin[x])^6 Cos[x]^8 + 1126 (I Sin[x])^8 Cos[x]^6 + 736 (I Sin[x])^5 Cos[x]^9 + 736 (I Sin[x])^9 Cos[x]^5 + 1244 (I Sin[x])^7 Cos[x]^7 + 32 (I Sin[x])^2 Cos[x]^12 + 32 (I Sin[x])^12 Cos[x]^2 + 122 (I Sin[x])^3 Cos[x]^11 + 122 (I Sin[x])^11 Cos[x]^3 + 4 (I Sin[x])^1 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^1) + Exp[-4 I y] (242 (I Sin[x])^5 Cos[x]^9 + 242 (I Sin[x])^9 Cos[x]^5 + 468 (I Sin[x])^7 Cos[x]^7 + 35 (I Sin[x])^3 Cos[x]^11 + 35 (I Sin[x])^11 Cos[x]^3 + 111 (I Sin[x])^4 Cos[x]^10 + 111 (I Sin[x])^10 Cos[x]^4 + 375 (I Sin[x])^6 Cos[x]^8 + 375 (I Sin[x])^8 Cos[x]^6 + 4 (I Sin[x])^2 Cos[x]^12 + 4 (I Sin[x])^12 Cos[x]^2) + Exp[-2 I y] (43 (I Sin[x])^6 Cos[x]^8 + 43 (I Sin[x])^8 Cos[x]^6 + 6 (I Sin[x])^4 Cos[x]^10 + 6 (I Sin[x])^10 Cos[x]^4 + 22 (I Sin[x])^5 Cos[x]^9 + 22 (I Sin[x])^9 Cos[x]^5 + 40 (I Sin[x])^7 Cos[x]^7) + Exp[0 I y] (2 (I Sin[x])^7 Cos[x]^7)]*\n(Exp[-14 I y] (1 (I Sin[x])^4 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^4) + Exp[-12 I y] (7 (I Sin[x])^3 Cos[x]^11 + 7 (I Sin[x])^11 Cos[x]^3 + 26 (I Sin[x])^5 Cos[x]^9 + 26 (I Sin[x])^9 Cos[x]^5 + 1 (I Sin[x])^2 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^2 + 12 (I Sin[x])^4 Cos[x]^10 + 12 (I Sin[x])^10 Cos[x]^4 + 29 (I Sin[x])^6 Cos[x]^8 + 29 (I Sin[x])^8 Cos[x]^6 + 32 (I Sin[x])^7 Cos[x]^7) + Exp[-10 I y] (134 (I Sin[x])^4 Cos[x]^10 + 134 (I Sin[x])^10 Cos[x]^4 + 363 (I Sin[x])^6 Cos[x]^8 + 363 (I Sin[x])^8 Cos[x]^6 + 14 (I Sin[x])^2 Cos[x]^12 + 14 (I Sin[x])^12 Cos[x]^2 + 46 (I Sin[x])^3 Cos[x]^11 + 46 (I Sin[x])^11 Cos[x]^3 + 244 (I Sin[x])^5 Cos[x]^9 + 244 (I Sin[x])^9 Cos[x]^5 + 396 (I Sin[x])^7 Cos[x]^7 + 2 (I Sin[x])^1 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^1) + Exp[-8 I y] (154 (I Sin[x])^3 Cos[x]^11 + 154 (I Sin[x])^11 Cos[x]^3 + 732 (I Sin[x])^5 Cos[x]^9 + 732 (I Sin[x])^9 Cos[x]^5 + 1250 (I Sin[x])^7 Cos[x]^7 + 376 (I Sin[x])^4 Cos[x]^10 + 376 (I Sin[x])^10 Cos[x]^4 + 1067 (I Sin[x])^6 Cos[x]^8 + 1067 (I Sin[x])^8 Cos[x]^6 + 40 (I Sin[x])^2 Cos[x]^12 + 40 (I Sin[x])^12 Cos[x]^2 + 8 (I Sin[x])^1 Cos[x]^13 + 8 (I Sin[x])^13 Cos[x]^1 + 1 Cos[x]^14 + 1 (I Sin[x])^14) + Exp[-6 I y] (361 (I Sin[x])^4 Cos[x]^10 + 361 (I Sin[x])^10 Cos[x]^4 + 1126 (I Sin[x])^6 Cos[x]^8 + 1126 (I Sin[x])^8 Cos[x]^6 + 736 (I Sin[x])^5 Cos[x]^9 + 736 (I Sin[x])^9 Cos[x]^5 + 1244 (I Sin[x])^7 Cos[x]^7 + 32 (I Sin[x])^2 Cos[x]^12 + 32 (I Sin[x])^12 Cos[x]^2 + 122 (I Sin[x])^3 Cos[x]^11 + 122 (I Sin[x])^11 Cos[x]^3 + 4 (I Sin[x])^1 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^1) + Exp[-4 I y] (242 (I Sin[x])^5 Cos[x]^9 + 242 (I Sin[x])^9 Cos[x]^5 + 468 (I Sin[x])^7 Cos[x]^7 + 35 (I Sin[x])^3 Cos[x]^11 + 35 (I Sin[x])^11 Cos[x]^3 + 111 (I Sin[x])^4 Cos[x]^10 + 111 (I Sin[x])^10 Cos[x]^4 + 375 (I Sin[x])^6 Cos[x]^8 + 375 (I Sin[x])^8 Cos[x]^6 + 4 (I Sin[x])^2 Cos[x]^12 + 4 (I Sin[x])^12 Cos[x]^2) + Exp[-2 I y] (43 (I Sin[x])^6 Cos[x]^8 + 43 (I Sin[x])^8 Cos[x]^6 + 6 (I Sin[x])^4 Cos[x]^10 + 6 (I Sin[x])^10 Cos[x]^4 + 22 (I Sin[x])^5 Cos[x]^9 + 22 (I Sin[x])^9 Cos[x]^5 + 40 (I Sin[x])^7 Cos[x]^7) + Exp[0 I y] (2 (I Sin[x])^7 Cos[x]^7))\n\namplitude[x_,y_] := Exp[-14 I y] (1 (I Sin[x])^4 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^4) + Exp[-12 I y] (7 (I Sin[x])^3 Cos[x]^11 + 7 (I Sin[x])^11 Cos[x]^3 + 26 (I Sin[x])^5 Cos[x]^9 + 26 (I Sin[x])^9 Cos[x]^5 + 1 (I Sin[x])^2 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^2 + 12 (I Sin[x])^4 Cos[x]^10 + 12 (I Sin[x])^10 Cos[x]^4 + 29 (I Sin[x])^6 Cos[x]^8 + 29 (I Sin[x])^8 Cos[x]^6 + 32 (I Sin[x])^7 Cos[x]^7) + Exp[-10 I y] (134 (I Sin[x])^4 Cos[x]^10 + 134 (I Sin[x])^10 Cos[x]^4 + 363 (I Sin[x])^6 Cos[x]^8 + 363 (I Sin[x])^8 Cos[x]^6 + 14 (I Sin[x])^2 Cos[x]^12 + 14 (I Sin[x])^12 Cos[x]^2 + 46 (I Sin[x])^3 Cos[x]^11 + 46 (I Sin[x])^11 Cos[x]^3 + 244 (I Sin[x])^5 Cos[x]^9 + 244 (I Sin[x])^9 Cos[x]^5 + 396 (I Sin[x])^7 Cos[x]^7 + 2 (I Sin[x])^1 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^1) + Exp[-8 I y] (154 (I Sin[x])^3 Cos[x]^11 + 154 (I Sin[x])^11 Cos[x]^3 + 732 (I Sin[x])^5 Cos[x]^9 + 732 (I Sin[x])^9 Cos[x]^5 + 1250 (I Sin[x])^7 Cos[x]^7 + 376 (I Sin[x])^4 Cos[x]^10 + 376 (I Sin[x])^10 Cos[x]^4 + 1067 (I Sin[x])^6 Cos[x]^8 + 1067 (I Sin[x])^8 Cos[x]^6 + 40 (I Sin[x])^2 Cos[x]^12 + 40 (I Sin[x])^12 Cos[x]^2 + 8 (I Sin[x])^1 Cos[x]^13 + 8 (I Sin[x])^13 Cos[x]^1 + 1 Cos[x]^14 + 1 (I Sin[x])^14) + Exp[-6 I y] (361 (I Sin[x])^4 Cos[x]^10 + 361 (I Sin[x])^10 Cos[x]^4 + 1126 (I Sin[x])^6 Cos[x]^8 + 1126 (I Sin[x])^8 Cos[x]^6 + 736 (I Sin[x])^5 Cos[x]^9 + 736 (I Sin[x])^9 Cos[x]^5 + 1244 (I Sin[x])^7 Cos[x]^7 + 32 (I Sin[x])^2 Cos[x]^12 + 32 (I Sin[x])^12 Cos[x]^2 + 122 (I Sin[x])^3 Cos[x]^11 + 122 (I Sin[x])^11 Cos[x]^3 + 4 (I Sin[x])^1 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^1) + Exp[-4 I y] (242 (I Sin[x])^5 Cos[x]^9 + 242 (I Sin[x])^9 Cos[x]^5 + 468 (I Sin[x])^7 Cos[x]^7 + 35 (I Sin[x])^3 Cos[x]^11 + 35 (I Sin[x])^11 Cos[x]^3 + 111 (I Sin[x])^4 Cos[x]^10 + 111 (I Sin[x])^10 Cos[x]^4 + 375 (I Sin[x])^6 Cos[x]^8 + 375 (I Sin[x])^8 Cos[x]^6 + 4 (I Sin[x])^2 Cos[x]^12 + 4 (I Sin[x])^12 Cos[x]^2) + Exp[-2 I y] (43 (I Sin[x])^6 Cos[x]^8 + 43 (I Sin[x])^8 Cos[x]^6 + 6 (I Sin[x])^4 Cos[x]^10 + 6 (I Sin[x])^10 Cos[x]^4 + 22 (I Sin[x])^5 Cos[x]^9 + 22 (I Sin[x])^9 Cos[x]^5 + 40 (I Sin[x])^7 Cos[x]^7) + Exp[0 I y] (2 (I Sin[x])^7 Cos[x]^7)\n\nammount = 14;\nname = \"14v4 1 4 1 2 2\";\nstates = 56;\n\n\nk = 0.1;\n\n\nmax = function[0, 0];\nx = 0;\ny = 0;\n\n\nFor[\u03b2 = 0 , \u03b2 <= Pi\/2, \u03b2 = \u03b2 + k,\n \tFor[\u03b3 = 0 , \u03b3 <= Pi\/2 - \u03b2, \u03b3 = \u03b3 + k,\n \t\n \t\tmax2 = function[\u03b2, \u03b3];\n \t\tIf[max2 > max, {x = \u03b2, y = \u03b3}];\n \t\tmax = Max[max, max2];\n \t]\n ]\n\nresult = NMaximize[{Re[states*function[a, b]\/(2^ammount)], x - k < a < x + k, y - k < b < y + k}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 3}];\n\nPrint[name, \": \", result]\n\nf = function[c, d]; n = Pi;\nPlot3D[f,{c,0,n},{d,0,n}, PlotRange -> All]\n\nContourPlot[function[x, y], {x, 0, n}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":192.2432432432,"max_line_length":2154,"alphanum_fraction":0.4964150148} {"size":10979,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 16;\nname = \"16v4 1 2 3 1 1 2 1 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^6 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^6) + Exp[-13 I y] (7 (I Sin[x])^7 Cos[x]^9 + 7 (I Sin[x])^9 Cos[x]^7 + 4 (I Sin[x])^6 Cos[x]^10 + 4 (I Sin[x])^10 Cos[x]^6 + 6 (I Sin[x])^8 Cos[x]^8 + 1 (I Sin[x])^5 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^5) + Exp[-11 I y] (23 (I Sin[x])^5 Cos[x]^11 + 23 (I Sin[x])^11 Cos[x]^5 + 31 (I Sin[x])^7 Cos[x]^9 + 31 (I Sin[x])^9 Cos[x]^7 + 25 (I Sin[x])^6 Cos[x]^10 + 25 (I Sin[x])^10 Cos[x]^6 + 28 (I Sin[x])^8 Cos[x]^8 + 10 (I Sin[x])^4 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3) + Exp[-9 I y] (204 (I Sin[x])^8 Cos[x]^8 + 166 (I Sin[x])^7 Cos[x]^9 + 166 (I Sin[x])^9 Cos[x]^7 + 112 (I Sin[x])^6 Cos[x]^10 + 112 (I Sin[x])^10 Cos[x]^6 + 56 (I Sin[x])^5 Cos[x]^11 + 56 (I Sin[x])^11 Cos[x]^5 + 17 (I Sin[x])^4 Cos[x]^12 + 17 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3) + Exp[-7 I y] (348 (I Sin[x])^6 Cos[x]^10 + 348 (I Sin[x])^10 Cos[x]^6 + 500 (I Sin[x])^8 Cos[x]^8 + 90 (I Sin[x])^4 Cos[x]^12 + 90 (I Sin[x])^12 Cos[x]^4 + 195 (I Sin[x])^5 Cos[x]^11 + 195 (I Sin[x])^11 Cos[x]^5 + 448 (I Sin[x])^7 Cos[x]^9 + 448 (I Sin[x])^9 Cos[x]^7 + 29 (I Sin[x])^3 Cos[x]^13 + 29 (I Sin[x])^13 Cos[x]^3 + 5 (I Sin[x])^2 Cos[x]^14 + 5 (I Sin[x])^14 Cos[x]^2) + Exp[-5 I y] (1137 (I Sin[x])^7 Cos[x]^9 + 1137 (I Sin[x])^9 Cos[x]^7 + 1264 (I Sin[x])^8 Cos[x]^8 + 737 (I Sin[x])^6 Cos[x]^10 + 737 (I Sin[x])^10 Cos[x]^6 + 347 (I Sin[x])^5 Cos[x]^11 + 347 (I Sin[x])^11 Cos[x]^5 + 119 (I Sin[x])^4 Cos[x]^12 + 119 (I Sin[x])^12 Cos[x]^4 + 28 (I Sin[x])^3 Cos[x]^13 + 28 (I Sin[x])^13 Cos[x]^3 + 3 (I Sin[x])^2 Cos[x]^14 + 3 (I Sin[x])^14 Cos[x]^2) + Exp[-3 I y] (1703 (I Sin[x])^7 Cos[x]^9 + 1703 (I Sin[x])^9 Cos[x]^7 + 708 (I Sin[x])^5 Cos[x]^11 + 708 (I Sin[x])^11 Cos[x]^5 + 105 (I Sin[x])^3 Cos[x]^13 + 105 (I Sin[x])^13 Cos[x]^3 + 312 (I Sin[x])^4 Cos[x]^12 + 312 (I Sin[x])^12 Cos[x]^4 + 1880 (I Sin[x])^8 Cos[x]^8 + 1207 (I Sin[x])^6 Cos[x]^10 + 1207 (I Sin[x])^10 Cos[x]^6 + 26 (I Sin[x])^2 Cos[x]^14 + 26 (I Sin[x])^14 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[-1 I y] (1556 (I Sin[x])^6 Cos[x]^10 + 1556 (I Sin[x])^10 Cos[x]^6 + 2770 (I Sin[x])^8 Cos[x]^8 + 2349 (I Sin[x])^7 Cos[x]^9 + 2349 (I Sin[x])^9 Cos[x]^7 + 780 (I Sin[x])^5 Cos[x]^11 + 780 (I Sin[x])^11 Cos[x]^5 + 282 (I Sin[x])^4 Cos[x]^12 + 282 (I Sin[x])^12 Cos[x]^4 + 70 (I Sin[x])^3 Cos[x]^13 + 70 (I Sin[x])^13 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[1 I y] (1572 (I Sin[x])^6 Cos[x]^10 + 1572 (I Sin[x])^10 Cos[x]^6 + 2394 (I Sin[x])^8 Cos[x]^8 + 426 (I Sin[x])^4 Cos[x]^12 + 426 (I Sin[x])^12 Cos[x]^4 + 39 (I Sin[x])^2 Cos[x]^14 + 39 (I Sin[x])^14 Cos[x]^2 + 152 (I Sin[x])^3 Cos[x]^13 + 152 (I Sin[x])^13 Cos[x]^3 + 2135 (I Sin[x])^7 Cos[x]^9 + 2135 (I Sin[x])^9 Cos[x]^7 + 906 (I Sin[x])^5 Cos[x]^11 + 906 (I Sin[x])^11 Cos[x]^5 + 7 (I Sin[x])^1 Cos[x]^15 + 7 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[3 I y] (627 (I Sin[x])^5 Cos[x]^11 + 627 (I Sin[x])^11 Cos[x]^5 + 1826 (I Sin[x])^9 Cos[x]^7 + 1826 (I Sin[x])^7 Cos[x]^9 + 2002 (I Sin[x])^8 Cos[x]^8 + 1233 (I Sin[x])^10 Cos[x]^6 + 1233 (I Sin[x])^6 Cos[x]^10 + 240 (I Sin[x])^4 Cos[x]^12 + 240 (I Sin[x])^12 Cos[x]^4 + 66 (I Sin[x])^3 Cos[x]^13 + 66 (I Sin[x])^13 Cos[x]^3 + 11 (I Sin[x])^2 Cos[x]^14 + 11 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^15 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^15) + Exp[5 I y] (968 (I Sin[x])^7 Cos[x]^9 + 968 (I Sin[x])^9 Cos[x]^7 + 463 (I Sin[x])^5 Cos[x]^11 + 463 (I Sin[x])^11 Cos[x]^5 + 78 (I Sin[x])^3 Cos[x]^13 + 78 (I Sin[x])^13 Cos[x]^3 + 218 (I Sin[x])^4 Cos[x]^12 + 218 (I Sin[x])^12 Cos[x]^4 + 1036 (I Sin[x])^8 Cos[x]^8 + 735 (I Sin[x])^6 Cos[x]^10 + 735 (I Sin[x])^10 Cos[x]^6 + 3 (I Sin[x])^1 Cos[x]^15 + 3 (I Sin[x])^15 Cos[x]^1 + 20 (I Sin[x])^2 Cos[x]^14 + 20 (I Sin[x])^14 Cos[x]^2) + Exp[7 I y] (334 (I Sin[x])^6 Cos[x]^10 + 334 (I Sin[x])^10 Cos[x]^6 + 584 (I Sin[x])^8 Cos[x]^8 + 65 (I Sin[x])^4 Cos[x]^12 + 65 (I Sin[x])^12 Cos[x]^4 + 480 (I Sin[x])^7 Cos[x]^9 + 480 (I Sin[x])^9 Cos[x]^7 + 177 (I Sin[x])^11 Cos[x]^5 + 177 (I Sin[x])^5 Cos[x]^11 + 15 (I Sin[x])^3 Cos[x]^13 + 15 (I Sin[x])^13 Cos[x]^3 + 2 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^14) + Exp[9 I y] (113 (I Sin[x])^6 Cos[x]^10 + 113 (I Sin[x])^10 Cos[x]^6 + 160 (I Sin[x])^8 Cos[x]^8 + 36 (I Sin[x])^4 Cos[x]^12 + 36 (I Sin[x])^12 Cos[x]^4 + 70 (I Sin[x])^5 Cos[x]^11 + 70 (I Sin[x])^11 Cos[x]^5 + 142 (I Sin[x])^9 Cos[x]^7 + 142 (I Sin[x])^7 Cos[x]^9 + 2 (I Sin[x])^2 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^2 + 12 (I Sin[x])^3 Cos[x]^13 + 12 (I Sin[x])^13 Cos[x]^3) + Exp[11 I y] (41 (I Sin[x])^7 Cos[x]^9 + 41 (I Sin[x])^9 Cos[x]^7 + 14 (I Sin[x])^5 Cos[x]^11 + 14 (I Sin[x])^11 Cos[x]^5 + 32 (I Sin[x])^8 Cos[x]^8 + 28 (I Sin[x])^10 Cos[x]^6 + 28 (I Sin[x])^6 Cos[x]^10 + 1 (I Sin[x])^13 Cos[x]^3 + 1 (I Sin[x])^3 Cos[x]^13 + 5 (I Sin[x])^12 Cos[x]^4 + 5 (I Sin[x])^4 Cos[x]^12) + Exp[13 I y] (7 (I Sin[x])^7 Cos[x]^9 + 7 (I Sin[x])^9 Cos[x]^7 + 1 (I Sin[x])^5 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^5 + 3 (I Sin[x])^6 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^6 + 8 (I Sin[x])^8 Cos[x]^8) + Exp[15 I y] (2 (I Sin[x])^8 Cos[x]^8))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^6 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^6) + Exp[-13 I y] (7 (I Sin[x])^7 Cos[x]^9 + 7 (I Sin[x])^9 Cos[x]^7 + 4 (I Sin[x])^6 Cos[x]^10 + 4 (I Sin[x])^10 Cos[x]^6 + 6 (I Sin[x])^8 Cos[x]^8 + 1 (I Sin[x])^5 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^5) + Exp[-11 I y] (23 (I Sin[x])^5 Cos[x]^11 + 23 (I Sin[x])^11 Cos[x]^5 + 31 (I Sin[x])^7 Cos[x]^9 + 31 (I Sin[x])^9 Cos[x]^7 + 25 (I Sin[x])^6 Cos[x]^10 + 25 (I Sin[x])^10 Cos[x]^6 + 28 (I Sin[x])^8 Cos[x]^8 + 10 (I Sin[x])^4 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3) + Exp[-9 I y] (204 (I Sin[x])^8 Cos[x]^8 + 166 (I Sin[x])^7 Cos[x]^9 + 166 (I Sin[x])^9 Cos[x]^7 + 112 (I Sin[x])^6 Cos[x]^10 + 112 (I Sin[x])^10 Cos[x]^6 + 56 (I Sin[x])^5 Cos[x]^11 + 56 (I Sin[x])^11 Cos[x]^5 + 17 (I Sin[x])^4 Cos[x]^12 + 17 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3) + Exp[-7 I y] (348 (I Sin[x])^6 Cos[x]^10 + 348 (I Sin[x])^10 Cos[x]^6 + 500 (I Sin[x])^8 Cos[x]^8 + 90 (I Sin[x])^4 Cos[x]^12 + 90 (I Sin[x])^12 Cos[x]^4 + 195 (I Sin[x])^5 Cos[x]^11 + 195 (I Sin[x])^11 Cos[x]^5 + 448 (I Sin[x])^7 Cos[x]^9 + 448 (I Sin[x])^9 Cos[x]^7 + 29 (I Sin[x])^3 Cos[x]^13 + 29 (I Sin[x])^13 Cos[x]^3 + 5 (I Sin[x])^2 Cos[x]^14 + 5 (I Sin[x])^14 Cos[x]^2) + Exp[-5 I y] (1137 (I Sin[x])^7 Cos[x]^9 + 1137 (I Sin[x])^9 Cos[x]^7 + 1264 (I Sin[x])^8 Cos[x]^8 + 737 (I Sin[x])^6 Cos[x]^10 + 737 (I Sin[x])^10 Cos[x]^6 + 347 (I Sin[x])^5 Cos[x]^11 + 347 (I Sin[x])^11 Cos[x]^5 + 119 (I Sin[x])^4 Cos[x]^12 + 119 (I Sin[x])^12 Cos[x]^4 + 28 (I Sin[x])^3 Cos[x]^13 + 28 (I Sin[x])^13 Cos[x]^3 + 3 (I Sin[x])^2 Cos[x]^14 + 3 (I Sin[x])^14 Cos[x]^2) + Exp[-3 I y] (1703 (I Sin[x])^7 Cos[x]^9 + 1703 (I Sin[x])^9 Cos[x]^7 + 708 (I Sin[x])^5 Cos[x]^11 + 708 (I Sin[x])^11 Cos[x]^5 + 105 (I Sin[x])^3 Cos[x]^13 + 105 (I Sin[x])^13 Cos[x]^3 + 312 (I Sin[x])^4 Cos[x]^12 + 312 (I Sin[x])^12 Cos[x]^4 + 1880 (I Sin[x])^8 Cos[x]^8 + 1207 (I Sin[x])^6 Cos[x]^10 + 1207 (I Sin[x])^10 Cos[x]^6 + 26 (I Sin[x])^2 Cos[x]^14 + 26 (I Sin[x])^14 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[-1 I y] (1556 (I Sin[x])^6 Cos[x]^10 + 1556 (I Sin[x])^10 Cos[x]^6 + 2770 (I Sin[x])^8 Cos[x]^8 + 2349 (I Sin[x])^7 Cos[x]^9 + 2349 (I Sin[x])^9 Cos[x]^7 + 780 (I Sin[x])^5 Cos[x]^11 + 780 (I Sin[x])^11 Cos[x]^5 + 282 (I Sin[x])^4 Cos[x]^12 + 282 (I Sin[x])^12 Cos[x]^4 + 70 (I Sin[x])^3 Cos[x]^13 + 70 (I Sin[x])^13 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[1 I y] (1572 (I Sin[x])^6 Cos[x]^10 + 1572 (I Sin[x])^10 Cos[x]^6 + 2394 (I Sin[x])^8 Cos[x]^8 + 426 (I Sin[x])^4 Cos[x]^12 + 426 (I Sin[x])^12 Cos[x]^4 + 39 (I Sin[x])^2 Cos[x]^14 + 39 (I Sin[x])^14 Cos[x]^2 + 152 (I Sin[x])^3 Cos[x]^13 + 152 (I Sin[x])^13 Cos[x]^3 + 2135 (I Sin[x])^7 Cos[x]^9 + 2135 (I Sin[x])^9 Cos[x]^7 + 906 (I Sin[x])^5 Cos[x]^11 + 906 (I Sin[x])^11 Cos[x]^5 + 7 (I Sin[x])^1 Cos[x]^15 + 7 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[3 I y] (627 (I Sin[x])^5 Cos[x]^11 + 627 (I Sin[x])^11 Cos[x]^5 + 1826 (I Sin[x])^9 Cos[x]^7 + 1826 (I Sin[x])^7 Cos[x]^9 + 2002 (I Sin[x])^8 Cos[x]^8 + 1233 (I Sin[x])^10 Cos[x]^6 + 1233 (I Sin[x])^6 Cos[x]^10 + 240 (I Sin[x])^4 Cos[x]^12 + 240 (I Sin[x])^12 Cos[x]^4 + 66 (I Sin[x])^3 Cos[x]^13 + 66 (I Sin[x])^13 Cos[x]^3 + 11 (I Sin[x])^2 Cos[x]^14 + 11 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^15 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^15) + Exp[5 I y] (968 (I Sin[x])^7 Cos[x]^9 + 968 (I Sin[x])^9 Cos[x]^7 + 463 (I Sin[x])^5 Cos[x]^11 + 463 (I Sin[x])^11 Cos[x]^5 + 78 (I Sin[x])^3 Cos[x]^13 + 78 (I Sin[x])^13 Cos[x]^3 + 218 (I Sin[x])^4 Cos[x]^12 + 218 (I Sin[x])^12 Cos[x]^4 + 1036 (I Sin[x])^8 Cos[x]^8 + 735 (I Sin[x])^6 Cos[x]^10 + 735 (I Sin[x])^10 Cos[x]^6 + 3 (I Sin[x])^1 Cos[x]^15 + 3 (I Sin[x])^15 Cos[x]^1 + 20 (I Sin[x])^2 Cos[x]^14 + 20 (I Sin[x])^14 Cos[x]^2) + Exp[7 I y] (334 (I Sin[x])^6 Cos[x]^10 + 334 (I Sin[x])^10 Cos[x]^6 + 584 (I Sin[x])^8 Cos[x]^8 + 65 (I Sin[x])^4 Cos[x]^12 + 65 (I Sin[x])^12 Cos[x]^4 + 480 (I Sin[x])^7 Cos[x]^9 + 480 (I Sin[x])^9 Cos[x]^7 + 177 (I Sin[x])^11 Cos[x]^5 + 177 (I Sin[x])^5 Cos[x]^11 + 15 (I Sin[x])^3 Cos[x]^13 + 15 (I Sin[x])^13 Cos[x]^3 + 2 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^14) + Exp[9 I y] (113 (I Sin[x])^6 Cos[x]^10 + 113 (I Sin[x])^10 Cos[x]^6 + 160 (I Sin[x])^8 Cos[x]^8 + 36 (I Sin[x])^4 Cos[x]^12 + 36 (I Sin[x])^12 Cos[x]^4 + 70 (I Sin[x])^5 Cos[x]^11 + 70 (I Sin[x])^11 Cos[x]^5 + 142 (I Sin[x])^9 Cos[x]^7 + 142 (I Sin[x])^7 Cos[x]^9 + 2 (I Sin[x])^2 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^2 + 12 (I Sin[x])^3 Cos[x]^13 + 12 (I Sin[x])^13 Cos[x]^3) + Exp[11 I y] (41 (I Sin[x])^7 Cos[x]^9 + 41 (I Sin[x])^9 Cos[x]^7 + 14 (I Sin[x])^5 Cos[x]^11 + 14 (I Sin[x])^11 Cos[x]^5 + 32 (I Sin[x])^8 Cos[x]^8 + 28 (I Sin[x])^10 Cos[x]^6 + 28 (I Sin[x])^6 Cos[x]^10 + 1 (I Sin[x])^13 Cos[x]^3 + 1 (I Sin[x])^3 Cos[x]^13 + 5 (I Sin[x])^12 Cos[x]^4 + 5 (I Sin[x])^4 Cos[x]^12) + Exp[13 I y] (7 (I Sin[x])^7 Cos[x]^9 + 7 (I Sin[x])^9 Cos[x]^7 + 1 (I Sin[x])^5 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^5 + 3 (I Sin[x])^6 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^6 + 8 (I Sin[x])^8 Cos[x]^8) + Exp[15 I y] (2 (I Sin[x])^8 Cos[x]^8));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":731.9333333333,"max_line_length":5266,"alphanum_fraction":0.5045996903} {"size":10473,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 16;\nname = \"16v3 1 2 1 1 1 1 2 2 2\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^7) + Exp[-13 I y] (7 (I Sin[x])^6 Cos[x]^10 + 7 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^8 Cos[x]^8 + 4 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^5 + 3 (I Sin[x])^7 Cos[x]^9 + 3 (I Sin[x])^9 Cos[x]^7) + Exp[-11 I y] (23 (I Sin[x])^6 Cos[x]^10 + 23 (I Sin[x])^10 Cos[x]^6 + 66 (I Sin[x])^8 Cos[x]^8 + 46 (I Sin[x])^7 Cos[x]^9 + 46 (I Sin[x])^9 Cos[x]^7 + 3 (I Sin[x])^5 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^5) + Exp[-9 I y] (158 (I Sin[x])^7 Cos[x]^9 + 158 (I Sin[x])^9 Cos[x]^7 + 120 (I Sin[x])^6 Cos[x]^10 + 120 (I Sin[x])^10 Cos[x]^6 + 152 (I Sin[x])^8 Cos[x]^8 + 70 (I Sin[x])^5 Cos[x]^11 + 70 (I Sin[x])^11 Cos[x]^5 + 28 (I Sin[x])^4 Cos[x]^12 + 28 (I Sin[x])^12 Cos[x]^4 + 3 (I Sin[x])^3 Cos[x]^13 + 3 (I Sin[x])^13 Cos[x]^3) + Exp[-7 I y] (594 (I Sin[x])^7 Cos[x]^9 + 594 (I Sin[x])^9 Cos[x]^7 + 99 (I Sin[x])^5 Cos[x]^11 + 99 (I Sin[x])^11 Cos[x]^5 + 296 (I Sin[x])^6 Cos[x]^10 + 296 (I Sin[x])^10 Cos[x]^6 + 726 (I Sin[x])^8 Cos[x]^8 + 13 (I Sin[x])^4 Cos[x]^12 + 13 (I Sin[x])^12 Cos[x]^4) + Exp[-5 I y] (752 (I Sin[x])^6 Cos[x]^10 + 752 (I Sin[x])^10 Cos[x]^6 + 1118 (I Sin[x])^8 Cos[x]^8 + 452 (I Sin[x])^5 Cos[x]^11 + 452 (I Sin[x])^11 Cos[x]^5 + 980 (I Sin[x])^7 Cos[x]^9 + 980 (I Sin[x])^9 Cos[x]^7 + 194 (I Sin[x])^4 Cos[x]^12 + 194 (I Sin[x])^12 Cos[x]^4 + 59 (I Sin[x])^3 Cos[x]^13 + 59 (I Sin[x])^13 Cos[x]^3 + 7 (I Sin[x])^2 Cos[x]^14 + 7 (I Sin[x])^14 Cos[x]^2) + Exp[-3 I y] (1263 (I Sin[x])^6 Cos[x]^10 + 1263 (I Sin[x])^10 Cos[x]^6 + 2208 (I Sin[x])^8 Cos[x]^8 + 1923 (I Sin[x])^7 Cos[x]^9 + 1923 (I Sin[x])^9 Cos[x]^7 + 153 (I Sin[x])^4 Cos[x]^12 + 153 (I Sin[x])^12 Cos[x]^4 + 543 (I Sin[x])^5 Cos[x]^11 + 543 (I Sin[x])^11 Cos[x]^5 + 19 (I Sin[x])^3 Cos[x]^13 + 19 (I Sin[x])^13 Cos[x]^3) + Exp[-1 I y] (2162 (I Sin[x])^7 Cos[x]^9 + 2162 (I Sin[x])^9 Cos[x]^7 + 910 (I Sin[x])^5 Cos[x]^11 + 910 (I Sin[x])^11 Cos[x]^5 + 440 (I Sin[x])^4 Cos[x]^12 + 440 (I Sin[x])^12 Cos[x]^4 + 1550 (I Sin[x])^6 Cos[x]^10 + 1550 (I Sin[x])^10 Cos[x]^6 + 2336 (I Sin[x])^8 Cos[x]^8 + 158 (I Sin[x])^3 Cos[x]^13 + 158 (I Sin[x])^13 Cos[x]^3 + 42 (I Sin[x])^2 Cos[x]^14 + 42 (I Sin[x])^14 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^15 + 5 (I Sin[x])^15 Cos[x]^1) + Exp[1 I y] (885 (I Sin[x])^5 Cos[x]^11 + 885 (I Sin[x])^11 Cos[x]^5 + 2259 (I Sin[x])^9 Cos[x]^7 + 2259 (I Sin[x])^7 Cos[x]^9 + 2552 (I Sin[x])^8 Cos[x]^8 + 1565 (I Sin[x])^6 Cos[x]^10 + 1565 (I Sin[x])^10 Cos[x]^6 + 91 (I Sin[x])^3 Cos[x]^13 + 91 (I Sin[x])^13 Cos[x]^3 + 348 (I Sin[x])^4 Cos[x]^12 + 348 (I Sin[x])^12 Cos[x]^4 + 11 (I Sin[x])^2 Cos[x]^14 + 11 (I Sin[x])^14 Cos[x]^2) + Exp[3 I y] (1888 (I Sin[x])^8 Cos[x]^8 + 1220 (I Sin[x])^6 Cos[x]^10 + 1220 (I Sin[x])^10 Cos[x]^6 + 322 (I Sin[x])^4 Cos[x]^12 + 322 (I Sin[x])^12 Cos[x]^4 + 119 (I Sin[x])^3 Cos[x]^13 + 119 (I Sin[x])^13 Cos[x]^3 + 713 (I Sin[x])^5 Cos[x]^11 + 713 (I Sin[x])^11 Cos[x]^5 + 1645 (I Sin[x])^7 Cos[x]^9 + 1645 (I Sin[x])^9 Cos[x]^7 + 33 (I Sin[x])^2 Cos[x]^14 + 33 (I Sin[x])^14 Cos[x]^2 + 8 (I Sin[x])^1 Cos[x]^15 + 8 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[5 I y] (182 (I Sin[x])^4 Cos[x]^12 + 182 (I Sin[x])^12 Cos[x]^4 + 741 (I Sin[x])^10 Cos[x]^6 + 741 (I Sin[x])^6 Cos[x]^10 + 1146 (I Sin[x])^8 Cos[x]^8 + 1032 (I Sin[x])^9 Cos[x]^7 + 1032 (I Sin[x])^7 Cos[x]^9 + 394 (I Sin[x])^5 Cos[x]^11 + 394 (I Sin[x])^11 Cos[x]^5 + 63 (I Sin[x])^3 Cos[x]^13 + 63 (I Sin[x])^13 Cos[x]^3 + 16 (I Sin[x])^2 Cos[x]^14 + 16 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[7 I y] (457 (I Sin[x])^9 Cos[x]^7 + 457 (I Sin[x])^7 Cos[x]^9 + 198 (I Sin[x])^5 Cos[x]^11 + 198 (I Sin[x])^11 Cos[x]^5 + 100 (I Sin[x])^4 Cos[x]^12 + 100 (I Sin[x])^12 Cos[x]^4 + 326 (I Sin[x])^6 Cos[x]^10 + 326 (I Sin[x])^10 Cos[x]^6 + 472 (I Sin[x])^8 Cos[x]^8 + 37 (I Sin[x])^3 Cos[x]^13 + 37 (I Sin[x])^13 Cos[x]^3 + 10 (I Sin[x])^2 Cos[x]^14 + 10 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[9 I y] (76 (I Sin[x])^5 Cos[x]^11 + 76 (I Sin[x])^11 Cos[x]^5 + 146 (I Sin[x])^9 Cos[x]^7 + 146 (I Sin[x])^7 Cos[x]^9 + 9 (I Sin[x])^3 Cos[x]^13 + 9 (I Sin[x])^13 Cos[x]^3 + 162 (I Sin[x])^8 Cos[x]^8 + 111 (I Sin[x])^6 Cos[x]^10 + 111 (I Sin[x])^10 Cos[x]^6 + 31 (I Sin[x])^4 Cos[x]^12 + 31 (I Sin[x])^12 Cos[x]^4 + 1 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^2) + Exp[11 I y] (38 (I Sin[x])^8 Cos[x]^8 + 29 (I Sin[x])^10 Cos[x]^6 + 29 (I Sin[x])^6 Cos[x]^10 + 8 (I Sin[x])^4 Cos[x]^12 + 8 (I Sin[x])^12 Cos[x]^4 + 19 (I Sin[x])^5 Cos[x]^11 + 19 (I Sin[x])^11 Cos[x]^5 + 28 (I Sin[x])^7 Cos[x]^9 + 28 (I Sin[x])^9 Cos[x]^7 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3) + Exp[13 I y] (5 (I Sin[x])^6 Cos[x]^10 + 5 (I Sin[x])^10 Cos[x]^6 + 4 (I Sin[x])^8 Cos[x]^8 + 1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4 + 5 (I Sin[x])^9 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^9 + 2 (I Sin[x])^5 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^5) + Exp[15 I y] (1 (I Sin[x])^9 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^9))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^7) + Exp[-13 I y] (7 (I Sin[x])^6 Cos[x]^10 + 7 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^8 Cos[x]^8 + 4 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^5 + 3 (I Sin[x])^7 Cos[x]^9 + 3 (I Sin[x])^9 Cos[x]^7) + Exp[-11 I y] (23 (I Sin[x])^6 Cos[x]^10 + 23 (I Sin[x])^10 Cos[x]^6 + 66 (I Sin[x])^8 Cos[x]^8 + 46 (I Sin[x])^7 Cos[x]^9 + 46 (I Sin[x])^9 Cos[x]^7 + 3 (I Sin[x])^5 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^5) + Exp[-9 I y] (158 (I Sin[x])^7 Cos[x]^9 + 158 (I Sin[x])^9 Cos[x]^7 + 120 (I Sin[x])^6 Cos[x]^10 + 120 (I Sin[x])^10 Cos[x]^6 + 152 (I Sin[x])^8 Cos[x]^8 + 70 (I Sin[x])^5 Cos[x]^11 + 70 (I Sin[x])^11 Cos[x]^5 + 28 (I Sin[x])^4 Cos[x]^12 + 28 (I Sin[x])^12 Cos[x]^4 + 3 (I Sin[x])^3 Cos[x]^13 + 3 (I Sin[x])^13 Cos[x]^3) + Exp[-7 I y] (594 (I Sin[x])^7 Cos[x]^9 + 594 (I Sin[x])^9 Cos[x]^7 + 99 (I Sin[x])^5 Cos[x]^11 + 99 (I Sin[x])^11 Cos[x]^5 + 296 (I Sin[x])^6 Cos[x]^10 + 296 (I Sin[x])^10 Cos[x]^6 + 726 (I Sin[x])^8 Cos[x]^8 + 13 (I Sin[x])^4 Cos[x]^12 + 13 (I Sin[x])^12 Cos[x]^4) + Exp[-5 I y] (752 (I Sin[x])^6 Cos[x]^10 + 752 (I Sin[x])^10 Cos[x]^6 + 1118 (I Sin[x])^8 Cos[x]^8 + 452 (I Sin[x])^5 Cos[x]^11 + 452 (I Sin[x])^11 Cos[x]^5 + 980 (I Sin[x])^7 Cos[x]^9 + 980 (I Sin[x])^9 Cos[x]^7 + 194 (I Sin[x])^4 Cos[x]^12 + 194 (I Sin[x])^12 Cos[x]^4 + 59 (I Sin[x])^3 Cos[x]^13 + 59 (I Sin[x])^13 Cos[x]^3 + 7 (I Sin[x])^2 Cos[x]^14 + 7 (I Sin[x])^14 Cos[x]^2) + Exp[-3 I y] (1263 (I Sin[x])^6 Cos[x]^10 + 1263 (I Sin[x])^10 Cos[x]^6 + 2208 (I Sin[x])^8 Cos[x]^8 + 1923 (I Sin[x])^7 Cos[x]^9 + 1923 (I Sin[x])^9 Cos[x]^7 + 153 (I Sin[x])^4 Cos[x]^12 + 153 (I Sin[x])^12 Cos[x]^4 + 543 (I Sin[x])^5 Cos[x]^11 + 543 (I Sin[x])^11 Cos[x]^5 + 19 (I Sin[x])^3 Cos[x]^13 + 19 (I Sin[x])^13 Cos[x]^3) + Exp[-1 I y] (2162 (I Sin[x])^7 Cos[x]^9 + 2162 (I Sin[x])^9 Cos[x]^7 + 910 (I Sin[x])^5 Cos[x]^11 + 910 (I Sin[x])^11 Cos[x]^5 + 440 (I Sin[x])^4 Cos[x]^12 + 440 (I Sin[x])^12 Cos[x]^4 + 1550 (I Sin[x])^6 Cos[x]^10 + 1550 (I Sin[x])^10 Cos[x]^6 + 2336 (I Sin[x])^8 Cos[x]^8 + 158 (I Sin[x])^3 Cos[x]^13 + 158 (I Sin[x])^13 Cos[x]^3 + 42 (I Sin[x])^2 Cos[x]^14 + 42 (I Sin[x])^14 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^15 + 5 (I Sin[x])^15 Cos[x]^1) + Exp[1 I y] (885 (I Sin[x])^5 Cos[x]^11 + 885 (I Sin[x])^11 Cos[x]^5 + 2259 (I Sin[x])^9 Cos[x]^7 + 2259 (I Sin[x])^7 Cos[x]^9 + 2552 (I Sin[x])^8 Cos[x]^8 + 1565 (I Sin[x])^6 Cos[x]^10 + 1565 (I Sin[x])^10 Cos[x]^6 + 91 (I Sin[x])^3 Cos[x]^13 + 91 (I Sin[x])^13 Cos[x]^3 + 348 (I Sin[x])^4 Cos[x]^12 + 348 (I Sin[x])^12 Cos[x]^4 + 11 (I Sin[x])^2 Cos[x]^14 + 11 (I Sin[x])^14 Cos[x]^2) + Exp[3 I y] (1888 (I Sin[x])^8 Cos[x]^8 + 1220 (I Sin[x])^6 Cos[x]^10 + 1220 (I Sin[x])^10 Cos[x]^6 + 322 (I Sin[x])^4 Cos[x]^12 + 322 (I Sin[x])^12 Cos[x]^4 + 119 (I Sin[x])^3 Cos[x]^13 + 119 (I Sin[x])^13 Cos[x]^3 + 713 (I Sin[x])^5 Cos[x]^11 + 713 (I Sin[x])^11 Cos[x]^5 + 1645 (I Sin[x])^7 Cos[x]^9 + 1645 (I Sin[x])^9 Cos[x]^7 + 33 (I Sin[x])^2 Cos[x]^14 + 33 (I Sin[x])^14 Cos[x]^2 + 8 (I Sin[x])^1 Cos[x]^15 + 8 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[5 I y] (182 (I Sin[x])^4 Cos[x]^12 + 182 (I Sin[x])^12 Cos[x]^4 + 741 (I Sin[x])^10 Cos[x]^6 + 741 (I Sin[x])^6 Cos[x]^10 + 1146 (I Sin[x])^8 Cos[x]^8 + 1032 (I Sin[x])^9 Cos[x]^7 + 1032 (I Sin[x])^7 Cos[x]^9 + 394 (I Sin[x])^5 Cos[x]^11 + 394 (I Sin[x])^11 Cos[x]^5 + 63 (I Sin[x])^3 Cos[x]^13 + 63 (I Sin[x])^13 Cos[x]^3 + 16 (I Sin[x])^2 Cos[x]^14 + 16 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[7 I y] (457 (I Sin[x])^9 Cos[x]^7 + 457 (I Sin[x])^7 Cos[x]^9 + 198 (I Sin[x])^5 Cos[x]^11 + 198 (I Sin[x])^11 Cos[x]^5 + 100 (I Sin[x])^4 Cos[x]^12 + 100 (I Sin[x])^12 Cos[x]^4 + 326 (I Sin[x])^6 Cos[x]^10 + 326 (I Sin[x])^10 Cos[x]^6 + 472 (I Sin[x])^8 Cos[x]^8 + 37 (I Sin[x])^3 Cos[x]^13 + 37 (I Sin[x])^13 Cos[x]^3 + 10 (I Sin[x])^2 Cos[x]^14 + 10 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[9 I y] (76 (I Sin[x])^5 Cos[x]^11 + 76 (I Sin[x])^11 Cos[x]^5 + 146 (I Sin[x])^9 Cos[x]^7 + 146 (I Sin[x])^7 Cos[x]^9 + 9 (I Sin[x])^3 Cos[x]^13 + 9 (I Sin[x])^13 Cos[x]^3 + 162 (I Sin[x])^8 Cos[x]^8 + 111 (I Sin[x])^6 Cos[x]^10 + 111 (I Sin[x])^10 Cos[x]^6 + 31 (I Sin[x])^4 Cos[x]^12 + 31 (I Sin[x])^12 Cos[x]^4 + 1 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^2) + Exp[11 I y] (38 (I Sin[x])^8 Cos[x]^8 + 29 (I Sin[x])^10 Cos[x]^6 + 29 (I Sin[x])^6 Cos[x]^10 + 8 (I Sin[x])^4 Cos[x]^12 + 8 (I Sin[x])^12 Cos[x]^4 + 19 (I Sin[x])^5 Cos[x]^11 + 19 (I Sin[x])^11 Cos[x]^5 + 28 (I Sin[x])^7 Cos[x]^9 + 28 (I Sin[x])^9 Cos[x]^7 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3) + Exp[13 I y] (5 (I Sin[x])^6 Cos[x]^10 + 5 (I Sin[x])^10 Cos[x]^6 + 4 (I Sin[x])^8 Cos[x]^8 + 1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4 + 5 (I Sin[x])^9 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^9 + 2 (I Sin[x])^5 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^5) + Exp[15 I y] (1 (I Sin[x])^9 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^9));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":698.2,"max_line_length":5012,"alphanum_fraction":0.5046309558} {"size":9903,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 15;\nname = \"15v3 1 3 1 1 1 3 1 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-14 I y] (1 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^4) + Exp[-12 I y] (3 (I Sin[x])^5 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^5 + 1 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^4 + 5 (I Sin[x])^9 Cos[x]^6 + 5 (I Sin[x])^6 Cos[x]^9 + 5 (I Sin[x])^8 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^8) + Exp[-10 I y] (5 (I Sin[x])^3 Cos[x]^12 + 5 (I Sin[x])^12 Cos[x]^3 + 25 (I Sin[x])^5 Cos[x]^10 + 25 (I Sin[x])^10 Cos[x]^5 + 9 (I Sin[x])^4 Cos[x]^11 + 9 (I Sin[x])^11 Cos[x]^4 + 27 (I Sin[x])^6 Cos[x]^9 + 27 (I Sin[x])^9 Cos[x]^6 + 25 (I Sin[x])^7 Cos[x]^8 + 25 (I Sin[x])^8 Cos[x]^7) + Exp[-8 I y] (115 (I Sin[x])^6 Cos[x]^9 + 115 (I Sin[x])^9 Cos[x]^6 + 21 (I Sin[x])^11 Cos[x]^4 + 21 (I Sin[x])^4 Cos[x]^11 + 61 (I Sin[x])^5 Cos[x]^10 + 61 (I Sin[x])^10 Cos[x]^5 + 163 (I Sin[x])^7 Cos[x]^8 + 163 (I Sin[x])^8 Cos[x]^7 + 4 (I Sin[x])^3 Cos[x]^12 + 4 (I Sin[x])^12 Cos[x]^3) + Exp[-6 I y] (98 (I Sin[x])^4 Cos[x]^11 + 98 (I Sin[x])^11 Cos[x]^4 + 303 (I Sin[x])^6 Cos[x]^9 + 303 (I Sin[x])^9 Cos[x]^6 + 181 (I Sin[x])^5 Cos[x]^10 + 181 (I Sin[x])^10 Cos[x]^5 + 385 (I Sin[x])^7 Cos[x]^8 + 385 (I Sin[x])^8 Cos[x]^7 + 8 (I Sin[x])^2 Cos[x]^13 + 8 (I Sin[x])^13 Cos[x]^2 + 26 (I Sin[x])^3 Cos[x]^12 + 26 (I Sin[x])^12 Cos[x]^3) + Exp[-4 I y] (854 (I Sin[x])^7 Cos[x]^8 + 854 (I Sin[x])^8 Cos[x]^7 + 342 (I Sin[x])^5 Cos[x]^10 + 342 (I Sin[x])^10 Cos[x]^5 + 126 (I Sin[x])^4 Cos[x]^11 + 126 (I Sin[x])^11 Cos[x]^4 + 646 (I Sin[x])^9 Cos[x]^6 + 646 (I Sin[x])^6 Cos[x]^9 + 30 (I Sin[x])^12 Cos[x]^3 + 30 (I Sin[x])^3 Cos[x]^12 + 4 (I Sin[x])^2 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^2) + Exp[-2 I y] (108 (I Sin[x])^3 Cos[x]^12 + 108 (I Sin[x])^12 Cos[x]^3 + 582 (I Sin[x])^5 Cos[x]^10 + 582 (I Sin[x])^10 Cos[x]^5 + 1120 (I Sin[x])^7 Cos[x]^8 + 1120 (I Sin[x])^8 Cos[x]^7 + 903 (I Sin[x])^6 Cos[x]^9 + 903 (I Sin[x])^9 Cos[x]^6 + 263 (I Sin[x])^4 Cos[x]^11 + 263 (I Sin[x])^11 Cos[x]^4 + 5 (I Sin[x])^1 Cos[x]^14 + 5 (I Sin[x])^14 Cos[x]^1 + 22 (I Sin[x])^2 Cos[x]^13 + 22 (I Sin[x])^13 Cos[x]^2) + Exp[0 I y] (1484 (I Sin[x])^8 Cos[x]^7 + 1484 (I Sin[x])^7 Cos[x]^8 + 1065 (I Sin[x])^6 Cos[x]^9 + 1065 (I Sin[x])^9 Cos[x]^6 + 229 (I Sin[x])^4 Cos[x]^11 + 229 (I Sin[x])^11 Cos[x]^4 + 63 (I Sin[x])^3 Cos[x]^12 + 63 (I Sin[x])^12 Cos[x]^3 + 579 (I Sin[x])^10 Cos[x]^5 + 579 (I Sin[x])^5 Cos[x]^10 + 11 (I Sin[x])^13 Cos[x]^2 + 11 (I Sin[x])^2 Cos[x]^13 + 1 (I Sin[x])^1 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^1) + Exp[2 I y] (36 (I Sin[x])^2 Cos[x]^13 + 36 (I Sin[x])^13 Cos[x]^2 + 303 (I Sin[x])^4 Cos[x]^11 + 303 (I Sin[x])^11 Cos[x]^4 + 883 (I Sin[x])^6 Cos[x]^9 + 883 (I Sin[x])^9 Cos[x]^6 + 1115 (I Sin[x])^8 Cos[x]^7 + 1115 (I Sin[x])^7 Cos[x]^8 + 556 (I Sin[x])^5 Cos[x]^10 + 556 (I Sin[x])^10 Cos[x]^5 + 104 (I Sin[x])^3 Cos[x]^12 + 104 (I Sin[x])^12 Cos[x]^3 + 1 Cos[x]^15 + 1 (I Sin[x])^15 + 5 (I Sin[x])^1 Cos[x]^14 + 5 (I Sin[x])^14 Cos[x]^1) + Exp[4 I y] (632 (I Sin[x])^9 Cos[x]^6 + 632 (I Sin[x])^6 Cos[x]^9 + 791 (I Sin[x])^8 Cos[x]^7 + 791 (I Sin[x])^7 Cos[x]^8 + 366 (I Sin[x])^10 Cos[x]^5 + 366 (I Sin[x])^5 Cos[x]^10 + 47 (I Sin[x])^12 Cos[x]^3 + 47 (I Sin[x])^3 Cos[x]^12 + 156 (I Sin[x])^4 Cos[x]^11 + 156 (I Sin[x])^11 Cos[x]^4 + 9 (I Sin[x])^2 Cos[x]^13 + 9 (I Sin[x])^13 Cos[x]^2 + 1 (I Sin[x])^14 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^14) + Exp[6 I y] (50 (I Sin[x])^3 Cos[x]^12 + 50 (I Sin[x])^12 Cos[x]^3 + 209 (I Sin[x])^5 Cos[x]^10 + 209 (I Sin[x])^10 Cos[x]^5 + 335 (I Sin[x])^7 Cos[x]^8 + 335 (I Sin[x])^8 Cos[x]^7 + 294 (I Sin[x])^9 Cos[x]^6 + 294 (I Sin[x])^6 Cos[x]^9 + 100 (I Sin[x])^4 Cos[x]^11 + 100 (I Sin[x])^11 Cos[x]^4 + 3 (I Sin[x])^1 Cos[x]^14 + 3 (I Sin[x])^14 Cos[x]^1 + 10 (I Sin[x])^2 Cos[x]^13 + 10 (I Sin[x])^13 Cos[x]^2) + Exp[8 I y] (75 (I Sin[x])^10 Cos[x]^5 + 75 (I Sin[x])^5 Cos[x]^10 + 133 (I Sin[x])^8 Cos[x]^7 + 133 (I Sin[x])^7 Cos[x]^8 + 107 (I Sin[x])^6 Cos[x]^9 + 107 (I Sin[x])^9 Cos[x]^6 + 36 (I Sin[x])^4 Cos[x]^11 + 36 (I Sin[x])^11 Cos[x]^4 + 11 (I Sin[x])^3 Cos[x]^12 + 11 (I Sin[x])^12 Cos[x]^3 + 2 (I Sin[x])^13 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^13) + Exp[10 I y] (3 (I Sin[x])^2 Cos[x]^13 + 3 (I Sin[x])^13 Cos[x]^2 + 19 (I Sin[x])^4 Cos[x]^11 + 19 (I Sin[x])^11 Cos[x]^4 + 21 (I Sin[x])^6 Cos[x]^9 + 21 (I Sin[x])^9 Cos[x]^6 + 23 (I Sin[x])^8 Cos[x]^7 + 23 (I Sin[x])^7 Cos[x]^8 + 20 (I Sin[x])^10 Cos[x]^5 + 20 (I Sin[x])^5 Cos[x]^10 + 5 (I Sin[x])^3 Cos[x]^12 + 5 (I Sin[x])^12 Cos[x]^3) + Exp[12 I y] (3 (I Sin[x])^11 Cos[x]^4 + 3 (I Sin[x])^4 Cos[x]^11 + 4 (I Sin[x])^6 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^6 + 2 (I Sin[x])^8 Cos[x]^7 + 2 (I Sin[x])^7 Cos[x]^8 + 4 (I Sin[x])^10 Cos[x]^5 + 4 (I Sin[x])^5 Cos[x]^10 + 1 (I Sin[x])^12 Cos[x]^3 + 1 (I Sin[x])^3 Cos[x]^12) + Exp[14 I y] (1 (I Sin[x])^3 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^3))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-14 I y] (1 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^4) + Exp[-12 I y] (3 (I Sin[x])^5 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^5 + 1 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^4 + 5 (I Sin[x])^9 Cos[x]^6 + 5 (I Sin[x])^6 Cos[x]^9 + 5 (I Sin[x])^8 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^8) + Exp[-10 I y] (5 (I Sin[x])^3 Cos[x]^12 + 5 (I Sin[x])^12 Cos[x]^3 + 25 (I Sin[x])^5 Cos[x]^10 + 25 (I Sin[x])^10 Cos[x]^5 + 9 (I Sin[x])^4 Cos[x]^11 + 9 (I Sin[x])^11 Cos[x]^4 + 27 (I Sin[x])^6 Cos[x]^9 + 27 (I Sin[x])^9 Cos[x]^6 + 25 (I Sin[x])^7 Cos[x]^8 + 25 (I Sin[x])^8 Cos[x]^7) + Exp[-8 I y] (115 (I Sin[x])^6 Cos[x]^9 + 115 (I Sin[x])^9 Cos[x]^6 + 21 (I Sin[x])^11 Cos[x]^4 + 21 (I Sin[x])^4 Cos[x]^11 + 61 (I Sin[x])^5 Cos[x]^10 + 61 (I Sin[x])^10 Cos[x]^5 + 163 (I Sin[x])^7 Cos[x]^8 + 163 (I Sin[x])^8 Cos[x]^7 + 4 (I Sin[x])^3 Cos[x]^12 + 4 (I Sin[x])^12 Cos[x]^3) + Exp[-6 I y] (98 (I Sin[x])^4 Cos[x]^11 + 98 (I Sin[x])^11 Cos[x]^4 + 303 (I Sin[x])^6 Cos[x]^9 + 303 (I Sin[x])^9 Cos[x]^6 + 181 (I Sin[x])^5 Cos[x]^10 + 181 (I Sin[x])^10 Cos[x]^5 + 385 (I Sin[x])^7 Cos[x]^8 + 385 (I Sin[x])^8 Cos[x]^7 + 8 (I Sin[x])^2 Cos[x]^13 + 8 (I Sin[x])^13 Cos[x]^2 + 26 (I Sin[x])^3 Cos[x]^12 + 26 (I Sin[x])^12 Cos[x]^3) + Exp[-4 I y] (854 (I Sin[x])^7 Cos[x]^8 + 854 (I Sin[x])^8 Cos[x]^7 + 342 (I Sin[x])^5 Cos[x]^10 + 342 (I Sin[x])^10 Cos[x]^5 + 126 (I Sin[x])^4 Cos[x]^11 + 126 (I Sin[x])^11 Cos[x]^4 + 646 (I Sin[x])^9 Cos[x]^6 + 646 (I Sin[x])^6 Cos[x]^9 + 30 (I Sin[x])^12 Cos[x]^3 + 30 (I Sin[x])^3 Cos[x]^12 + 4 (I Sin[x])^2 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^2) + Exp[-2 I y] (108 (I Sin[x])^3 Cos[x]^12 + 108 (I Sin[x])^12 Cos[x]^3 + 582 (I Sin[x])^5 Cos[x]^10 + 582 (I Sin[x])^10 Cos[x]^5 + 1120 (I Sin[x])^7 Cos[x]^8 + 1120 (I Sin[x])^8 Cos[x]^7 + 903 (I Sin[x])^6 Cos[x]^9 + 903 (I Sin[x])^9 Cos[x]^6 + 263 (I Sin[x])^4 Cos[x]^11 + 263 (I Sin[x])^11 Cos[x]^4 + 5 (I Sin[x])^1 Cos[x]^14 + 5 (I Sin[x])^14 Cos[x]^1 + 22 (I Sin[x])^2 Cos[x]^13 + 22 (I Sin[x])^13 Cos[x]^2) + Exp[0 I y] (1484 (I Sin[x])^8 Cos[x]^7 + 1484 (I Sin[x])^7 Cos[x]^8 + 1065 (I Sin[x])^6 Cos[x]^9 + 1065 (I Sin[x])^9 Cos[x]^6 + 229 (I Sin[x])^4 Cos[x]^11 + 229 (I Sin[x])^11 Cos[x]^4 + 63 (I Sin[x])^3 Cos[x]^12 + 63 (I Sin[x])^12 Cos[x]^3 + 579 (I Sin[x])^10 Cos[x]^5 + 579 (I Sin[x])^5 Cos[x]^10 + 11 (I Sin[x])^13 Cos[x]^2 + 11 (I Sin[x])^2 Cos[x]^13 + 1 (I Sin[x])^1 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^1) + Exp[2 I y] (36 (I Sin[x])^2 Cos[x]^13 + 36 (I Sin[x])^13 Cos[x]^2 + 303 (I Sin[x])^4 Cos[x]^11 + 303 (I Sin[x])^11 Cos[x]^4 + 883 (I Sin[x])^6 Cos[x]^9 + 883 (I Sin[x])^9 Cos[x]^6 + 1115 (I Sin[x])^8 Cos[x]^7 + 1115 (I Sin[x])^7 Cos[x]^8 + 556 (I Sin[x])^5 Cos[x]^10 + 556 (I Sin[x])^10 Cos[x]^5 + 104 (I Sin[x])^3 Cos[x]^12 + 104 (I Sin[x])^12 Cos[x]^3 + 1 Cos[x]^15 + 1 (I Sin[x])^15 + 5 (I Sin[x])^1 Cos[x]^14 + 5 (I Sin[x])^14 Cos[x]^1) + Exp[4 I y] (632 (I Sin[x])^9 Cos[x]^6 + 632 (I Sin[x])^6 Cos[x]^9 + 791 (I Sin[x])^8 Cos[x]^7 + 791 (I Sin[x])^7 Cos[x]^8 + 366 (I Sin[x])^10 Cos[x]^5 + 366 (I Sin[x])^5 Cos[x]^10 + 47 (I Sin[x])^12 Cos[x]^3 + 47 (I Sin[x])^3 Cos[x]^12 + 156 (I Sin[x])^4 Cos[x]^11 + 156 (I Sin[x])^11 Cos[x]^4 + 9 (I Sin[x])^2 Cos[x]^13 + 9 (I Sin[x])^13 Cos[x]^2 + 1 (I Sin[x])^14 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^14) + Exp[6 I y] (50 (I Sin[x])^3 Cos[x]^12 + 50 (I Sin[x])^12 Cos[x]^3 + 209 (I Sin[x])^5 Cos[x]^10 + 209 (I Sin[x])^10 Cos[x]^5 + 335 (I Sin[x])^7 Cos[x]^8 + 335 (I Sin[x])^8 Cos[x]^7 + 294 (I Sin[x])^9 Cos[x]^6 + 294 (I Sin[x])^6 Cos[x]^9 + 100 (I Sin[x])^4 Cos[x]^11 + 100 (I Sin[x])^11 Cos[x]^4 + 3 (I Sin[x])^1 Cos[x]^14 + 3 (I Sin[x])^14 Cos[x]^1 + 10 (I Sin[x])^2 Cos[x]^13 + 10 (I Sin[x])^13 Cos[x]^2) + Exp[8 I y] (75 (I Sin[x])^10 Cos[x]^5 + 75 (I Sin[x])^5 Cos[x]^10 + 133 (I Sin[x])^8 Cos[x]^7 + 133 (I Sin[x])^7 Cos[x]^8 + 107 (I Sin[x])^6 Cos[x]^9 + 107 (I Sin[x])^9 Cos[x]^6 + 36 (I Sin[x])^4 Cos[x]^11 + 36 (I Sin[x])^11 Cos[x]^4 + 11 (I Sin[x])^3 Cos[x]^12 + 11 (I Sin[x])^12 Cos[x]^3 + 2 (I Sin[x])^13 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^13) + Exp[10 I y] (3 (I Sin[x])^2 Cos[x]^13 + 3 (I Sin[x])^13 Cos[x]^2 + 19 (I Sin[x])^4 Cos[x]^11 + 19 (I Sin[x])^11 Cos[x]^4 + 21 (I Sin[x])^6 Cos[x]^9 + 21 (I Sin[x])^9 Cos[x]^6 + 23 (I Sin[x])^8 Cos[x]^7 + 23 (I Sin[x])^7 Cos[x]^8 + 20 (I Sin[x])^10 Cos[x]^5 + 20 (I Sin[x])^5 Cos[x]^10 + 5 (I Sin[x])^3 Cos[x]^12 + 5 (I Sin[x])^12 Cos[x]^3) + Exp[12 I y] (3 (I Sin[x])^11 Cos[x]^4 + 3 (I Sin[x])^4 Cos[x]^11 + 4 (I Sin[x])^6 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^6 + 2 (I Sin[x])^8 Cos[x]^7 + 2 (I Sin[x])^7 Cos[x]^8 + 4 (I Sin[x])^10 Cos[x]^5 + 4 (I Sin[x])^5 Cos[x]^10 + 1 (I Sin[x])^12 Cos[x]^3 + 1 (I Sin[x])^3 Cos[x]^12) + Exp[14 I y] (1 (I Sin[x])^3 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^3));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", 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{"size":390,"ext":"cdf","lang":"Mathematica","max_stars_count":null,"content":"\/* Quartus Prime Version 16.0.0 Build 211 04\/27\/2016 SJ Standard Edition *\/\nJedecChain;\n\tFileRevision(JESD32A);\n\tDefaultMfr(6E);\n\n\tP ActionCode(Ign)\n\t\tDevice PartName(SOCVHPS) MfrSpec(OpMask(0));\n\tP ActionCode(Cfg)\n\t\tDevice PartName(5CSEMA5F31) Path(\"\/users\/zicew\/ece327\/new\/lab0\/output_files\/\") File(\"example.sof\") MfrSpec(OpMask(1));\n\nChainEnd;\n\nAlteraBegin;\n\tChainType(JTAG);\nAlteraEnd;\n","avg_line_length":24.375,"max_line_length":120,"alphanum_fraction":0.7487179487} {"size":10631,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 16;\nname = \"16v4 4 2 1 1 1 1 2\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-15 I y] (2 (I Sin[x])^8 Cos[x]^8) + Exp[-13 I y] (6 (I Sin[x])^7 Cos[x]^9 + 6 (I Sin[x])^9 Cos[x]^7 + 5 (I Sin[x])^6 Cos[x]^10 + 5 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^5 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^5 + 1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^8 Cos[x]^8) + Exp[-11 I y] (48 (I Sin[x])^7 Cos[x]^9 + 48 (I Sin[x])^9 Cos[x]^7 + 52 (I Sin[x])^8 Cos[x]^8 + 22 (I Sin[x])^10 Cos[x]^6 + 22 (I Sin[x])^6 Cos[x]^10 + 8 (I Sin[x])^11 Cos[x]^5 + 8 (I Sin[x])^5 Cos[x]^11 + 1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4) + Exp[-9 I y] (144 (I Sin[x])^8 Cos[x]^8 + 108 (I Sin[x])^6 Cos[x]^10 + 108 (I Sin[x])^10 Cos[x]^6 + 87 (I Sin[x])^5 Cos[x]^11 + 87 (I Sin[x])^11 Cos[x]^5 + 118 (I Sin[x])^7 Cos[x]^9 + 118 (I Sin[x])^9 Cos[x]^7 + 48 (I Sin[x])^4 Cos[x]^12 + 48 (I Sin[x])^12 Cos[x]^4 + 19 (I Sin[x])^3 Cos[x]^13 + 19 (I Sin[x])^13 Cos[x]^3 + 3 (I Sin[x])^2 Cos[x]^14 + 3 (I Sin[x])^14 Cos[x]^2) + Exp[-7 I y] (356 (I Sin[x])^6 Cos[x]^10 + 356 (I Sin[x])^10 Cos[x]^6 + 556 (I Sin[x])^8 Cos[x]^8 + 490 (I Sin[x])^9 Cos[x]^7 + 490 (I Sin[x])^7 Cos[x]^9 + 173 (I Sin[x])^5 Cos[x]^11 + 173 (I Sin[x])^11 Cos[x]^5 + 59 (I Sin[x])^12 Cos[x]^4 + 59 (I Sin[x])^4 Cos[x]^12 + 9 (I Sin[x])^13 Cos[x]^3 + 9 (I Sin[x])^3 Cos[x]^13) + Exp[-5 I y] (944 (I Sin[x])^9 Cos[x]^7 + 944 (I Sin[x])^7 Cos[x]^9 + 475 (I Sin[x])^5 Cos[x]^11 + 475 (I Sin[x])^11 Cos[x]^5 + 243 (I Sin[x])^4 Cos[x]^12 + 243 (I Sin[x])^12 Cos[x]^4 + 743 (I Sin[x])^6 Cos[x]^10 + 743 (I Sin[x])^10 Cos[x]^6 + 958 (I Sin[x])^8 Cos[x]^8 + 89 (I Sin[x])^3 Cos[x]^13 + 89 (I Sin[x])^13 Cos[x]^3 + 26 (I Sin[x])^2 Cos[x]^14 + 26 (I Sin[x])^14 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[-3 I y] (611 (I Sin[x])^5 Cos[x]^11 + 611 (I Sin[x])^11 Cos[x]^5 + 1850 (I Sin[x])^9 Cos[x]^7 + 1850 (I Sin[x])^7 Cos[x]^9 + 1201 (I Sin[x])^10 Cos[x]^6 + 1201 (I Sin[x])^6 Cos[x]^10 + 2118 (I Sin[x])^8 Cos[x]^8 + 216 (I Sin[x])^12 Cos[x]^4 + 216 (I Sin[x])^4 Cos[x]^12 + 59 (I Sin[x])^3 Cos[x]^13 + 59 (I Sin[x])^13 Cos[x]^3 + 9 (I Sin[x])^14 Cos[x]^2 + 9 (I Sin[x])^2 Cos[x]^14) + Exp[-1 I y] (1570 (I Sin[x])^10 Cos[x]^6 + 1570 (I Sin[x])^6 Cos[x]^10 + 2418 (I Sin[x])^8 Cos[x]^8 + 925 (I Sin[x])^5 Cos[x]^11 + 925 (I Sin[x])^11 Cos[x]^5 + 2120 (I Sin[x])^7 Cos[x]^9 + 2120 (I Sin[x])^9 Cos[x]^7 + 422 (I Sin[x])^4 Cos[x]^12 + 422 (I Sin[x])^12 Cos[x]^4 + 149 (I Sin[x])^3 Cos[x]^13 + 149 (I Sin[x])^13 Cos[x]^3 + 33 (I Sin[x])^2 Cos[x]^14 + 33 (I Sin[x])^14 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^15 + 6 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[1 I y] (1564 (I Sin[x])^6 Cos[x]^10 + 1564 (I Sin[x])^10 Cos[x]^6 + 2754 (I Sin[x])^8 Cos[x]^8 + 282 (I Sin[x])^4 Cos[x]^12 + 282 (I Sin[x])^12 Cos[x]^4 + 2384 (I Sin[x])^9 Cos[x]^7 + 2384 (I Sin[x])^7 Cos[x]^9 + 747 (I Sin[x])^5 Cos[x]^11 + 747 (I Sin[x])^11 Cos[x]^5 + 67 (I Sin[x])^3 Cos[x]^13 + 67 (I Sin[x])^13 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[3 I y] (1748 (I Sin[x])^9 Cos[x]^7 + 1748 (I Sin[x])^7 Cos[x]^9 + 677 (I Sin[x])^5 Cos[x]^11 + 677 (I Sin[x])^11 Cos[x]^5 + 287 (I Sin[x])^4 Cos[x]^12 + 287 (I Sin[x])^12 Cos[x]^4 + 1221 (I Sin[x])^6 Cos[x]^10 + 1221 (I Sin[x])^10 Cos[x]^6 + 1902 (I Sin[x])^8 Cos[x]^8 + 91 (I Sin[x])^3 Cos[x]^13 + 91 (I Sin[x])^13 Cos[x]^3 + 26 (I Sin[x])^2 Cos[x]^14 + 26 (I Sin[x])^14 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[5 I y] (389 (I Sin[x])^5 Cos[x]^11 + 389 (I Sin[x])^11 Cos[x]^5 + 1082 (I Sin[x])^9 Cos[x]^7 + 1082 (I Sin[x])^7 Cos[x]^9 + 41 (I Sin[x])^3 Cos[x]^13 + 41 (I Sin[x])^13 Cos[x]^3 + 1220 (I Sin[x])^8 Cos[x]^8 + 739 (I Sin[x])^6 Cos[x]^10 + 739 (I Sin[x])^10 Cos[x]^6 + 135 (I Sin[x])^4 Cos[x]^12 + 135 (I Sin[x])^12 Cos[x]^4 + 7 (I Sin[x])^2 Cos[x]^14 + 7 (I Sin[x])^14 Cos[x]^2) + Exp[7 I y] (548 (I Sin[x])^8 Cos[x]^8 + 329 (I Sin[x])^6 Cos[x]^10 + 329 (I Sin[x])^10 Cos[x]^6 + 86 (I Sin[x])^4 Cos[x]^12 + 86 (I Sin[x])^12 Cos[x]^4 + 30 (I Sin[x])^3 Cos[x]^13 + 30 (I Sin[x])^13 Cos[x]^3 + 182 (I Sin[x])^5 Cos[x]^11 + 182 (I Sin[x])^11 Cos[x]^5 + 460 (I Sin[x])^7 Cos[x]^9 + 460 (I Sin[x])^9 Cos[x]^7 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2) + Exp[9 I y] (35 (I Sin[x])^4 Cos[x]^12 + 35 (I Sin[x])^12 Cos[x]^4 + 116 (I Sin[x])^10 Cos[x]^6 + 116 (I Sin[x])^6 Cos[x]^10 + 160 (I Sin[x])^8 Cos[x]^8 + 148 (I Sin[x])^9 Cos[x]^7 + 148 (I Sin[x])^7 Cos[x]^9 + 70 (I Sin[x])^5 Cos[x]^11 + 70 (I Sin[x])^11 Cos[x]^5 + 6 (I Sin[x])^3 Cos[x]^13 + 6 (I Sin[x])^13 Cos[x]^3) + Exp[11 I y] (38 (I Sin[x])^9 Cos[x]^7 + 38 (I Sin[x])^7 Cos[x]^9 + 18 (I Sin[x])^5 Cos[x]^11 + 18 (I Sin[x])^11 Cos[x]^5 + 5 (I Sin[x])^4 Cos[x]^12 + 5 (I Sin[x])^12 Cos[x]^4 + 27 (I Sin[x])^6 Cos[x]^10 + 27 (I Sin[x])^10 Cos[x]^6 + 34 (I Sin[x])^8 Cos[x]^8) + Exp[13 I y] (4 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^9 Cos[x]^7 + 4 (I Sin[x])^7 Cos[x]^9 + 6 (I Sin[x])^10 Cos[x]^6 + 6 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^8 Cos[x]^8) + Exp[15 I y] (1 (I Sin[x])^10 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^10))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-15 I y] (2 (I Sin[x])^8 Cos[x]^8) + Exp[-13 I y] (6 (I Sin[x])^7 Cos[x]^9 + 6 (I Sin[x])^9 Cos[x]^7 + 5 (I Sin[x])^6 Cos[x]^10 + 5 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^5 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^5 + 1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^8 Cos[x]^8) + Exp[-11 I y] (48 (I Sin[x])^7 Cos[x]^9 + 48 (I Sin[x])^9 Cos[x]^7 + 52 (I Sin[x])^8 Cos[x]^8 + 22 (I Sin[x])^10 Cos[x]^6 + 22 (I Sin[x])^6 Cos[x]^10 + 8 (I Sin[x])^11 Cos[x]^5 + 8 (I Sin[x])^5 Cos[x]^11 + 1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4) + Exp[-9 I y] (144 (I Sin[x])^8 Cos[x]^8 + 108 (I Sin[x])^6 Cos[x]^10 + 108 (I Sin[x])^10 Cos[x]^6 + 87 (I Sin[x])^5 Cos[x]^11 + 87 (I Sin[x])^11 Cos[x]^5 + 118 (I Sin[x])^7 Cos[x]^9 + 118 (I Sin[x])^9 Cos[x]^7 + 48 (I Sin[x])^4 Cos[x]^12 + 48 (I Sin[x])^12 Cos[x]^4 + 19 (I Sin[x])^3 Cos[x]^13 + 19 (I Sin[x])^13 Cos[x]^3 + 3 (I Sin[x])^2 Cos[x]^14 + 3 (I Sin[x])^14 Cos[x]^2) + Exp[-7 I y] (356 (I Sin[x])^6 Cos[x]^10 + 356 (I Sin[x])^10 Cos[x]^6 + 556 (I Sin[x])^8 Cos[x]^8 + 490 (I Sin[x])^9 Cos[x]^7 + 490 (I Sin[x])^7 Cos[x]^9 + 173 (I Sin[x])^5 Cos[x]^11 + 173 (I Sin[x])^11 Cos[x]^5 + 59 (I Sin[x])^12 Cos[x]^4 + 59 (I Sin[x])^4 Cos[x]^12 + 9 (I Sin[x])^13 Cos[x]^3 + 9 (I Sin[x])^3 Cos[x]^13) + Exp[-5 I y] (944 (I Sin[x])^9 Cos[x]^7 + 944 (I Sin[x])^7 Cos[x]^9 + 475 (I Sin[x])^5 Cos[x]^11 + 475 (I Sin[x])^11 Cos[x]^5 + 243 (I Sin[x])^4 Cos[x]^12 + 243 (I Sin[x])^12 Cos[x]^4 + 743 (I Sin[x])^6 Cos[x]^10 + 743 (I Sin[x])^10 Cos[x]^6 + 958 (I Sin[x])^8 Cos[x]^8 + 89 (I Sin[x])^3 Cos[x]^13 + 89 (I Sin[x])^13 Cos[x]^3 + 26 (I Sin[x])^2 Cos[x]^14 + 26 (I Sin[x])^14 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[-3 I y] (611 (I Sin[x])^5 Cos[x]^11 + 611 (I Sin[x])^11 Cos[x]^5 + 1850 (I Sin[x])^9 Cos[x]^7 + 1850 (I Sin[x])^7 Cos[x]^9 + 1201 (I Sin[x])^10 Cos[x]^6 + 1201 (I Sin[x])^6 Cos[x]^10 + 2118 (I Sin[x])^8 Cos[x]^8 + 216 (I Sin[x])^12 Cos[x]^4 + 216 (I Sin[x])^4 Cos[x]^12 + 59 (I Sin[x])^3 Cos[x]^13 + 59 (I Sin[x])^13 Cos[x]^3 + 9 (I Sin[x])^14 Cos[x]^2 + 9 (I Sin[x])^2 Cos[x]^14) + Exp[-1 I y] (1570 (I Sin[x])^10 Cos[x]^6 + 1570 (I Sin[x])^6 Cos[x]^10 + 2418 (I Sin[x])^8 Cos[x]^8 + 925 (I Sin[x])^5 Cos[x]^11 + 925 (I Sin[x])^11 Cos[x]^5 + 2120 (I Sin[x])^7 Cos[x]^9 + 2120 (I Sin[x])^9 Cos[x]^7 + 422 (I Sin[x])^4 Cos[x]^12 + 422 (I Sin[x])^12 Cos[x]^4 + 149 (I Sin[x])^3 Cos[x]^13 + 149 (I Sin[x])^13 Cos[x]^3 + 33 (I Sin[x])^2 Cos[x]^14 + 33 (I Sin[x])^14 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^15 + 6 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[1 I y] (1564 (I Sin[x])^6 Cos[x]^10 + 1564 (I Sin[x])^10 Cos[x]^6 + 2754 (I Sin[x])^8 Cos[x]^8 + 282 (I Sin[x])^4 Cos[x]^12 + 282 (I Sin[x])^12 Cos[x]^4 + 2384 (I Sin[x])^9 Cos[x]^7 + 2384 (I Sin[x])^7 Cos[x]^9 + 747 (I Sin[x])^5 Cos[x]^11 + 747 (I Sin[x])^11 Cos[x]^5 + 67 (I Sin[x])^3 Cos[x]^13 + 67 (I Sin[x])^13 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[3 I y] (1748 (I Sin[x])^9 Cos[x]^7 + 1748 (I Sin[x])^7 Cos[x]^9 + 677 (I Sin[x])^5 Cos[x]^11 + 677 (I Sin[x])^11 Cos[x]^5 + 287 (I Sin[x])^4 Cos[x]^12 + 287 (I Sin[x])^12 Cos[x]^4 + 1221 (I Sin[x])^6 Cos[x]^10 + 1221 (I Sin[x])^10 Cos[x]^6 + 1902 (I Sin[x])^8 Cos[x]^8 + 91 (I Sin[x])^3 Cos[x]^13 + 91 (I Sin[x])^13 Cos[x]^3 + 26 (I Sin[x])^2 Cos[x]^14 + 26 (I Sin[x])^14 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[5 I y] (389 (I Sin[x])^5 Cos[x]^11 + 389 (I Sin[x])^11 Cos[x]^5 + 1082 (I Sin[x])^9 Cos[x]^7 + 1082 (I Sin[x])^7 Cos[x]^9 + 41 (I Sin[x])^3 Cos[x]^13 + 41 (I Sin[x])^13 Cos[x]^3 + 1220 (I Sin[x])^8 Cos[x]^8 + 739 (I Sin[x])^6 Cos[x]^10 + 739 (I Sin[x])^10 Cos[x]^6 + 135 (I Sin[x])^4 Cos[x]^12 + 135 (I Sin[x])^12 Cos[x]^4 + 7 (I Sin[x])^2 Cos[x]^14 + 7 (I Sin[x])^14 Cos[x]^2) + Exp[7 I y] (548 (I Sin[x])^8 Cos[x]^8 + 329 (I Sin[x])^6 Cos[x]^10 + 329 (I Sin[x])^10 Cos[x]^6 + 86 (I Sin[x])^4 Cos[x]^12 + 86 (I Sin[x])^12 Cos[x]^4 + 30 (I Sin[x])^3 Cos[x]^13 + 30 (I Sin[x])^13 Cos[x]^3 + 182 (I Sin[x])^5 Cos[x]^11 + 182 (I Sin[x])^11 Cos[x]^5 + 460 (I Sin[x])^7 Cos[x]^9 + 460 (I Sin[x])^9 Cos[x]^7 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2) + Exp[9 I y] (35 (I Sin[x])^4 Cos[x]^12 + 35 (I Sin[x])^12 Cos[x]^4 + 116 (I Sin[x])^10 Cos[x]^6 + 116 (I Sin[x])^6 Cos[x]^10 + 160 (I Sin[x])^8 Cos[x]^8 + 148 (I Sin[x])^9 Cos[x]^7 + 148 (I Sin[x])^7 Cos[x]^9 + 70 (I Sin[x])^5 Cos[x]^11 + 70 (I Sin[x])^11 Cos[x]^5 + 6 (I Sin[x])^3 Cos[x]^13 + 6 (I Sin[x])^13 Cos[x]^3) + Exp[11 I y] (38 (I Sin[x])^9 Cos[x]^7 + 38 (I Sin[x])^7 Cos[x]^9 + 18 (I Sin[x])^5 Cos[x]^11 + 18 (I Sin[x])^11 Cos[x]^5 + 5 (I Sin[x])^4 Cos[x]^12 + 5 (I Sin[x])^12 Cos[x]^4 + 27 (I Sin[x])^6 Cos[x]^10 + 27 (I Sin[x])^10 Cos[x]^6 + 34 (I Sin[x])^8 Cos[x]^8) + Exp[13 I y] (4 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^9 Cos[x]^7 + 4 (I Sin[x])^7 Cos[x]^9 + 6 (I Sin[x])^10 Cos[x]^6 + 6 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^8 Cos[x]^8) + Exp[15 I y] (1 (I Sin[x])^10 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^10));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":708.7333333333,"max_line_length":5093,"alphanum_fraction":0.504279936} {"size":11019,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 16;\nname = \"16v4 1 3 1 1 1 3 2\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^5 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^5) + Exp[-13 I y] (2 (I Sin[x])^4 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^4 + 4 (I Sin[x])^10 Cos[x]^6 + 4 (I Sin[x])^6 Cos[x]^10 + 1 (I Sin[x])^3 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^3 + 3 (I Sin[x])^9 Cos[x]^7 + 3 (I Sin[x])^7 Cos[x]^9 + 4 (I Sin[x])^8 Cos[x]^8 + 3 (I Sin[x])^5 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^5) + Exp[-11 I y] (6 (I Sin[x])^4 Cos[x]^12 + 6 (I Sin[x])^12 Cos[x]^4 + 32 (I Sin[x])^6 Cos[x]^10 + 32 (I Sin[x])^10 Cos[x]^6 + 12 (I Sin[x])^5 Cos[x]^11 + 12 (I Sin[x])^11 Cos[x]^5 + 37 (I Sin[x])^7 Cos[x]^9 + 37 (I Sin[x])^9 Cos[x]^7 + 36 (I Sin[x])^8 Cos[x]^8) + Exp[-9 I y] (79 (I Sin[x])^5 Cos[x]^11 + 79 (I Sin[x])^11 Cos[x]^5 + 136 (I Sin[x])^9 Cos[x]^7 + 136 (I Sin[x])^7 Cos[x]^9 + 44 (I Sin[x])^4 Cos[x]^12 + 44 (I Sin[x])^12 Cos[x]^4 + 136 (I Sin[x])^8 Cos[x]^8 + 108 (I Sin[x])^6 Cos[x]^10 + 108 (I Sin[x])^10 Cos[x]^6 + 16 (I Sin[x])^3 Cos[x]^13 + 16 (I Sin[x])^13 Cos[x]^3 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2) + Exp[-7 I y] (165 (I Sin[x])^5 Cos[x]^11 + 165 (I Sin[x])^11 Cos[x]^5 + 516 (I Sin[x])^7 Cos[x]^9 + 516 (I Sin[x])^9 Cos[x]^7 + 320 (I Sin[x])^6 Cos[x]^10 + 320 (I Sin[x])^10 Cos[x]^6 + 12 (I Sin[x])^3 Cos[x]^13 + 12 (I Sin[x])^13 Cos[x]^3 + 46 (I Sin[x])^4 Cos[x]^12 + 46 (I Sin[x])^12 Cos[x]^4 + 612 (I Sin[x])^8 Cos[x]^8) + Exp[-5 I y] (746 (I Sin[x])^6 Cos[x]^10 + 746 (I Sin[x])^10 Cos[x]^6 + 247 (I Sin[x])^4 Cos[x]^12 + 247 (I Sin[x])^12 Cos[x]^4 + 994 (I Sin[x])^8 Cos[x]^8 + 92 (I Sin[x])^3 Cos[x]^13 + 92 (I Sin[x])^13 Cos[x]^3 + 909 (I Sin[x])^7 Cos[x]^9 + 909 (I Sin[x])^9 Cos[x]^7 + 486 (I Sin[x])^5 Cos[x]^11 + 486 (I Sin[x])^11 Cos[x]^5 + 22 (I Sin[x])^2 Cos[x]^14 + 22 (I Sin[x])^14 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[-3 I y] (227 (I Sin[x])^4 Cos[x]^12 + 227 (I Sin[x])^12 Cos[x]^4 + 2066 (I Sin[x])^8 Cos[x]^8 + 1251 (I Sin[x])^6 Cos[x]^10 + 1251 (I Sin[x])^10 Cos[x]^6 + 1841 (I Sin[x])^7 Cos[x]^9 + 1841 (I Sin[x])^9 Cos[x]^7 + 596 (I Sin[x])^5 Cos[x]^11 + 596 (I Sin[x])^11 Cos[x]^5 + 9 (I Sin[x])^2 Cos[x]^14 + 9 (I Sin[x])^14 Cos[x]^2 + 48 (I Sin[x])^3 Cos[x]^13 + 48 (I Sin[x])^13 Cos[x]^3) + Exp[-1 I y] (2154 (I Sin[x])^7 Cos[x]^9 + 2154 (I Sin[x])^9 Cos[x]^7 + 929 (I Sin[x])^5 Cos[x]^11 + 929 (I Sin[x])^11 Cos[x]^5 + 146 (I Sin[x])^3 Cos[x]^13 + 146 (I Sin[x])^13 Cos[x]^3 + 39 (I Sin[x])^2 Cos[x]^14 + 39 (I Sin[x])^14 Cos[x]^2 + 1569 (I Sin[x])^6 Cos[x]^10 + 1569 (I Sin[x])^10 Cos[x]^6 + 420 (I Sin[x])^4 Cos[x]^12 + 420 (I Sin[x])^12 Cos[x]^4 + 2342 (I Sin[x])^8 Cos[x]^8 + 6 (I Sin[x])^1 Cos[x]^15 + 6 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[1 I y] (82 (I Sin[x])^3 Cos[x]^13 + 82 (I Sin[x])^13 Cos[x]^3 + 2366 (I Sin[x])^9 Cos[x]^7 + 2366 (I Sin[x])^7 Cos[x]^9 + 785 (I Sin[x])^5 Cos[x]^11 + 785 (I Sin[x])^11 Cos[x]^5 + 2764 (I Sin[x])^8 Cos[x]^8 + 1532 (I Sin[x])^6 Cos[x]^10 + 1532 (I Sin[x])^10 Cos[x]^6 + 274 (I Sin[x])^4 Cos[x]^12 + 274 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2) + Exp[3 I y] (1964 (I Sin[x])^8 Cos[x]^8 + 1222 (I Sin[x])^10 Cos[x]^6 + 1222 (I Sin[x])^6 Cos[x]^10 + 294 (I Sin[x])^4 Cos[x]^12 + 294 (I Sin[x])^12 Cos[x]^4 + 97 (I Sin[x])^3 Cos[x]^13 + 97 (I Sin[x])^13 Cos[x]^3 + 663 (I Sin[x])^5 Cos[x]^11 + 663 (I Sin[x])^11 Cos[x]^5 + 1721 (I Sin[x])^7 Cos[x]^9 + 1721 (I Sin[x])^9 Cos[x]^7 + 22 (I Sin[x])^2 Cos[x]^14 + 22 (I Sin[x])^14 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[5 I y] (148 (I Sin[x])^4 Cos[x]^12 + 148 (I Sin[x])^12 Cos[x]^4 + 745 (I Sin[x])^10 Cos[x]^6 + 745 (I Sin[x])^6 Cos[x]^10 + 1224 (I Sin[x])^8 Cos[x]^8 + 1095 (I Sin[x])^9 Cos[x]^7 + 1095 (I Sin[x])^7 Cos[x]^9 + 364 (I Sin[x])^5 Cos[x]^11 + 364 (I Sin[x])^11 Cos[x]^5 + 7 (I Sin[x])^2 Cos[x]^14 + 7 (I Sin[x])^14 Cos[x]^2 + 32 (I Sin[x])^3 Cos[x]^13 + 32 (I Sin[x])^13 Cos[x]^3) + Exp[7 I y] (480 (I Sin[x])^9 Cos[x]^7 + 480 (I Sin[x])^7 Cos[x]^9 + 189 (I Sin[x])^11 Cos[x]^5 + 189 (I Sin[x])^5 Cos[x]^11 + 24 (I Sin[x])^3 Cos[x]^13 + 24 (I Sin[x])^13 Cos[x]^3 + 5 (I Sin[x])^2 Cos[x]^14 + 5 (I Sin[x])^14 Cos[x]^2 + 76 (I Sin[x])^4 Cos[x]^12 + 76 (I Sin[x])^12 Cos[x]^4 + 323 (I Sin[x])^6 Cos[x]^10 + 323 (I Sin[x])^10 Cos[x]^6 + 536 (I Sin[x])^8 Cos[x]^8) + Exp[9 I y] (8 (I Sin[x])^3 Cos[x]^13 + 8 (I Sin[x])^13 Cos[x]^3 + 75 (I Sin[x])^11 Cos[x]^5 + 75 (I Sin[x])^5 Cos[x]^11 + 148 (I Sin[x])^9 Cos[x]^7 + 148 (I Sin[x])^7 Cos[x]^9 + 120 (I Sin[x])^10 Cos[x]^6 + 120 (I Sin[x])^6 Cos[x]^10 + 160 (I Sin[x])^8 Cos[x]^8 + 24 (I Sin[x])^4 Cos[x]^12 + 24 (I Sin[x])^12 Cos[x]^4) + Exp[11 I y] (32 (I Sin[x])^10 Cos[x]^6 + 32 (I Sin[x])^6 Cos[x]^10 + 30 (I Sin[x])^8 Cos[x]^8 + 9 (I Sin[x])^4 Cos[x]^12 + 9 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3 + 16 (I Sin[x])^5 Cos[x]^11 + 16 (I Sin[x])^11 Cos[x]^5 + 31 (I Sin[x])^7 Cos[x]^9 + 31 (I Sin[x])^9 Cos[x]^7) + Exp[13 I y] (3 (I Sin[x])^4 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^4 + 4 (I Sin[x])^10 Cos[x]^6 + 4 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^8 Cos[x]^8 + 4 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^5 Cos[x]^11 + 3 (I Sin[x])^9 Cos[x]^7 + 3 (I Sin[x])^7 Cos[x]^9) + Exp[15 I y] (1 (I Sin[x])^11 Cos[x]^5 + 1 (I Sin[x])^5 Cos[x]^11))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^5 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^5) + Exp[-13 I y] (2 (I Sin[x])^4 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^4 + 4 (I Sin[x])^10 Cos[x]^6 + 4 (I Sin[x])^6 Cos[x]^10 + 1 (I Sin[x])^3 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^3 + 3 (I Sin[x])^9 Cos[x]^7 + 3 (I Sin[x])^7 Cos[x]^9 + 4 (I Sin[x])^8 Cos[x]^8 + 3 (I Sin[x])^5 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^5) + Exp[-11 I y] (6 (I Sin[x])^4 Cos[x]^12 + 6 (I Sin[x])^12 Cos[x]^4 + 32 (I Sin[x])^6 Cos[x]^10 + 32 (I Sin[x])^10 Cos[x]^6 + 12 (I Sin[x])^5 Cos[x]^11 + 12 (I Sin[x])^11 Cos[x]^5 + 37 (I Sin[x])^7 Cos[x]^9 + 37 (I Sin[x])^9 Cos[x]^7 + 36 (I Sin[x])^8 Cos[x]^8) + Exp[-9 I y] (79 (I Sin[x])^5 Cos[x]^11 + 79 (I Sin[x])^11 Cos[x]^5 + 136 (I Sin[x])^9 Cos[x]^7 + 136 (I Sin[x])^7 Cos[x]^9 + 44 (I Sin[x])^4 Cos[x]^12 + 44 (I Sin[x])^12 Cos[x]^4 + 136 (I Sin[x])^8 Cos[x]^8 + 108 (I Sin[x])^6 Cos[x]^10 + 108 (I Sin[x])^10 Cos[x]^6 + 16 (I Sin[x])^3 Cos[x]^13 + 16 (I Sin[x])^13 Cos[x]^3 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2) + Exp[-7 I y] (165 (I Sin[x])^5 Cos[x]^11 + 165 (I Sin[x])^11 Cos[x]^5 + 516 (I Sin[x])^7 Cos[x]^9 + 516 (I Sin[x])^9 Cos[x]^7 + 320 (I Sin[x])^6 Cos[x]^10 + 320 (I Sin[x])^10 Cos[x]^6 + 12 (I Sin[x])^3 Cos[x]^13 + 12 (I Sin[x])^13 Cos[x]^3 + 46 (I Sin[x])^4 Cos[x]^12 + 46 (I Sin[x])^12 Cos[x]^4 + 612 (I Sin[x])^8 Cos[x]^8) + Exp[-5 I y] (746 (I Sin[x])^6 Cos[x]^10 + 746 (I Sin[x])^10 Cos[x]^6 + 247 (I Sin[x])^4 Cos[x]^12 + 247 (I Sin[x])^12 Cos[x]^4 + 994 (I Sin[x])^8 Cos[x]^8 + 92 (I Sin[x])^3 Cos[x]^13 + 92 (I Sin[x])^13 Cos[x]^3 + 909 (I Sin[x])^7 Cos[x]^9 + 909 (I Sin[x])^9 Cos[x]^7 + 486 (I Sin[x])^5 Cos[x]^11 + 486 (I Sin[x])^11 Cos[x]^5 + 22 (I Sin[x])^2 Cos[x]^14 + 22 (I Sin[x])^14 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[-3 I y] (227 (I Sin[x])^4 Cos[x]^12 + 227 (I Sin[x])^12 Cos[x]^4 + 2066 (I Sin[x])^8 Cos[x]^8 + 1251 (I Sin[x])^6 Cos[x]^10 + 1251 (I Sin[x])^10 Cos[x]^6 + 1841 (I Sin[x])^7 Cos[x]^9 + 1841 (I Sin[x])^9 Cos[x]^7 + 596 (I Sin[x])^5 Cos[x]^11 + 596 (I Sin[x])^11 Cos[x]^5 + 9 (I Sin[x])^2 Cos[x]^14 + 9 (I Sin[x])^14 Cos[x]^2 + 48 (I Sin[x])^3 Cos[x]^13 + 48 (I Sin[x])^13 Cos[x]^3) + Exp[-1 I y] (2154 (I Sin[x])^7 Cos[x]^9 + 2154 (I Sin[x])^9 Cos[x]^7 + 929 (I Sin[x])^5 Cos[x]^11 + 929 (I Sin[x])^11 Cos[x]^5 + 146 (I Sin[x])^3 Cos[x]^13 + 146 (I Sin[x])^13 Cos[x]^3 + 39 (I Sin[x])^2 Cos[x]^14 + 39 (I Sin[x])^14 Cos[x]^2 + 1569 (I Sin[x])^6 Cos[x]^10 + 1569 (I Sin[x])^10 Cos[x]^6 + 420 (I Sin[x])^4 Cos[x]^12 + 420 (I Sin[x])^12 Cos[x]^4 + 2342 (I Sin[x])^8 Cos[x]^8 + 6 (I Sin[x])^1 Cos[x]^15 + 6 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[1 I y] (82 (I Sin[x])^3 Cos[x]^13 + 82 (I Sin[x])^13 Cos[x]^3 + 2366 (I Sin[x])^9 Cos[x]^7 + 2366 (I Sin[x])^7 Cos[x]^9 + 785 (I Sin[x])^5 Cos[x]^11 + 785 (I Sin[x])^11 Cos[x]^5 + 2764 (I Sin[x])^8 Cos[x]^8 + 1532 (I Sin[x])^6 Cos[x]^10 + 1532 (I Sin[x])^10 Cos[x]^6 + 274 (I Sin[x])^4 Cos[x]^12 + 274 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2) + Exp[3 I y] (1964 (I Sin[x])^8 Cos[x]^8 + 1222 (I Sin[x])^10 Cos[x]^6 + 1222 (I Sin[x])^6 Cos[x]^10 + 294 (I Sin[x])^4 Cos[x]^12 + 294 (I Sin[x])^12 Cos[x]^4 + 97 (I Sin[x])^3 Cos[x]^13 + 97 (I Sin[x])^13 Cos[x]^3 + 663 (I Sin[x])^5 Cos[x]^11 + 663 (I Sin[x])^11 Cos[x]^5 + 1721 (I Sin[x])^7 Cos[x]^9 + 1721 (I Sin[x])^9 Cos[x]^7 + 22 (I Sin[x])^2 Cos[x]^14 + 22 (I Sin[x])^14 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[5 I y] (148 (I Sin[x])^4 Cos[x]^12 + 148 (I Sin[x])^12 Cos[x]^4 + 745 (I Sin[x])^10 Cos[x]^6 + 745 (I Sin[x])^6 Cos[x]^10 + 1224 (I Sin[x])^8 Cos[x]^8 + 1095 (I Sin[x])^9 Cos[x]^7 + 1095 (I Sin[x])^7 Cos[x]^9 + 364 (I Sin[x])^5 Cos[x]^11 + 364 (I Sin[x])^11 Cos[x]^5 + 7 (I Sin[x])^2 Cos[x]^14 + 7 (I Sin[x])^14 Cos[x]^2 + 32 (I Sin[x])^3 Cos[x]^13 + 32 (I Sin[x])^13 Cos[x]^3) + Exp[7 I y] (480 (I Sin[x])^9 Cos[x]^7 + 480 (I Sin[x])^7 Cos[x]^9 + 189 (I Sin[x])^11 Cos[x]^5 + 189 (I Sin[x])^5 Cos[x]^11 + 24 (I Sin[x])^3 Cos[x]^13 + 24 (I Sin[x])^13 Cos[x]^3 + 5 (I Sin[x])^2 Cos[x]^14 + 5 (I Sin[x])^14 Cos[x]^2 + 76 (I Sin[x])^4 Cos[x]^12 + 76 (I Sin[x])^12 Cos[x]^4 + 323 (I Sin[x])^6 Cos[x]^10 + 323 (I Sin[x])^10 Cos[x]^6 + 536 (I Sin[x])^8 Cos[x]^8) + Exp[9 I y] (8 (I Sin[x])^3 Cos[x]^13 + 8 (I Sin[x])^13 Cos[x]^3 + 75 (I Sin[x])^11 Cos[x]^5 + 75 (I Sin[x])^5 Cos[x]^11 + 148 (I Sin[x])^9 Cos[x]^7 + 148 (I Sin[x])^7 Cos[x]^9 + 120 (I Sin[x])^10 Cos[x]^6 + 120 (I Sin[x])^6 Cos[x]^10 + 160 (I Sin[x])^8 Cos[x]^8 + 24 (I Sin[x])^4 Cos[x]^12 + 24 (I Sin[x])^12 Cos[x]^4) + Exp[11 I y] (32 (I Sin[x])^10 Cos[x]^6 + 32 (I Sin[x])^6 Cos[x]^10 + 30 (I Sin[x])^8 Cos[x]^8 + 9 (I Sin[x])^4 Cos[x]^12 + 9 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3 + 16 (I Sin[x])^5 Cos[x]^11 + 16 (I Sin[x])^11 Cos[x]^5 + 31 (I Sin[x])^7 Cos[x]^9 + 31 (I Sin[x])^9 Cos[x]^7) + Exp[13 I y] (3 (I Sin[x])^4 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^4 + 4 (I Sin[x])^10 Cos[x]^6 + 4 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^8 Cos[x]^8 + 4 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^5 Cos[x]^11 + 3 (I Sin[x])^9 Cos[x]^7 + 3 (I Sin[x])^7 Cos[x]^9) + Exp[15 I y] (1 (I Sin[x])^11 Cos[x]^5 + 1 (I Sin[x])^5 Cos[x]^11));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":734.6,"max_line_length":5287,"alphanum_fraction":0.5039477267} {"size":10133,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 16;\nname = \"16v1 1 9 4 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^5 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^5) + Exp[-13 I y] (4 (I Sin[x])^6 Cos[x]^10 + 4 (I Sin[x])^10 Cos[x]^6 + 3 (I Sin[x])^5 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^5 + 2 (I Sin[x])^4 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3 + 2 (I Sin[x])^9 Cos[x]^7 + 2 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^8 Cos[x]^8) + Exp[-11 I y] (15 (I Sin[x])^4 Cos[x]^12 + 15 (I Sin[x])^12 Cos[x]^4 + 25 (I Sin[x])^6 Cos[x]^10 + 25 (I Sin[x])^10 Cos[x]^6 + 9 (I Sin[x])^3 Cos[x]^13 + 9 (I Sin[x])^13 Cos[x]^3 + 14 (I Sin[x])^5 Cos[x]^11 + 14 (I Sin[x])^11 Cos[x]^5 + 25 (I Sin[x])^7 Cos[x]^9 + 25 (I Sin[x])^9 Cos[x]^7 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2 + 24 (I Sin[x])^8 Cos[x]^8 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[-9 I y] (79 (I Sin[x])^5 Cos[x]^11 + 79 (I Sin[x])^11 Cos[x]^5 + 122 (I Sin[x])^9 Cos[x]^7 + 122 (I Sin[x])^7 Cos[x]^9 + 58 (I Sin[x])^4 Cos[x]^12 + 58 (I Sin[x])^12 Cos[x]^4 + 96 (I Sin[x])^10 Cos[x]^6 + 96 (I Sin[x])^6 Cos[x]^10 + 124 (I Sin[x])^8 Cos[x]^8 + 28 (I Sin[x])^3 Cos[x]^13 + 28 (I Sin[x])^13 Cos[x]^3 + 8 (I Sin[x])^2 Cos[x]^14 + 8 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[-7 I y] (62 (I Sin[x])^3 Cos[x]^13 + 62 (I Sin[x])^13 Cos[x]^3 + 246 (I Sin[x])^5 Cos[x]^11 + 246 (I Sin[x])^11 Cos[x]^5 + 381 (I Sin[x])^7 Cos[x]^9 + 381 (I Sin[x])^9 Cos[x]^7 + 19 (I Sin[x])^2 Cos[x]^14 + 19 (I Sin[x])^14 Cos[x]^2 + 309 (I Sin[x])^6 Cos[x]^10 + 309 (I Sin[x])^10 Cos[x]^6 + 137 (I Sin[x])^4 Cos[x]^12 + 137 (I Sin[x])^12 Cos[x]^4 + 412 (I Sin[x])^8 Cos[x]^8 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[-5 I y] (248 (I Sin[x])^4 Cos[x]^12 + 248 (I Sin[x])^12 Cos[x]^4 + 982 (I Sin[x])^8 Cos[x]^8 + 754 (I Sin[x])^6 Cos[x]^10 + 754 (I Sin[x])^10 Cos[x]^6 + 504 (I Sin[x])^5 Cos[x]^11 + 504 (I Sin[x])^11 Cos[x]^5 + 901 (I Sin[x])^9 Cos[x]^7 + 901 (I Sin[x])^7 Cos[x]^9 + 86 (I Sin[x])^3 Cos[x]^13 + 86 (I Sin[x])^13 Cos[x]^3 + 19 (I Sin[x])^2 Cos[x]^14 + 19 (I Sin[x])^14 Cos[x]^2) + Exp[-3 I y] (364 (I Sin[x])^4 Cos[x]^12 + 364 (I Sin[x])^12 Cos[x]^4 + 1253 (I Sin[x])^6 Cos[x]^10 + 1253 (I Sin[x])^10 Cos[x]^6 + 1726 (I Sin[x])^8 Cos[x]^8 + 133 (I Sin[x])^3 Cos[x]^13 + 133 (I Sin[x])^13 Cos[x]^3 + 1604 (I Sin[x])^7 Cos[x]^9 + 1604 (I Sin[x])^9 Cos[x]^7 + 739 (I Sin[x])^5 Cos[x]^11 + 739 (I Sin[x])^11 Cos[x]^5 + 40 (I Sin[x])^2 Cos[x]^14 + 40 (I Sin[x])^14 Cos[x]^2 + 9 (I Sin[x])^1 Cos[x]^15 + 9 (I Sin[x])^15 Cos[x]^1) + Exp[-1 I y] (856 (I Sin[x])^5 Cos[x]^11 + 856 (I Sin[x])^11 Cos[x]^5 + 2313 (I Sin[x])^7 Cos[x]^9 + 2313 (I Sin[x])^9 Cos[x]^7 + 1616 (I Sin[x])^6 Cos[x]^10 + 1616 (I Sin[x])^10 Cos[x]^6 + 2532 (I Sin[x])^8 Cos[x]^8 + 318 (I Sin[x])^4 Cos[x]^12 + 318 (I Sin[x])^12 Cos[x]^4 + 66 (I Sin[x])^3 Cos[x]^13 + 66 (I Sin[x])^13 Cos[x]^3) + Exp[1 I y] (863 (I Sin[x])^5 Cos[x]^11 + 863 (I Sin[x])^11 Cos[x]^5 + 2238 (I Sin[x])^7 Cos[x]^9 + 2238 (I Sin[x])^9 Cos[x]^7 + 374 (I Sin[x])^4 Cos[x]^12 + 374 (I Sin[x])^12 Cos[x]^4 + 2548 (I Sin[x])^8 Cos[x]^8 + 1523 (I Sin[x])^6 Cos[x]^10 + 1523 (I Sin[x])^10 Cos[x]^6 + 134 (I Sin[x])^3 Cos[x]^13 + 134 (I Sin[x])^13 Cos[x]^3 + 29 (I Sin[x])^2 Cos[x]^14 + 29 (I Sin[x])^14 Cos[x]^2) + Exp[3 I y] (1223 (I Sin[x])^6 Cos[x]^10 + 1223 (I Sin[x])^10 Cos[x]^6 + 2390 (I Sin[x])^8 Cos[x]^8 + 1992 (I Sin[x])^7 Cos[x]^9 + 1992 (I Sin[x])^9 Cos[x]^7 + 493 (I Sin[x])^5 Cos[x]^11 + 493 (I Sin[x])^11 Cos[x]^5 + 102 (I Sin[x])^4 Cos[x]^12 + 102 (I Sin[x])^12 Cos[x]^4) + Exp[5 I y] (751 (I Sin[x])^6 Cos[x]^10 + 751 (I Sin[x])^10 Cos[x]^6 + 1160 (I Sin[x])^8 Cos[x]^8 + 415 (I Sin[x])^5 Cos[x]^11 + 415 (I Sin[x])^11 Cos[x]^5 + 1036 (I Sin[x])^9 Cos[x]^7 + 1036 (I Sin[x])^7 Cos[x]^9 + 181 (I Sin[x])^4 Cos[x]^12 + 181 (I Sin[x])^12 Cos[x]^4 + 40 (I Sin[x])^3 Cos[x]^13 + 40 (I Sin[x])^13 Cos[x]^3) + Exp[7 I y] (626 (I Sin[x])^7 Cos[x]^9 + 626 (I Sin[x])^9 Cos[x]^7 + 67 (I Sin[x])^5 Cos[x]^11 + 67 (I Sin[x])^11 Cos[x]^5 + 752 (I Sin[x])^8 Cos[x]^8 + 296 (I Sin[x])^6 Cos[x]^10 + 296 (I Sin[x])^10 Cos[x]^6) + Exp[9 I y] (145 (I Sin[x])^7 Cos[x]^9 + 145 (I Sin[x])^9 Cos[x]^7 + 136 (I Sin[x])^6 Cos[x]^10 + 136 (I Sin[x])^10 Cos[x]^6 + 134 (I Sin[x])^8 Cos[x]^8 + 86 (I Sin[x])^5 Cos[x]^11 + 86 (I Sin[x])^11 Cos[x]^5 + 21 (I Sin[x])^4 Cos[x]^12 + 21 (I Sin[x])^12 Cos[x]^4) + Exp[11 I y] (82 (I Sin[x])^8 Cos[x]^8 + 15 (I Sin[x])^6 Cos[x]^10 + 15 (I Sin[x])^10 Cos[x]^6 + 49 (I Sin[x])^9 Cos[x]^7 + 49 (I Sin[x])^7 Cos[x]^9) + Exp[13 I y] (2 (I Sin[x])^8 Cos[x]^8 + 7 (I Sin[x])^6 Cos[x]^10 + 7 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^5 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^5 + 5 (I Sin[x])^7 Cos[x]^9 + 5 (I Sin[x])^9 Cos[x]^7) + Exp[15 I y] (1 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^7))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^5 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^5) + Exp[-13 I y] (4 (I Sin[x])^6 Cos[x]^10 + 4 (I Sin[x])^10 Cos[x]^6 + 3 (I Sin[x])^5 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^5 + 2 (I Sin[x])^4 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3 + 2 (I Sin[x])^9 Cos[x]^7 + 2 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^8 Cos[x]^8) + Exp[-11 I y] (15 (I Sin[x])^4 Cos[x]^12 + 15 (I Sin[x])^12 Cos[x]^4 + 25 (I Sin[x])^6 Cos[x]^10 + 25 (I Sin[x])^10 Cos[x]^6 + 9 (I Sin[x])^3 Cos[x]^13 + 9 (I Sin[x])^13 Cos[x]^3 + 14 (I Sin[x])^5 Cos[x]^11 + 14 (I Sin[x])^11 Cos[x]^5 + 25 (I Sin[x])^7 Cos[x]^9 + 25 (I Sin[x])^9 Cos[x]^7 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2 + 24 (I Sin[x])^8 Cos[x]^8 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[-9 I y] (79 (I Sin[x])^5 Cos[x]^11 + 79 (I Sin[x])^11 Cos[x]^5 + 122 (I Sin[x])^9 Cos[x]^7 + 122 (I Sin[x])^7 Cos[x]^9 + 58 (I Sin[x])^4 Cos[x]^12 + 58 (I Sin[x])^12 Cos[x]^4 + 96 (I Sin[x])^10 Cos[x]^6 + 96 (I Sin[x])^6 Cos[x]^10 + 124 (I Sin[x])^8 Cos[x]^8 + 28 (I Sin[x])^3 Cos[x]^13 + 28 (I Sin[x])^13 Cos[x]^3 + 8 (I Sin[x])^2 Cos[x]^14 + 8 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[-7 I y] (62 (I Sin[x])^3 Cos[x]^13 + 62 (I Sin[x])^13 Cos[x]^3 + 246 (I Sin[x])^5 Cos[x]^11 + 246 (I Sin[x])^11 Cos[x]^5 + 381 (I Sin[x])^7 Cos[x]^9 + 381 (I Sin[x])^9 Cos[x]^7 + 19 (I Sin[x])^2 Cos[x]^14 + 19 (I Sin[x])^14 Cos[x]^2 + 309 (I Sin[x])^6 Cos[x]^10 + 309 (I Sin[x])^10 Cos[x]^6 + 137 (I Sin[x])^4 Cos[x]^12 + 137 (I Sin[x])^12 Cos[x]^4 + 412 (I Sin[x])^8 Cos[x]^8 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[-5 I y] (248 (I Sin[x])^4 Cos[x]^12 + 248 (I Sin[x])^12 Cos[x]^4 + 982 (I Sin[x])^8 Cos[x]^8 + 754 (I Sin[x])^6 Cos[x]^10 + 754 (I Sin[x])^10 Cos[x]^6 + 504 (I Sin[x])^5 Cos[x]^11 + 504 (I Sin[x])^11 Cos[x]^5 + 901 (I Sin[x])^9 Cos[x]^7 + 901 (I Sin[x])^7 Cos[x]^9 + 86 (I Sin[x])^3 Cos[x]^13 + 86 (I Sin[x])^13 Cos[x]^3 + 19 (I Sin[x])^2 Cos[x]^14 + 19 (I Sin[x])^14 Cos[x]^2) + Exp[-3 I y] (364 (I Sin[x])^4 Cos[x]^12 + 364 (I Sin[x])^12 Cos[x]^4 + 1253 (I Sin[x])^6 Cos[x]^10 + 1253 (I Sin[x])^10 Cos[x]^6 + 1726 (I Sin[x])^8 Cos[x]^8 + 133 (I Sin[x])^3 Cos[x]^13 + 133 (I Sin[x])^13 Cos[x]^3 + 1604 (I Sin[x])^7 Cos[x]^9 + 1604 (I Sin[x])^9 Cos[x]^7 + 739 (I Sin[x])^5 Cos[x]^11 + 739 (I Sin[x])^11 Cos[x]^5 + 40 (I Sin[x])^2 Cos[x]^14 + 40 (I Sin[x])^14 Cos[x]^2 + 9 (I Sin[x])^1 Cos[x]^15 + 9 (I Sin[x])^15 Cos[x]^1) + Exp[-1 I y] (856 (I Sin[x])^5 Cos[x]^11 + 856 (I Sin[x])^11 Cos[x]^5 + 2313 (I Sin[x])^7 Cos[x]^9 + 2313 (I Sin[x])^9 Cos[x]^7 + 1616 (I Sin[x])^6 Cos[x]^10 + 1616 (I Sin[x])^10 Cos[x]^6 + 2532 (I Sin[x])^8 Cos[x]^8 + 318 (I Sin[x])^4 Cos[x]^12 + 318 (I Sin[x])^12 Cos[x]^4 + 66 (I Sin[x])^3 Cos[x]^13 + 66 (I Sin[x])^13 Cos[x]^3) + Exp[1 I y] (863 (I Sin[x])^5 Cos[x]^11 + 863 (I Sin[x])^11 Cos[x]^5 + 2238 (I Sin[x])^7 Cos[x]^9 + 2238 (I Sin[x])^9 Cos[x]^7 + 374 (I Sin[x])^4 Cos[x]^12 + 374 (I Sin[x])^12 Cos[x]^4 + 2548 (I Sin[x])^8 Cos[x]^8 + 1523 (I Sin[x])^6 Cos[x]^10 + 1523 (I Sin[x])^10 Cos[x]^6 + 134 (I Sin[x])^3 Cos[x]^13 + 134 (I Sin[x])^13 Cos[x]^3 + 29 (I Sin[x])^2 Cos[x]^14 + 29 (I Sin[x])^14 Cos[x]^2) + Exp[3 I y] (1223 (I Sin[x])^6 Cos[x]^10 + 1223 (I Sin[x])^10 Cos[x]^6 + 2390 (I Sin[x])^8 Cos[x]^8 + 1992 (I Sin[x])^7 Cos[x]^9 + 1992 (I Sin[x])^9 Cos[x]^7 + 493 (I Sin[x])^5 Cos[x]^11 + 493 (I Sin[x])^11 Cos[x]^5 + 102 (I Sin[x])^4 Cos[x]^12 + 102 (I Sin[x])^12 Cos[x]^4) + Exp[5 I y] (751 (I Sin[x])^6 Cos[x]^10 + 751 (I Sin[x])^10 Cos[x]^6 + 1160 (I Sin[x])^8 Cos[x]^8 + 415 (I Sin[x])^5 Cos[x]^11 + 415 (I Sin[x])^11 Cos[x]^5 + 1036 (I Sin[x])^9 Cos[x]^7 + 1036 (I Sin[x])^7 Cos[x]^9 + 181 (I Sin[x])^4 Cos[x]^12 + 181 (I Sin[x])^12 Cos[x]^4 + 40 (I Sin[x])^3 Cos[x]^13 + 40 (I Sin[x])^13 Cos[x]^3) + Exp[7 I y] (626 (I Sin[x])^7 Cos[x]^9 + 626 (I Sin[x])^9 Cos[x]^7 + 67 (I Sin[x])^5 Cos[x]^11 + 67 (I Sin[x])^11 Cos[x]^5 + 752 (I Sin[x])^8 Cos[x]^8 + 296 (I Sin[x])^6 Cos[x]^10 + 296 (I Sin[x])^10 Cos[x]^6) + Exp[9 I y] (145 (I Sin[x])^7 Cos[x]^9 + 145 (I Sin[x])^9 Cos[x]^7 + 136 (I Sin[x])^6 Cos[x]^10 + 136 (I Sin[x])^10 Cos[x]^6 + 134 (I Sin[x])^8 Cos[x]^8 + 86 (I Sin[x])^5 Cos[x]^11 + 86 (I Sin[x])^11 Cos[x]^5 + 21 (I Sin[x])^4 Cos[x]^12 + 21 (I Sin[x])^12 Cos[x]^4) + Exp[11 I y] (82 (I Sin[x])^8 Cos[x]^8 + 15 (I Sin[x])^6 Cos[x]^10 + 15 (I Sin[x])^10 Cos[x]^6 + 49 (I Sin[x])^9 Cos[x]^7 + 49 (I Sin[x])^7 Cos[x]^9) + Exp[13 I y] (2 (I Sin[x])^8 Cos[x]^8 + 7 (I Sin[x])^6 Cos[x]^10 + 7 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^5 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^5 + 5 (I Sin[x])^7 Cos[x]^9 + 5 (I Sin[x])^9 Cos[x]^7) + Exp[15 I y] (1 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^7));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":675.5333333333,"max_line_length":4847,"alphanum_fraction":0.505082404} {"size":11131,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 16;\nname = \"16v2 3 1 4 2 1 1 1 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^9 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^9) + Exp[-13 I y] (6 (I Sin[x])^10 Cos[x]^6 + 6 (I Sin[x])^6 Cos[x]^10 + 5 (I Sin[x])^9 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^9 + 2 (I Sin[x])^5 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^8 Cos[x]^8) + Exp[-11 I y] (44 (I Sin[x])^8 Cos[x]^8 + 28 (I Sin[x])^10 Cos[x]^6 + 28 (I Sin[x])^6 Cos[x]^10 + 33 (I Sin[x])^9 Cos[x]^7 + 33 (I Sin[x])^7 Cos[x]^9 + 15 (I Sin[x])^11 Cos[x]^5 + 15 (I Sin[x])^5 Cos[x]^11 + 6 (I Sin[x])^4 Cos[x]^12 + 6 (I Sin[x])^12 Cos[x]^4 + 1 (I Sin[x])^3 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^3) + Exp[-9 I y] (55 (I Sin[x])^11 Cos[x]^5 + 55 (I Sin[x])^5 Cos[x]^11 + 174 (I Sin[x])^7 Cos[x]^9 + 174 (I Sin[x])^9 Cos[x]^7 + 204 (I Sin[x])^8 Cos[x]^8 + 104 (I Sin[x])^6 Cos[x]^10 + 104 (I Sin[x])^10 Cos[x]^6 + 18 (I Sin[x])^4 Cos[x]^12 + 18 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3) + Exp[-7 I y] (483 (I Sin[x])^7 Cos[x]^9 + 483 (I Sin[x])^9 Cos[x]^7 + 185 (I Sin[x])^11 Cos[x]^5 + 185 (I Sin[x])^5 Cos[x]^11 + 328 (I Sin[x])^10 Cos[x]^6 + 328 (I Sin[x])^6 Cos[x]^10 + 524 (I Sin[x])^8 Cos[x]^8 + 78 (I Sin[x])^12 Cos[x]^4 + 78 (I Sin[x])^4 Cos[x]^12 + 25 (I Sin[x])^3 Cos[x]^13 + 25 (I Sin[x])^13 Cos[x]^3 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2) + Exp[-5 I y] (125 (I Sin[x])^12 Cos[x]^4 + 125 (I Sin[x])^4 Cos[x]^12 + 1250 (I Sin[x])^8 Cos[x]^8 + 759 (I Sin[x])^6 Cos[x]^10 + 759 (I Sin[x])^10 Cos[x]^6 + 1103 (I Sin[x])^9 Cos[x]^7 + 1103 (I Sin[x])^7 Cos[x]^9 + 358 (I Sin[x])^5 Cos[x]^11 + 358 (I Sin[x])^11 Cos[x]^5 + 30 (I Sin[x])^13 Cos[x]^3 + 30 (I Sin[x])^3 Cos[x]^13 + 3 (I Sin[x])^2 Cos[x]^14 + 3 (I Sin[x])^14 Cos[x]^2) + Exp[-3 I y] (1818 (I Sin[x])^8 Cos[x]^8 + 1240 (I Sin[x])^10 Cos[x]^6 + 1240 (I Sin[x])^6 Cos[x]^10 + 1631 (I Sin[x])^9 Cos[x]^7 + 1631 (I Sin[x])^7 Cos[x]^9 + 736 (I Sin[x])^11 Cos[x]^5 + 736 (I Sin[x])^5 Cos[x]^11 + 343 (I Sin[x])^4 Cos[x]^12 + 343 (I Sin[x])^12 Cos[x]^4 + 114 (I Sin[x])^3 Cos[x]^13 + 114 (I Sin[x])^13 Cos[x]^3 + 28 (I Sin[x])^2 Cos[x]^14 + 28 (I Sin[x])^14 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[-1 I y] (780 (I Sin[x])^11 Cos[x]^5 + 780 (I Sin[x])^5 Cos[x]^11 + 2383 (I Sin[x])^9 Cos[x]^7 + 2383 (I Sin[x])^7 Cos[x]^9 + 2752 (I Sin[x])^8 Cos[x]^8 + 1531 (I Sin[x])^6 Cos[x]^10 + 1531 (I Sin[x])^10 Cos[x]^6 + 280 (I Sin[x])^12 Cos[x]^4 + 280 (I Sin[x])^4 Cos[x]^12 + 71 (I Sin[x])^13 Cos[x]^3 + 71 (I Sin[x])^3 Cos[x]^13 + 13 (I Sin[x])^14 Cos[x]^2 + 13 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[1 I y] (2156 (I Sin[x])^7 Cos[x]^9 + 2156 (I Sin[x])^9 Cos[x]^7 + 921 (I Sin[x])^5 Cos[x]^11 + 921 (I Sin[x])^11 Cos[x]^5 + 2362 (I Sin[x])^8 Cos[x]^8 + 1562 (I Sin[x])^6 Cos[x]^10 + 1562 (I Sin[x])^10 Cos[x]^6 + 418 (I Sin[x])^4 Cos[x]^12 + 418 (I Sin[x])^12 Cos[x]^4 + 151 (I Sin[x])^3 Cos[x]^13 + 151 (I Sin[x])^13 Cos[x]^3 + 38 (I Sin[x])^2 Cos[x]^14 + 38 (I Sin[x])^14 Cos[x]^2 + 7 (I Sin[x])^1 Cos[x]^15 + 7 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[3 I y] (1241 (I Sin[x])^10 Cos[x]^6 + 1241 (I Sin[x])^6 Cos[x]^10 + 2088 (I Sin[x])^8 Cos[x]^8 + 1830 (I Sin[x])^7 Cos[x]^9 + 1830 (I Sin[x])^9 Cos[x]^7 + 595 (I Sin[x])^11 Cos[x]^5 + 595 (I Sin[x])^5 Cos[x]^11 + 226 (I Sin[x])^12 Cos[x]^4 + 226 (I Sin[x])^4 Cos[x]^12 + 59 (I Sin[x])^13 Cos[x]^3 + 59 (I Sin[x])^3 Cos[x]^13 + 9 (I Sin[x])^2 Cos[x]^14 + 9 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^15 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^15) + Exp[5 I y] (728 (I Sin[x])^6 Cos[x]^10 + 728 (I Sin[x])^10 Cos[x]^6 + 1108 (I Sin[x])^8 Cos[x]^8 + 984 (I Sin[x])^9 Cos[x]^7 + 984 (I Sin[x])^7 Cos[x]^9 + 210 (I Sin[x])^4 Cos[x]^12 + 210 (I Sin[x])^12 Cos[x]^4 + 430 (I Sin[x])^5 Cos[x]^11 + 430 (I Sin[x])^11 Cos[x]^5 + 74 (I Sin[x])^3 Cos[x]^13 + 74 (I Sin[x])^13 Cos[x]^3 + 20 (I Sin[x])^2 Cos[x]^14 + 20 (I Sin[x])^14 Cos[x]^2 + 3 (I Sin[x])^1 Cos[x]^15 + 3 (I Sin[x])^15 Cos[x]^1) + Exp[7 I y] (197 (I Sin[x])^11 Cos[x]^5 + 197 (I Sin[x])^5 Cos[x]^11 + 478 (I Sin[x])^9 Cos[x]^7 + 478 (I Sin[x])^7 Cos[x]^9 + 333 (I Sin[x])^6 Cos[x]^10 + 333 (I Sin[x])^10 Cos[x]^6 + 532 (I Sin[x])^8 Cos[x]^8 + 70 (I Sin[x])^12 Cos[x]^4 + 70 (I Sin[x])^4 Cos[x]^12 + 18 (I Sin[x])^3 Cos[x]^13 + 18 (I Sin[x])^13 Cos[x]^3 + 3 (I Sin[x])^14 Cos[x]^2 + 3 (I Sin[x])^2 Cos[x]^14) + Exp[9 I y] (77 (I Sin[x])^5 Cos[x]^11 + 77 (I Sin[x])^11 Cos[x]^5 + 141 (I Sin[x])^9 Cos[x]^7 + 141 (I Sin[x])^7 Cos[x]^9 + 144 (I Sin[x])^8 Cos[x]^8 + 114 (I Sin[x])^6 Cos[x]^10 + 114 (I Sin[x])^10 Cos[x]^6 + 36 (I Sin[x])^4 Cos[x]^12 + 36 (I Sin[x])^12 Cos[x]^4 + 13 (I Sin[x])^3 Cos[x]^13 + 13 (I Sin[x])^13 Cos[x]^3 + 2 (I Sin[x])^2 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^2) + Exp[11 I y] (30 (I Sin[x])^10 Cos[x]^6 + 30 (I Sin[x])^6 Cos[x]^10 + 34 (I Sin[x])^8 Cos[x]^8 + 14 (I Sin[x])^5 Cos[x]^11 + 14 (I Sin[x])^11 Cos[x]^5 + 33 (I Sin[x])^7 Cos[x]^9 + 33 (I Sin[x])^9 Cos[x]^7 + 9 (I Sin[x])^12 Cos[x]^4 + 9 (I Sin[x])^4 Cos[x]^12 + 2 (I Sin[x])^13 Cos[x]^3 + 2 (I Sin[x])^3 Cos[x]^13) + Exp[13 I y] (1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4 + 4 (I Sin[x])^10 Cos[x]^6 + 4 (I Sin[x])^6 Cos[x]^10 + 6 (I Sin[x])^8 Cos[x]^8 + 5 (I Sin[x])^9 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^9 + 2 (I Sin[x])^5 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^5) + Exp[15 I y] (1 (I Sin[x])^11 Cos[x]^5 + 1 (I Sin[x])^5 Cos[x]^11))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^9 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^9) + Exp[-13 I y] (6 (I Sin[x])^10 Cos[x]^6 + 6 (I Sin[x])^6 Cos[x]^10 + 5 (I Sin[x])^9 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^9 + 2 (I Sin[x])^5 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^8 Cos[x]^8) + Exp[-11 I y] (44 (I Sin[x])^8 Cos[x]^8 + 28 (I Sin[x])^10 Cos[x]^6 + 28 (I Sin[x])^6 Cos[x]^10 + 33 (I Sin[x])^9 Cos[x]^7 + 33 (I Sin[x])^7 Cos[x]^9 + 15 (I Sin[x])^11 Cos[x]^5 + 15 (I Sin[x])^5 Cos[x]^11 + 6 (I Sin[x])^4 Cos[x]^12 + 6 (I Sin[x])^12 Cos[x]^4 + 1 (I Sin[x])^3 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^3) + Exp[-9 I y] (55 (I Sin[x])^11 Cos[x]^5 + 55 (I Sin[x])^5 Cos[x]^11 + 174 (I Sin[x])^7 Cos[x]^9 + 174 (I Sin[x])^9 Cos[x]^7 + 204 (I Sin[x])^8 Cos[x]^8 + 104 (I Sin[x])^6 Cos[x]^10 + 104 (I Sin[x])^10 Cos[x]^6 + 18 (I Sin[x])^4 Cos[x]^12 + 18 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3) + Exp[-7 I y] (483 (I Sin[x])^7 Cos[x]^9 + 483 (I Sin[x])^9 Cos[x]^7 + 185 (I Sin[x])^11 Cos[x]^5 + 185 (I Sin[x])^5 Cos[x]^11 + 328 (I Sin[x])^10 Cos[x]^6 + 328 (I Sin[x])^6 Cos[x]^10 + 524 (I Sin[x])^8 Cos[x]^8 + 78 (I Sin[x])^12 Cos[x]^4 + 78 (I Sin[x])^4 Cos[x]^12 + 25 (I Sin[x])^3 Cos[x]^13 + 25 (I Sin[x])^13 Cos[x]^3 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2) + Exp[-5 I y] (125 (I Sin[x])^12 Cos[x]^4 + 125 (I Sin[x])^4 Cos[x]^12 + 1250 (I Sin[x])^8 Cos[x]^8 + 759 (I Sin[x])^6 Cos[x]^10 + 759 (I Sin[x])^10 Cos[x]^6 + 1103 (I Sin[x])^9 Cos[x]^7 + 1103 (I Sin[x])^7 Cos[x]^9 + 358 (I Sin[x])^5 Cos[x]^11 + 358 (I Sin[x])^11 Cos[x]^5 + 30 (I Sin[x])^13 Cos[x]^3 + 30 (I Sin[x])^3 Cos[x]^13 + 3 (I Sin[x])^2 Cos[x]^14 + 3 (I Sin[x])^14 Cos[x]^2) + Exp[-3 I y] (1818 (I Sin[x])^8 Cos[x]^8 + 1240 (I Sin[x])^10 Cos[x]^6 + 1240 (I Sin[x])^6 Cos[x]^10 + 1631 (I Sin[x])^9 Cos[x]^7 + 1631 (I Sin[x])^7 Cos[x]^9 + 736 (I Sin[x])^11 Cos[x]^5 + 736 (I Sin[x])^5 Cos[x]^11 + 343 (I Sin[x])^4 Cos[x]^12 + 343 (I Sin[x])^12 Cos[x]^4 + 114 (I Sin[x])^3 Cos[x]^13 + 114 (I Sin[x])^13 Cos[x]^3 + 28 (I Sin[x])^2 Cos[x]^14 + 28 (I Sin[x])^14 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[-1 I y] (780 (I Sin[x])^11 Cos[x]^5 + 780 (I Sin[x])^5 Cos[x]^11 + 2383 (I Sin[x])^9 Cos[x]^7 + 2383 (I Sin[x])^7 Cos[x]^9 + 2752 (I Sin[x])^8 Cos[x]^8 + 1531 (I Sin[x])^6 Cos[x]^10 + 1531 (I Sin[x])^10 Cos[x]^6 + 280 (I Sin[x])^12 Cos[x]^4 + 280 (I Sin[x])^4 Cos[x]^12 + 71 (I Sin[x])^13 Cos[x]^3 + 71 (I Sin[x])^3 Cos[x]^13 + 13 (I Sin[x])^14 Cos[x]^2 + 13 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[1 I y] (2156 (I Sin[x])^7 Cos[x]^9 + 2156 (I Sin[x])^9 Cos[x]^7 + 921 (I Sin[x])^5 Cos[x]^11 + 921 (I Sin[x])^11 Cos[x]^5 + 2362 (I Sin[x])^8 Cos[x]^8 + 1562 (I Sin[x])^6 Cos[x]^10 + 1562 (I Sin[x])^10 Cos[x]^6 + 418 (I Sin[x])^4 Cos[x]^12 + 418 (I Sin[x])^12 Cos[x]^4 + 151 (I Sin[x])^3 Cos[x]^13 + 151 (I Sin[x])^13 Cos[x]^3 + 38 (I Sin[x])^2 Cos[x]^14 + 38 (I Sin[x])^14 Cos[x]^2 + 7 (I Sin[x])^1 Cos[x]^15 + 7 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[3 I y] (1241 (I Sin[x])^10 Cos[x]^6 + 1241 (I Sin[x])^6 Cos[x]^10 + 2088 (I Sin[x])^8 Cos[x]^8 + 1830 (I Sin[x])^7 Cos[x]^9 + 1830 (I Sin[x])^9 Cos[x]^7 + 595 (I Sin[x])^11 Cos[x]^5 + 595 (I Sin[x])^5 Cos[x]^11 + 226 (I Sin[x])^12 Cos[x]^4 + 226 (I Sin[x])^4 Cos[x]^12 + 59 (I Sin[x])^13 Cos[x]^3 + 59 (I Sin[x])^3 Cos[x]^13 + 9 (I Sin[x])^2 Cos[x]^14 + 9 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^15 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^15) + Exp[5 I y] (728 (I Sin[x])^6 Cos[x]^10 + 728 (I Sin[x])^10 Cos[x]^6 + 1108 (I Sin[x])^8 Cos[x]^8 + 984 (I Sin[x])^9 Cos[x]^7 + 984 (I Sin[x])^7 Cos[x]^9 + 210 (I Sin[x])^4 Cos[x]^12 + 210 (I Sin[x])^12 Cos[x]^4 + 430 (I Sin[x])^5 Cos[x]^11 + 430 (I Sin[x])^11 Cos[x]^5 + 74 (I Sin[x])^3 Cos[x]^13 + 74 (I Sin[x])^13 Cos[x]^3 + 20 (I Sin[x])^2 Cos[x]^14 + 20 (I Sin[x])^14 Cos[x]^2 + 3 (I Sin[x])^1 Cos[x]^15 + 3 (I Sin[x])^15 Cos[x]^1) + Exp[7 I y] (197 (I Sin[x])^11 Cos[x]^5 + 197 (I Sin[x])^5 Cos[x]^11 + 478 (I Sin[x])^9 Cos[x]^7 + 478 (I Sin[x])^7 Cos[x]^9 + 333 (I Sin[x])^6 Cos[x]^10 + 333 (I Sin[x])^10 Cos[x]^6 + 532 (I Sin[x])^8 Cos[x]^8 + 70 (I Sin[x])^12 Cos[x]^4 + 70 (I Sin[x])^4 Cos[x]^12 + 18 (I Sin[x])^3 Cos[x]^13 + 18 (I Sin[x])^13 Cos[x]^3 + 3 (I Sin[x])^14 Cos[x]^2 + 3 (I Sin[x])^2 Cos[x]^14) + Exp[9 I y] (77 (I Sin[x])^5 Cos[x]^11 + 77 (I Sin[x])^11 Cos[x]^5 + 141 (I Sin[x])^9 Cos[x]^7 + 141 (I Sin[x])^7 Cos[x]^9 + 144 (I Sin[x])^8 Cos[x]^8 + 114 (I Sin[x])^6 Cos[x]^10 + 114 (I Sin[x])^10 Cos[x]^6 + 36 (I Sin[x])^4 Cos[x]^12 + 36 (I Sin[x])^12 Cos[x]^4 + 13 (I Sin[x])^3 Cos[x]^13 + 13 (I Sin[x])^13 Cos[x]^3 + 2 (I Sin[x])^2 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^2) + Exp[11 I y] (30 (I Sin[x])^10 Cos[x]^6 + 30 (I Sin[x])^6 Cos[x]^10 + 34 (I Sin[x])^8 Cos[x]^8 + 14 (I Sin[x])^5 Cos[x]^11 + 14 (I Sin[x])^11 Cos[x]^5 + 33 (I Sin[x])^7 Cos[x]^9 + 33 (I Sin[x])^9 Cos[x]^7 + 9 (I Sin[x])^12 Cos[x]^4 + 9 (I Sin[x])^4 Cos[x]^12 + 2 (I Sin[x])^13 Cos[x]^3 + 2 (I Sin[x])^3 Cos[x]^13) + Exp[13 I y] (1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4 + 4 (I Sin[x])^10 Cos[x]^6 + 4 (I Sin[x])^6 Cos[x]^10 + 6 (I Sin[x])^8 Cos[x]^8 + 5 (I Sin[x])^9 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^9 + 2 (I Sin[x])^5 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^5) + Exp[15 I y] (1 (I Sin[x])^11 Cos[x]^5 + 1 (I Sin[x])^5 Cos[x]^11));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":742.0666666667,"max_line_length":5342,"alphanum_fraction":0.5038181655} {"size":7967,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 14;\nname = \"14v2 2 2 3 1 1 2 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-13 I y] (2 (I Sin[x])^7 Cos[x]^7) + Exp[-11 I y] (7 (I Sin[x])^6 Cos[x]^8 + 7 (I Sin[x])^8 Cos[x]^6 + 8 (I Sin[x])^7 Cos[x]^7 + 2 (I Sin[x])^5 Cos[x]^9 + 2 (I Sin[x])^9 Cos[x]^5) + Exp[-9 I y] (38 (I Sin[x])^8 Cos[x]^6 + 38 (I Sin[x])^6 Cos[x]^8 + 18 (I Sin[x])^9 Cos[x]^5 + 18 (I Sin[x])^5 Cos[x]^9 + 36 (I Sin[x])^7 Cos[x]^7 + 4 (I Sin[x])^4 Cos[x]^10 + 4 (I Sin[x])^10 Cos[x]^4) + Exp[-7 I y] (138 (I Sin[x])^7 Cos[x]^7 + 72 (I Sin[x])^5 Cos[x]^9 + 72 (I Sin[x])^9 Cos[x]^5 + 111 (I Sin[x])^6 Cos[x]^8 + 111 (I Sin[x])^8 Cos[x]^6 + 29 (I Sin[x])^4 Cos[x]^10 + 29 (I Sin[x])^10 Cos[x]^4 + 5 (I Sin[x])^3 Cos[x]^11 + 5 (I Sin[x])^11 Cos[x]^3) + Exp[-5 I y] (356 (I Sin[x])^7 Cos[x]^7 + 168 (I Sin[x])^9 Cos[x]^5 + 168 (I Sin[x])^5 Cos[x]^9 + 71 (I Sin[x])^10 Cos[x]^4 + 71 (I Sin[x])^4 Cos[x]^10 + 277 (I Sin[x])^8 Cos[x]^6 + 277 (I Sin[x])^6 Cos[x]^8 + 19 (I Sin[x])^3 Cos[x]^11 + 19 (I Sin[x])^11 Cos[x]^3 + 2 (I Sin[x])^2 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^2) + Exp[-3 I y] (451 (I Sin[x])^8 Cos[x]^6 + 451 (I Sin[x])^6 Cos[x]^8 + 180 (I Sin[x])^4 Cos[x]^10 + 180 (I Sin[x])^10 Cos[x]^4 + 318 (I Sin[x])^5 Cos[x]^9 + 318 (I Sin[x])^9 Cos[x]^5 + 478 (I Sin[x])^7 Cos[x]^7 + 77 (I Sin[x])^3 Cos[x]^11 + 77 (I Sin[x])^11 Cos[x]^3 + 20 (I Sin[x])^2 Cos[x]^12 + 20 (I Sin[x])^12 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^1) + Exp[-1 I y] (666 (I Sin[x])^6 Cos[x]^8 + 666 (I Sin[x])^8 Cos[x]^6 + 423 (I Sin[x])^9 Cos[x]^5 + 423 (I Sin[x])^5 Cos[x]^9 + 734 (I Sin[x])^7 Cos[x]^7 + 191 (I Sin[x])^4 Cos[x]^10 + 191 (I Sin[x])^10 Cos[x]^4 + 57 (I Sin[x])^11 Cos[x]^3 + 57 (I Sin[x])^3 Cos[x]^11 + 11 (I Sin[x])^12 Cos[x]^2 + 11 (I Sin[x])^2 Cos[x]^12 + 1 (I Sin[x])^1 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^1) + Exp[1 I y] (642 (I Sin[x])^7 Cos[x]^7 + 427 (I Sin[x])^5 Cos[x]^9 + 427 (I Sin[x])^9 Cos[x]^5 + 111 (I Sin[x])^3 Cos[x]^11 + 111 (I Sin[x])^11 Cos[x]^3 + 253 (I Sin[x])^4 Cos[x]^10 + 253 (I Sin[x])^10 Cos[x]^4 + 557 (I Sin[x])^6 Cos[x]^8 + 557 (I Sin[x])^8 Cos[x]^6 + 37 (I Sin[x])^2 Cos[x]^12 + 37 (I Sin[x])^12 Cos[x]^2 + 9 (I Sin[x])^1 Cos[x]^13 + 9 (I Sin[x])^13 Cos[x]^1 + 1 Cos[x]^14 + 1 (I Sin[x])^14) + Exp[3 I y] (307 (I Sin[x])^5 Cos[x]^9 + 307 (I Sin[x])^9 Cos[x]^5 + 592 (I Sin[x])^7 Cos[x]^7 + 140 (I Sin[x])^10 Cos[x]^4 + 140 (I Sin[x])^4 Cos[x]^10 + 486 (I Sin[x])^6 Cos[x]^8 + 486 (I Sin[x])^8 Cos[x]^6 + 47 (I Sin[x])^11 Cos[x]^3 + 47 (I Sin[x])^3 Cos[x]^11 + 10 (I Sin[x])^2 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^2 + 1 (I Sin[x])^13 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^13) + Exp[5 I y] (265 (I Sin[x])^8 Cos[x]^6 + 265 (I Sin[x])^6 Cos[x]^8 + 90 (I Sin[x])^4 Cos[x]^10 + 90 (I Sin[x])^10 Cos[x]^4 + 173 (I Sin[x])^5 Cos[x]^9 + 173 (I Sin[x])^9 Cos[x]^5 + 278 (I Sin[x])^7 Cos[x]^7 + 10 (I Sin[x])^2 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^2 + 37 (I Sin[x])^3 Cos[x]^11 + 37 (I Sin[x])^11 Cos[x]^3 + 1 (I Sin[x])^1 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^1) + Exp[7 I y] (112 (I Sin[x])^6 Cos[x]^8 + 112 (I Sin[x])^8 Cos[x]^6 + 33 (I Sin[x])^4 Cos[x]^10 + 33 (I Sin[x])^10 Cos[x]^4 + 70 (I Sin[x])^9 Cos[x]^5 + 70 (I Sin[x])^5 Cos[x]^9 + 122 (I Sin[x])^7 Cos[x]^7 + 9 (I Sin[x])^11 Cos[x]^3 + 9 (I Sin[x])^3 Cos[x]^11 + 1 (I Sin[x])^12 Cos[x]^2 + 1 (I Sin[x])^2 Cos[x]^12) + Exp[9 I y] (40 (I Sin[x])^7 Cos[x]^7 + 20 (I Sin[x])^9 Cos[x]^5 + 20 (I Sin[x])^5 Cos[x]^9 + 2 (I Sin[x])^3 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^3 + 9 (I Sin[x])^4 Cos[x]^10 + 9 (I Sin[x])^10 Cos[x]^4 + 27 (I Sin[x])^6 Cos[x]^8 + 27 (I Sin[x])^8 Cos[x]^6) + Exp[11 I y] (4 (I Sin[x])^5 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^5 + 6 (I Sin[x])^7 Cos[x]^7 + 1 (I Sin[x])^10 Cos[x]^4 + 1 (I Sin[x])^4 Cos[x]^10 + 5 (I Sin[x])^6 Cos[x]^8 + 5 (I Sin[x])^8 Cos[x]^6) + Exp[13 I y] (1 (I Sin[x])^8 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^8))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-13 I y] (2 (I Sin[x])^7 Cos[x]^7) + Exp[-11 I y] (7 (I Sin[x])^6 Cos[x]^8 + 7 (I Sin[x])^8 Cos[x]^6 + 8 (I Sin[x])^7 Cos[x]^7 + 2 (I Sin[x])^5 Cos[x]^9 + 2 (I Sin[x])^9 Cos[x]^5) + Exp[-9 I y] (38 (I Sin[x])^8 Cos[x]^6 + 38 (I Sin[x])^6 Cos[x]^8 + 18 (I Sin[x])^9 Cos[x]^5 + 18 (I Sin[x])^5 Cos[x]^9 + 36 (I Sin[x])^7 Cos[x]^7 + 4 (I Sin[x])^4 Cos[x]^10 + 4 (I Sin[x])^10 Cos[x]^4) + Exp[-7 I y] (138 (I Sin[x])^7 Cos[x]^7 + 72 (I Sin[x])^5 Cos[x]^9 + 72 (I Sin[x])^9 Cos[x]^5 + 111 (I Sin[x])^6 Cos[x]^8 + 111 (I Sin[x])^8 Cos[x]^6 + 29 (I Sin[x])^4 Cos[x]^10 + 29 (I Sin[x])^10 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+ 57 (I Sin[x])^3 Cos[x]^11 + 11 (I Sin[x])^12 Cos[x]^2 + 11 (I Sin[x])^2 Cos[x]^12 + 1 (I Sin[x])^1 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^1) + Exp[1 I y] (642 (I Sin[x])^7 Cos[x]^7 + 427 (I Sin[x])^5 Cos[x]^9 + 427 (I Sin[x])^9 Cos[x]^5 + 111 (I Sin[x])^3 Cos[x]^11 + 111 (I Sin[x])^11 Cos[x]^3 + 253 (I Sin[x])^4 Cos[x]^10 + 253 (I Sin[x])^10 Cos[x]^4 + 557 (I Sin[x])^6 Cos[x]^8 + 557 (I Sin[x])^8 Cos[x]^6 + 37 (I Sin[x])^2 Cos[x]^12 + 37 (I Sin[x])^12 Cos[x]^2 + 9 (I Sin[x])^1 Cos[x]^13 + 9 (I Sin[x])^13 Cos[x]^1 + 1 Cos[x]^14 + 1 (I Sin[x])^14) + Exp[3 I y] (307 (I Sin[x])^5 Cos[x]^9 + 307 (I Sin[x])^9 Cos[x]^5 + 592 (I Sin[x])^7 Cos[x]^7 + 140 (I Sin[x])^10 Cos[x]^4 + 140 (I Sin[x])^4 Cos[x]^10 + 486 (I Sin[x])^6 Cos[x]^8 + 486 (I Sin[x])^8 Cos[x]^6 + 47 (I Sin[x])^11 Cos[x]^3 + 47 (I Sin[x])^3 Cos[x]^11 + 10 (I Sin[x])^2 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^2 + 1 (I Sin[x])^13 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^13) + Exp[5 I y] (265 (I Sin[x])^8 Cos[x]^6 + 265 (I Sin[x])^6 Cos[x]^8 + 90 (I Sin[x])^4 Cos[x]^10 + 90 (I Sin[x])^10 Cos[x]^4 + 173 (I Sin[x])^5 Cos[x]^9 + 173 (I Sin[x])^9 Cos[x]^5 + 278 (I Sin[x])^7 Cos[x]^7 + 10 (I Sin[x])^2 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^2 + 37 (I Sin[x])^3 Cos[x]^11 + 37 (I Sin[x])^11 Cos[x]^3 + 1 (I Sin[x])^1 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^1) + Exp[7 I y] (112 (I Sin[x])^6 Cos[x]^8 + 112 (I Sin[x])^8 Cos[x]^6 + 33 (I Sin[x])^4 Cos[x]^10 + 33 (I Sin[x])^10 Cos[x]^4 + 70 (I Sin[x])^9 Cos[x]^5 + 70 (I Sin[x])^5 Cos[x]^9 + 122 (I Sin[x])^7 Cos[x]^7 + 9 (I Sin[x])^11 Cos[x]^3 + 9 (I Sin[x])^3 Cos[x]^11 + 1 (I Sin[x])^12 Cos[x]^2 + 1 (I Sin[x])^2 Cos[x]^12) + Exp[9 I y] (40 (I Sin[x])^7 Cos[x]^7 + 20 (I Sin[x])^9 Cos[x]^5 + 20 (I Sin[x])^5 Cos[x]^9 + 2 (I Sin[x])^3 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^3 + 9 (I Sin[x])^4 Cos[x]^10 + 9 (I Sin[x])^10 Cos[x]^4 + 27 (I Sin[x])^6 Cos[x]^8 + 27 (I Sin[x])^8 Cos[x]^6) + Exp[11 I y] (4 (I Sin[x])^5 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^5 + 6 (I Sin[x])^7 Cos[x]^7 + 1 (I Sin[x])^10 Cos[x]^4 + 1 (I Sin[x])^4 Cos[x]^10 + 5 (I Sin[x])^6 Cos[x]^8 + 5 (I Sin[x])^8 Cos[x]^6) + Exp[13 I y] (1 (I Sin[x])^8 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^8));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":531.1333333333,"max_line_length":3761,"alphanum_fraction":0.4969248149} 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\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XHU360wfLayd0VAC6Y5Ta0Wt+3CgL2iGQUc7ZAetnKomp2MgjfLR\/ovNULC5AidNbkKPbfdubKCRMWCz6eIYt6N4LqTdfqacQX+3KZyw1eXioTe\/TrCa5vAj19TeVK3EZdf98GW+gzk\/PKwy1M4F8\/srq6v\/NkFJqc\/ubGklKP2bF1bqkY5JGwtbPadr8MuCDAf0thOwN+WhG9eF4rAToONf0C0GRl7mSI9L1di8N4KW7m7BSD5ZehsdmoD5jtrKSpBHRTpCvA+86EDS\/gLvr4kCsqcE\/9BDCCAH+8XSY3UbpBJjlU+oEJDke0PA8XdaiFk4pBQRd18va5St0\/YuBPf9aqtzmuvA8uYnFNBEwyYzuA811pOxvyaLod8j2Z04GXXluZ9hg0Zg\/Jz83Ww0Y\/omudedVgqXuzSNP4S+dceyUtXICFXDh4+kl+LTtYVW7nn5+Eso9rt2eMWvMJomjF50IyGUdGjfWZFUDade+yWWiPybGGfuuDahEQD2RvVNcXQus0rN1GViA2KN5xI8\/ub7yYf2z85lfCcRbxFsrYeFnlN8HFBHwKLvCawdJa7e+bK\/+ffd6BafM3XgFKwv+JSZLnm\/3t\/We79132sVTA1kbwlqHwAzvArrtHYnAF7U84H+ueXwdW\/I2Kz24sgPCbXX2WMBLVyL9b84emE\/shY38gwKspLtV55zFwBDQHZD46NMXDbKn8ZxkUKms81KDBHVIOn1+HKNYld2G0S50zxaARhKcsJ3rN09OiSO+ugTgVrOtc276kGEJIwMx137sJPnuymNpvp0FGzfdY1lIFs05JrT4szYJEfi8J6+7wyNndh4JPK2+8eMWBkIa9GzvCqlevu0ND+T1QkfzsNLuw4llygUoe16w3+ZgfQ4FtXmr10VTtusU0FPev6JZ4D\/ofnAIu8C1zkXUDIQh8HpMiY5wp+70Nvfa8CY30KRC\/6J7ZIa57N6+pF48Rwx1Vf2yGBPCj1jusyqLtP+d5r68UA64z1aa\/bIfVvg25ofhzcKROkPTBpxlyvFcK7BynwZDym6fipWog72qn81rMe47ivu71nosCVRxnGZnbF8MZ05Pild404anhBVnOUCo\/6U7h65ucF55neqs\/mROxXetKlMT+Oh\/quxNpPFoLO+cS2rWcb0S9HWqwk5j2OyW182SVCgbGqDayH1xAxSmfLDrcd6Tg6OVRw7gIFHE99\/k2lN6P9jj0njh6Nx7aOoLY3xZ3QqfZOitg3AIliRkTxkwX\/6q8XtM8hfaID0BJBLntNzv1Xf4lEaOWoXOoDHsq1kxYzSeBbIcDUrtwMvhIMM+bBXCy21bj5Gl2RYOPxbHxZExzQF6ZQVApwsCwwb611Jo5VFa1Pna\/rxdRLW9zVK3D3Ruc8peNhGPUjeahhvo4mbnyyTEmgFPVPVg1Sx4JQceZIZfSFepDrP\/bcLK8It\/S1apsHJ4DQpz9He083QIbnV5svL0uBwzSz8vsDOpz0OeeV11aNxN5nkjlhNZByJodD8AoDCNUSlKvvCbil\/+Tw\/o8J8FcuPp737BDMLuokNy+cb8PS+faSTtKj53W3TV8U6PdJZRWxDUA4y6mMdOUGNNf\/Kd8UQME3E2z2Zsc6ls450b3js7Xa22rsV5wqtD\/QgDeZI7zvhZNRzXeIx3ayDuVXE+YE45vQvLWMmL+PihvK8sdZeerQefpO7yTXfJ0d9d1NYYSKR6z1LLx9qtBBPCn6CaMBJJcRPxcfISHfu+QbXFMlOGly6lnCnjoILi8fMpqvd64vk11JYk2C2YQDbc0qnXBAWuqcoFE7tugrR7y4nQveY2Mz2+9SQCvLZV3iLAnzT3vOao7nQUrLlJrz3k4g6o24HT7Tic2PKzUlQjKBRGZpu9LaCWl3FdddO0DGFxF7\/twCBq7+GtYdxVUGWyTZjKjzf8dwtOG5hJR66P\/BwXi0uRByNeON5ySOo+khquP1Ew0gbbvr0Z7cKmh51jIouyMKuMZNGvolm2Bled5+jmcVoN7700xm5h26Onexvcttgq95Q4Zt\/gTg+tBnVUHwAwu7Y98bAshAPLHPfKU8AduoXY98BCohtGpsqjB8Pr\/e8p1P41IzcrE5MX8m1EDFqY27vs5Q4e66mlU+vgQcjzndcpyvBkY9Ph45f7YQokTibtXLVeI99pOONWxENOtq+\/XZvghkD1yPnjQuQ547yUO\/rzXizV\/al331qkBA7EHE6OMK\/DUToMpS0Yq3ggeuSxkVQI+kJ7vx8jwUTv56i6mxCSkavnz9ntWQILW7g+9LKfoarUDxnY1IJxZYrTzUhmeS7omoi\/QCa8g+15PFOTDGmXTQ5BoRDwiVCqzM7IOAl9MV25lTYDjx+VRRbj2m9JwYLJqPq4jkN6PfaMh2NXacUliHDltpUWNZJGTTMWzKb56Pd7Uf7LexNaHoiQ7zXWxkzDagrPnJTMUhQfY\/2l7dsE3RaH9jVA6EnktM2T+RD6evs0k1XI8AZwJva++mLojfE3NPtrkO6I+jk91uBCKZsUomUKYbFE+FHQp0q4NOvR9miWnxUOTt9PySfTd8Lck5Sr3ZCB8bH654W9QMS\/f4S33fYXt+htN\/NYJqw8aoBNGef33fehxtunbNBLiiN7stTrsb6XN6l7r5OmHAfnOz4DoyHibWVZgntgLf02RD3ygC7pm5co5hSsU+nUNSn24TQW2bdxbrvlY8fdbEqtx5fjyqLt03FqpBNSmOb8LHa2E84jzhZDUdRUJtBE58ImD82WTPNyKl4LDnpnsyLxUlRTcSX\/s1onGv6sgd3Vp4pfKXLBdPRSfyqb85k\/VoOMsi82lLPlApn7c62hZCNUdlwk3pRmSKTj3WyvsDk\/+XS\/bP13tRt4b\/0a2h8XjUNu+Iarzx0CzZIpwMWzzrX4h5d6Piaf+1rLN38d6dyVXffXvw3Pprj3gt6JBGoCXlUD+C9h2Zs3WavUv6OnDJDmWxyQoAOba6yBIaA72\/LO8PjKRBYfTeuoHyZqy4rnlx645E4M98PGui0gdpFlJPTrxswLZftfvE3fIgaPjCzPOCHjCafEu0rGlG5vOlfidb8mB1TooyqbEPmLNbZqTTi4BNvjqdIcEAzg9QO+j4BRLiBgrCJ3Lh4obt6b\/lu+fjtk30x4mXeP7ZxdJU51zoMvvz7SgrA\/a5XZ3x+ByOt0s\/tw+pJ4BnhVjG783dQGP1V9jE\/BFd7cLXEqobsGgru946qTY4GXN9POpGNfRyXTdUNm9E2qv6vSUbyRBb\/PcuhFSBn+ZN9pg\/dVi0z2PmJhcZLE2fn4nzr4NtZrxCCq\/rsfbb747GBx1w1cF\/\/aa6Eth\/qm3DxuxaVB5nklMRm49\/75WSKoIqoSxhS3m4YC36DRg+2arbAS9cow9K61dBao43elYV4YsFX2\/cffPZWqL6IBBnKYFexSU4Wm99s4CJiJOFs7kJvgNw4NXLHrmySpQ3cD9GX9aMtxb5J64\/dKcNMvLw+I5t40WtLZj463DqfYM+YHqptXN1SimOhzdrHFveir9jl\/Nxz\/RCTML5Fc1VGWi3cA8LTgu+FZDtYj0gdegLVvezffD9Pj\/Obecu\/lafr6f6WMpKlRvRbi2bw1qpanQL4EqK\/v5\/3BZpoZfCdfgy7EjeYFsNbvq0KtoQiqHwdOCI1VA9\/h2ZuhD\/owG3xNve9xrPB5pY70SN3ACMhXxrkUxqxxcLvBQMWKwHHy\/Ug0ucVcynGtrFr+oDtXifdKb5vHzGzRrC+UtwzdYzb\/TD6zFyTDON8aP7X\/\/Cpf\/V8\/zrdwhZ2AdwcR9Y8n3Gc01OEpv46\/GejmjLhhkGyNZmzPzsImMTVRTCrBpx09GRMpp5F3C27SmJNSGhVoFUiDipErc945Qy1qeDfWBmqWlZCa47ZLWOsqoA77PuXkY9RgcNKUt7DvYybPAT4zyaV4\/T5kGJT860IrsmH88lejKU1f+WOLm1GXN4LxFNVVvwomiN9xOLCJhrCDiqF1oLqmqFhQNOFDzmnByh1kLCSV5t0b82DXBAZ\/lG\/lIy1nPsnq0MI2OWH\/GL2cl6UP+QfH31Ixq+eVra\/eYPCZnWHvFrLPOHSglNq5nmGPBDLle6DwWYp2\/6kZxiQeLUieabRukQJrlHrG0dCeyzC2qcP7djxQSf\/avRfnRcHH9qla56kGUeZpGSrjn8GVjKx1BJg7fzuFU+7vc1+MSzqR\/ae1Y1KuY2IJP+eHaEQR6GfSl5neLWAxOn4jM2uzbg21Z5iWn9XNwzsUFph3kfGHfsurF8fyvO3Lo8oXWNAglah+g28s6of45k2sfUA38tJoQJhp0wMmSltuOAB3C1HRrWc+ta4vDAx0UOj9xCfzQuX+DwwBKHZ2leVS\/wfGDNIs\/n6iIn7SOEGl2RpUMY4\/eGbRQGaG3+Jit1PRUlS5mn7F8wgLsmoCMpnw4DPB7FaVLRaH101RvDG3TYpC9xJ2uWAbZJqn4rM9\/i99IdDTcyaCjbbfzw44NyICYt06SmtiFvbsp3p29kHH7a9XFHeCUUyBa\/PlnfjFa37ujXrCRj77fY5486K2EN\/pLhy27HXeoXohL0SJh7VXPF1wPvsOs+yN8ZrYVrL1c1yF9qA7bgZdd\/6DcDF\/epbTUH5vfvMKOOUc0OuMCmFCryrh3W9gQNB6qSQS2byLmBOxczXqdc2jD\/uU9WafErV9fA9gf6vCxeCSgfVF7I4dMCv+3fv9qYUAVfMSWBYBiHD4iuX56atEETx+3B6NUlEPnntKnnqXakyrAemD48MF\/v\/7+8DhgLXndUR5ABVm1rX8RFFeMOunyyuTUdHa8o9verNMIX31GLF\/LFeLrH+0SRfBNO\/7isah7VBEOrOJ\/HL8\/CyPPDB08xCNhdc5xzxKoRFHRMRLKCfqDIQOSGt\/yteKKrcVLNgADxhHOiilfz8dBUf7X6pXqM0a1fp\/mUAGqtW6LFGlJx4+yyz7v3NeGBKUxqFq4D7V\/Tj8qECzErICL5i2srEqZL5wihA2gQQDvBl1qC7+Iul\/vJpCBp5\/L06foBrE7yFuRakTefd3koxe3IwlhBMX3NpD68baLz+P5YMQ6LhF3fLvQVmX4J4vX8ViSLrYv5k9SBDRoqBk\/JdFCOOThluJuILzUT1+XP56NS7MfVlifRYPP\/8t5RcJH3vv9dpfxAZQd2pYWPjrlQsKW8U9m\/kwpJs+znu2SpsOWOMr\/Q30YI0vCYtDErxKChlu035BkQVCC8O\/1KPVyS6+lwYi\/AFts0NXMrBjzMErgjN9EMI4q5QUxq2UhMXH7usl4Hxp59RntOSoPUG4ank7R60fVvoXlQXzu+PrL1EbU0G3RcpELzbnThhsM7v4todeDuV3WD4szvYOTeRntX7m6UHDWf0rxHxkxb+9KU7WnA1aNg+K6QgR3Kz81TY8nY4k4\/cFUmAczKrFe+Su\/Bhud3gqO06tBb\/OWfBj8q3I55leIfRcX4maRpClZi+UuHLjhKh8s+NaYHXlAx2Wmv7p+1nfiDfXYuLzca2MoG19XEl6L29g7prd4U9JIN+USoL0CuMwd5dURImDHBYnaxhoJ3P33\/xpdcjWMNilLVHCRsXeChwcwCDw0WeWi4eP8F7\/73\/gsb2ZRdzcfyYfbC4dG4rQMQ8DfqurlYHfrODWZLhhKh1mpsWe7xYDR07Xb\/LtEDcbfuNL19OZ8PCEfwr5yvs\/Xvq9S6sjbg7sCamDcGLf\/ufXZUdm74a9yM1fvCs40JjagRdEPl2P9xpGNEjnEV1KPSpb8+16JaUF\/CMo\/lai9eW57t5razGSV\/5N2WEGxF4mbBV91jvdjaJtSxpm++7nO4F2HoSAZRh63Wos\/bQBaeHj4R2Q0Or0JSjVrJYPL4llzWoxbosA9WeXq4ByqVyi+cEa2C7MknHEQnKvTc2+tJZdTjudQ\/DwMFquDCWYe8uggyHCZGNvXsbMWptA9\/T+lWgOfr08UrxMjwrL\/mVZJIPYpdWHtb+3Y9sKmTikhZdJDNEqCuTyxC8UcfyPFUOnzjd79qcMwDd7BZ5t8pSwcRPsc3drEUuNhiw1wn9gU7zB4WrtXMBsi\/ePoImQoGMxolIWIhsHdYbOrwbgRjUnTTrfD5+dFg\/jNvbRj6mc99+cnxEa6Ylm95bpQHRpHj0mbKNLjz6VYBi0w2ikwnxtCvJYHMa27m6fl8lT\/Y\/\/ygRiEqFZbWcskUwv3Lwfbq78mwnKhongpleFZLbsj+TwEoD\/S1tOe1g4ymw14N5RL0yhVL9ZGshEteV8OvclJA2zNM3nx1HtJuRzBCVKuRhelW7fObRTBdveJNpk8X7Cs7KGnnR0Ap2l\/lv0dLQXRbYaLjjW74OfX+op10Pb6\/HLB8\/5VyoAScMlOvYoB+gCRr2vc+YBt7VlpiQgHX3gy1gsqv4LGaPLwqqRuIMi7eCocouHpzpk+xVyuyvSt9eyi3B8iZTJ0NrGSc3Oq3asCrZcmXE\/7jy4kdPBXvRXLm4xG1VKXevBNnh7TtUjQaUdn1ZCXHiS5wFWCh8Mi3YVzhkb2HjZqx8vcVQepBBthsWnG6K7wDS\/Kux641asFFvy34j98W5lrudlg7Uw+XF\/zKl\/QAqKzVazrg0wDkk0ezw\/P6lnS8OO23klN8FwGitr8yLBnoga4gPc6E2Hb89s3HzvZ8I2hnPhSvofaA4SlPljV1RGyXqGxXfkXGm1JCZ2VoddAtYVt742cBWl5V9UrIb8fItyp+7gZ1sEvdZ69iRjX6\/VQckhlrRxOnc8eLKA1QvkKg1sCxCDNcaiyjyjqQVKbc+oFSAVdfr+f\/OFWIEsfj0fldBZbH0Sz2CpPQhi9juryLiN3ulR9W3qCiK4\/X1wzVKuwqPriHZ2cubpFMljvxnYwrb6\/Prw8pxru+58QqjuUt6ffwP\/o9WNTv4X\/0e3ByUf\/gtjqfGiwUiUv6B98d\/lqB+iSYdhetiBHKhk0TdLgn0IyqqquurNlDhemR0DB6XT5smWn6eHl3C1bu4XrKO0cGjmImefE3BVDOF7\/q+d96dJvI4tbwp8Kf6ARuXddMuPFwlX\/qBAGLfvy84cHTiJaL\/piLdQEuchFxkYu4VBfgXZ6ggVJdArqL7Xlyz6oOhRfqCzSO9OKWDKpD6z+R5NmEBhzoSJC3qOpDoSFTUUZ5FXosf0njLiHglqdHffxe9+ONdzN3p1wJeFdGsoNPvQ4jRLpJhIP9WDk4OnxZIQ\/GeDveq7r0wiejRywrjYrAZNqBY7imDK4cvDf80r4XFCtlpk7MjwdjlLv4pmUB3PNvKrzH1Q\/Ugg29qSr5sCnjwh\/824ja\/OUqWiFk2BRZY1F6uQ13hf1hW+fYjX\/eq2txSn+Aj4SK5buTsqFm7adXnxy70DIo7iALxydUvSCrGdlQAEe5vpfEupDhZNawmen8PO7y\/2iWQqyAlI3c98x21czHF+MbeWIIMjaO8hs9aagc936ipLwUD7myft6fUAxpnpeHbMUZ+Mxj\/6XpSgI2cZ8lTEQiDLgrflGS6cKfiTm7B5YRUF9kwMHnXhnki\/iVC8bS8dOnURENqEGitW172UAxWL7fevlLUzc6Nl\/XnbLxhSV\/Pb6t06Y2biEwuuDTB0s+fasf\/b96b7D70n31ZFsI2K2YUqU9GoTIOf\/4GaMo1GKfTiL5pIAAbVkVu8EgKLreX6VPCkJL22TVdo9wSDgVkXq7NwEP6c1Qnr9ngLOlQV7PqnSISef44dSdjXoe81v0sx5INzE0f7i8GZ\/1Cjzx+FCN7FHHfCWlW0Cq1W2tgn8LvNBgL7xo14ulfu6Ps57lQ+mjUt3vya1wKonrShhx4J8OZILpVLdnYAxcfdXZHzJCBWPHtQJlrQzgk9t7M5P7O1TvjzWV1aFDJNEjSsh4fj9QOd2Z6JwCOVJvNtq204Htz84TOfoMqE3wuNo5nALFXXmHVfWJaC1hgnF7KKhoZvqt9\/FTdHzVvTFUpg31AxktavUkHNY6ICRxyw91gtJr\/PIbUEHyto+ZHRm3epw9W3MyCT6O+QyfGqjHP4E36FYZFJQX4lB4kFOJrlJXb3R0VsBQqMXDqGkGRljt6zJyy8Or3g9ePtpcBtTl+0P\/OnShQHCw10auYsxUFE05a1ELhaEv0Zzehbw9+81ZaHU4Ynolk\/KlGi4ctn+4Rr4HWRk664IkKEgIeLxSwrwG8l2kzfVGU5BJmj127jMNk+kXZd1s5uvkuaJDK7IykGnryWFfdyquuLDT+2BWDbC8P8d9qjEffVsOz3lKMbDX6cetTZEEOFHtvOvs83SsPRPJvlurAE5kcbjLhUeCvM\/VTbos\/dASZHekg1AKzlk\/uLgvv4UNf0rir50ahP9wrdFmkWu9xMFuXuBgo9AiB1vll45F8HzeoN19vyNOnIxsYx8LfiTkY\/FGdcKcAgMqVURWBwWT8L7mSXXtffl45Yu+6pV0KohtDQ9rWEdG+irH7TmGScjFd1o9\/xIdhEchMqeWgl\/H9PIEIR8\/ftCo3lJOAaueCrmSjVRUVU7+o\/YiCbfH3XX6oFoFc\/YDp0jTZDy35dLQUFEeUHT2qEvzlsCOExt+UdmpmPQuTy0oPgnWFY1LNXGUQpKjTkT4cRqu+a1bzsqfB+H\/e+4HS+d+12QMC5T2tsLS+cCS\/iH0f88Dl84BwKL0xQ4eUiOUVtRv3XKJAcsSv2n7uZMhzvSjyXX7BthrwzRy1q4LJES1CeyVndC8jPphu000qqWvnVUuH4alvozwBynNtwWzkNkKLaPfDi\/xu3Ajv+T9iCPh\/3w2r0tQb9UOf0V2AY9vQta1oKSxpybp3hCSF+9n19CEs\/l9a2Fsq5Da8pgh3Ld4z1upGkjl9asGfnJQ5UH5AaR2XoJzo3nIqH+xc\/WhJhA\/NSWgcSQEC6u3LXvDm48ph+x3CqU1gLbQ7w8xrxIwNAMD3ZkSkLOSs57FnQAbpvR1fmako4isbGTZ6iJ0fzpmaZBIRPXPJTlhZY04wupQtWOuA3WHdaVgshlLOsqK5M+0INGua\/CieCu+pnSL4rsG\/L2daS6svgnZOnJ7h2zb8cT\/8s3w8qL+syHbbtammYxJZs8fZ1lRcdFXEX6\/OPr1QSIJl8fzn3evov07b9wZ1zNw62kmjh8pyGrmboQt76Q5PZoKgbqqh3jEKAtltUipj9gaQWtK9+atvBrYyP+KzhlSC9kL+n90XbxHUxuz82p9UwsBlb1E3aohdF\/I05DPbZX+lQsEcJ0KH1wmMIDsYrdXP1FwxMoAnfVuV6shknZCey54fpw1fYxt+YPB5rlAD395Peo27ZBsPsyAqe+rHqaEpkG\/+oavSRfr8O\/2fWIrDtNh5O7VM1OzRByTnbygbFuLb244dywT7J7\/P8fwEsjtuN\/pY66SRhLKtj9OejqfB97ctYfH+W89hO38cXBoWzwWywVc3BXTiXprZQIERCphy8Ejfy0iQ\/FvYFBaFJ2M7Xue++Z11oK+1xnBqxG+EMWakNa4ug\/5vV4b3\/WuQoxNefvy4hdQPC92fJfDAFofm3RfUV+DBZtOFuk8iYJlvH4cBtP9yJ2tRf2jW4+DO1YqXI79+u\/e1mlytCyldxhb5MqWSz9IhDNcwlo7r0XDskHaG\/P6YXwWx+O1y8H73\/Ol9+c01bc\/ykrFI17MI4yyKhz43et5\/hMZXd1qeX\/de4RcdtyxjY+rkbpxx4jrSTL2E\/KuGItGQNiRmxlPontRbyK98xNnIYi9tH6cUjg\/X9bYrtdtasPJXIW8TvZeOC2UcJT3Zjvu2ud48eZsAc6lTZtvv9aLOdMhfmrb29DK2spga0E5ZnxoDaErdiGhLqbE+xkR6RyXC86x1+Ck0Wd1nrW9GL2yhBh+hIi\/Iy0fcK2joj353JgDRwMoX10b3GHbgGyrcu3Nt9Cw99bomNpwCyz6v6Prgv878C7unx09taeZXwz\/84ENW\/ANh\/Z6wTx+p1oIPzNdQfb8P19f50z2tRRgV79QYnWwEK+nPn8vnVkAhEVu9n942vD\/w9OGJZ42qfiCvldbLo5crH8fVZEO8myKRtsVB8H0vartieESFLLy+X5xNh1ib175+6FnAC7ZdH5+uaMAj37sH9AKzv\/3PCuMG1xiqiD3Nue9Bo\/58bwXYcFfy4Ai3zaZHM5ieF7KWT7xKhFjx1pZDZ0YIP78N3x4XwSBvfU80W9yMfI3VfnM6W4Icjwd2adZArITJ4IS1sRgRFcOO\/t8fapBvXr\/r88QnAn1sedprcH8hf4grFnksSxybFBqkcfC05vxu3LZELxwO\/lnD3M9Ri70DSEvc6hLpPgA8FHHR\/WuV+C2dTYbyFwlWMH+e8WDsH4Y2T2RcbGoFpn3lfCriZSjmiDt3F96P+S8u21Wu6UOvRqEX5X35aNWUaGBtm8besnNRBydaQHRt7eNTaUqUJM+w2dxsgX5rBzONLE3wseJ1TGfD1ciX6WnlNLlKmiYnFgXGB4GhLR03riGfhR3fU5qX1n3b70s8WEefBefFNxDRm+a\/OlKpzrQJ33Yz+5PRSHOXQKOPCTMLaCaKF8uA8UdykJhihQ8HdV9pXN+fZy2ef021KIOrg8Gm7hokfHZgv8j7l\/wf4Qlfq\/j9OGDz9b0YifXdoXXXQR4QeJxVDlfjzu0J7PEQ5swQOfFpTKLln991kxu4iyH6+rxLe\/J5S+mGiGb89Iaq8JeXHHIXJ+LPRNYuWUbQlTLcGke6rLfpAtL58OvQsvQ4Z4CvEUTGzy3YxDushR8ZwqIwysr8z6hQD\/UscoL6\/QR8JlM8K67+9MxhVdpb\/6qIeBd0Pfir\/PXadIbUnHn7m9rzR71w17htYPL3zdgSFwVX5VNGzxdWEfovFa\/8LjpANrrnDlQ8JkIRyvbItWaC5Bqciw\/baQX994ba1pe3wQ71INZthcN4pdF\/UMF+dP4JWoruDoyyRXtH8TsRR2FI38joc2kEVZ23Xt3MrAfGYv79rfftxMkIkvgiFAj\/+bP+cAnzirll9WNI0fCLlryV0LOxBq2jO2FoNl5fWvklj78uBDHYdlCHEeFRQ5n+REJ4bm4AsjStt69SnkYl3jv8GHvmguO2eAGMyx3Ovux\/KdchfhcLjBnMTc62\/Uhy8I4Q5vSvsPV8\/UnfY2qxzfDPhygnLjnx14LLxb4G1iRtDqkVKsfDaZmpv0bKpZ8oPAsaLWEFHZjT\/2e6ULrarBN2Gdw5gEJ18gavad97MEIks3q6\/a1cLHqp6LobBseIG0YSMvowTvs4TySkuUwPqGObPIdqL6mZ6vyplaEM4ePdZUNgE3s5L0friWQkDR4\/LVzE3ZGJ1ctsx0E0kIeAq\/dgoTKWZvQpb+548OhQVjqf1Gf7N3UpdSMAr9q+epu9MMe9bhKi63Z4Gn+VtBEqgGN3t1KfVXXD2paFcbR+Xng3sQbnXi8C9fcVBDxTqpDJZOnRzpW1gPbNVPByOpWHDHuCQhN8IIpcY1dA\/oM1Gh3q+yfn0eumwejz1+OBtXRrWYPDLvQ45egB5d+PcrGpd70K3uKnWoRiS5HuvHIw+UdxeotqGVFvvZSLxI9PFutf\/8\/XH15OJTv9z9RVJKkKEJIUiSUJXUKpUWRLdqVSpIKRUiRREmSUCEhSchOtmPfl7HMYAxjVmMvaS\/9fC+j3\/V5\/\/tcc5nxPM99369zzmvRZqNJAlyUtI8CUe8X6p7efaDt6vtw8nkp9D8OP\/uwKhdIzg+chW5RwczpefbZqwVg\/8rupfzaSJAVK4wd1e+FF76PSjYbvoeAJW9M9ynRoJE8Z\/5u0gDM+nL7WBgf1hmnAjfn7t86HT78kE\/hIRXkNtrbr9fkQAHXZ3uNbH7y8\/o+SH\/GfwA2DYChZIyYvjoRbXNbLnq69IPvI7+28Dm9GE0tvJhN6ALy1cGf1DU0oF+89VDNn4xCgd0+Dzgd8NKt5KhlNhnomyXjHjm8hpBMfw03ezZWz5tUdCvqQt04SZGCbySYzVUsFT\/F1DpKxC2THj\/WL+qEn5nWsh7Tz8cu\/xCfzHUiSuV1HaUKkWCIHb6AIcMB7+rFrz+GdKCqqbGj\/6c2yO3XMo\/\/yAG\/nPiBjROdqD414itGaYPdQicU6rdyZnN1gZurO5tLjrs5X2t1LcjQ77JBrdW0ALl5DbhcWuReqFAnaL68NsjrWYZRL\/dYHmEPoQvPn5Qm7W7gt9q5\/rhLDlrPe59u+24I0VpnK88QEfTddoV8fpaD99\/p8D24OIxlz1NEu+5lovSST1HYN4LO73\/\/WhhbjVtc9tGrjJNwdv1y\/XXxy5fRPbGETDx83Mu0IHQUxQQadLWqizHwkE5YqTIHbbg8an4uPy3lZJzI28YBrOHyqD8Gbfbk\/ds6\/ZyqR9+rDWDUkH7AHu\/pdZtkKhqRQIA038fkWwMsPHopd45GKA3dS08LrG5rgweuSicidrFxVI1wWKyPhsvXtrxel9IMNNmnhnYb2\/GJhONKqzoKKPkkbd3r2Y5DfKeuhZW0o92qWwvCEqiweGXi28OjLegTsTDEKLgDJ3TlY8df0qHA+4FByqJWDMWshYSQcGCmJtFD7tJx1sdGSUzsifiDUEys+znqHkDD2fz6hkJ+Y2yiofSg7LwUjR6Ys2\/48PaI0mmc7PKO9w8DSwz8zIxWNM7mveL9lQfOLt7ORHUplfE7BytxhOuvVbWE1Vl3kIbHsjo7HwnWo\/FHYtmSURae+9gx329fCi7fvedMoA7zXw7sxl513WXv+1GPanWie0cqVkjeeVo5jbe0q7+PNsTQ0OfLvD2XTEqQHJrkYOTSjq\/D6Y58ct2QW\/os7c\/iWtwkZySTfrsdD0autt0r0QPeW\/ViHM6UY00TQUx3HQHVXa797cgYhlDxu19viHchV2+Ce5ZcktSqGALyRXfLP\/1krJ7Rp6CIumodadcwTNFSXV5e6UGOWGPcFLENRfne6oxqDoLukq2HB107UTw31rXPsw3Hy2z5xms5kNhzpkO4mYxjvD8WpV8nIGdz+ZrDeT3I\/8bJp+YOG2sPfF4UvaYbFWb0JvgfvQk+i\/\/mv\/5sD2r2Rl6vvcRE\/eZbwnCLhMR6kWX856lYzXOq68BeNg7WaT280N6JYXMFaqyIvWgabbpR+8IAOjyU334\/hIgjxKs\/TLaxYFjgRvyKW13o\/tNCZtiVgArMzT3PGtjw4HTuK5XhHlSKjvepVu7AvGBXQWc5NoSp\/c6IC+\/BOX+LVdXC63EkfU+\/1BomuOcdvFWWRcGi5\/MfqP4lIL\/Mwh0NjwgYt4PnZ1VAG9hpyLZr17Nx8eHFUgR21+x7ArN9SAVp67WDyt2oMfOewGwfkuAVUhA5Pl3XtkjTqqTZCC53fHwH6SDAWrzJoLcO68r36A+Is1A1kvzodwwD2JaHvCkPqjG0ZFtplDIbZ3W7\/acEXpzLrkfFh59fLtjIQI3n2gOOIzT4qlN7Itm0Ed94id6i6TKw5fCBvDdmLMDWPZy\/p2vwYwBnVelOJvarf01SiWaC7KJLT29v5wBXz\/VPv\/N8jamTld709Uy9QywqBbl+MsjVf\/37vNMM\/xCtL5mEu2SwYE9Y6oK7Nd24843ilVhNKqpZ7xjf\/IH97zpTf03AMmrPrC83zvpya874cmNBncK60BYONrrOV18rxITZ+pTr742z\/t6z9eznxyJLJHLYqDc47nHwHR04B+Y\/pAql40SnxgfMZ+HEEO\/iyz8Y4E1yWzAQ9BKlKCpb28+woUXO1+vyu1q08tPc\/+N6N97QXTP4XJ0Jscq2Ci\/KWzDcbZvEqwvdeD9kzc6vrQw47CxU08pbjVPd3+vwEwV\/h265efYGCyY++UXGTrSjAFnRtd6\/GxcNbiGWSrAgan1Ou5tCM17Wo68ZFO79bz7sLI\/xv\/mwcIabD+uT57aFT5+EcbdMl\/AqDKPs\/mXM6+sqkQ\/2L4vJJGN5ClHD4PYQCp\/SlfspWYHSjvHCKtsYyNUdoEGgSWKgKQtshN4KJF1kYNth8NxS0odOpLeL\/VSZELN8bhExhomz6332ev6zH14FoXT8c3zST0C+ByfNs66MS9Ph5o\/Pd8COjrnzeRX9bLr++fhd1+hb6tFGQSE\/ycZwzREM5PINuP1S3M3tlwZx82r\/5py1CaeScc5Wyt0DFUOoYffxXmNOHmZ+PdV0rLUX73kzX28lD+ICvdQ0s22l6M+trw1n6mucra9PROvR9yx5B6OiLZW68zLhuoSC9kEnEqjJlYiGvYoC9vbUzSY7E0GN4dNrHEuBLezVTwxlhvGIumyBpBQBnl35KvH7QStmJqkKvTs2jM7BC0zpvc3QfJcpKC1cj0LrtC7fGHiMod\/dN3ovawOFg5su3kthw1dBrTVf\/9Th\/O\/l93ctHETfU3z+ftN4xE9j923BwCYUjlNyX9YzjKXcuZXeiXmr7p6qxkO+V96kpAyg29mbX2w2dWJDwDL3iOE6tNpACvPyGsLcL2JZsvu60P7kro6\/dk2oqRGmz4xmo+HMc8TagS0Gp7VqkZtfhl8TRi1OObKxPuL20fpD1ciKeiphxcvGtI+uxCB7BpZue5u9m1OLQVeG5ntkMPGk0FK\/M35MPJWTt4u5rHn6dzKbO0+yMIX7+Qi3SGO\/4Ap0WH3nXIpIG0rNc4urPkHAMcKckYy1NWjU8nihnGgXGii\/WdctV48ObnKSi5YVIid6vbVCHgnlHJUvDj5tQNmYlCfjGr1AUFPqeqpFnM2jhCKeNwfDDSizc9t\/+i+mn0PRpCAZ1NyXVsj3kmZzLaHtjyhbya8HvlsYNvtIENGSJqDh82oAIpgEYVWbLrCO2vhhcQkJ\/f8O10lJcuCXD8n83t5uKDfhWAzfaJ8+NyjBvaEcmNqhhMNdBFyaLC09MDIIm04U7TF43Y\/q5WdzhVuaMc0xhr21fwikLaPWkyb7cM3ptRY8HnX4NdjGZ0HR\/+9Trczk7WpY2IyqiryJVmIc4B9tfrf6ARktrlvXP4mvwD1P556KKGdB59GuJ\/QSAlJtit\/Ga9Zh4\/VQ6+vtbPC01rh1sr8DlVb1JOyfrv8+CjwnTa7MgxPJjWt3NtIxbLfDjW0d7ej4WuxviEoVaBpL7V+pT8OV6gnqf6dxzf7LJ1ZLryiG5WVRp9f50\/7L+8JZ3peCm7vFcb1WpP4gGB3WHphd13hphuePszz\/uBmeP55+nbprm0sCZLsQV9RX9qLJexM1OZdeyBRf\/CDxTyimjpg\/qTxLxWfEr96D1\/vh5\/COru7LI0g3cL6rGlcGwRfNkt64liGd+k71zbyR6f085Pn8Y7Vw65rAUrHOKnSXjKvQMRrH7Pm51OAvFTC7P+xeJ8R+TB3EU+KnNdonq4EndIeuKisHq6wvtX7KHcFNva8fauypg6879c9oBmchxW6Op4LsKApJB7hbB5fDumPpknmhr3FCTkLmC20EuXp\/OMnNzRHS\/3VSMWn0H87XD\/iV7yqdh0K60e6OF0bx6+UHQ\/OEO6GU24cRCTvfdfbhMBYJhATrDJIgzqh6X5ZNEU6JNPuIDZLQOGjjj8CT0\/fdVKht7boekLUOHL94vgwSLOanZKVRkUeDukgliAVxi1s85v+shI8fl9tJ6\/XgT+Etcb0\/WaDIfvudwFMLUn0vjSum7+fQoa0j\/sociKnLS7U37sIQo\/2ywepMHH6Tt+BceysmNC7Z1bqdhNcTvJ2mYlnol3xKZJV6G96iur3MMP4AOyujFDsJ9bjyigzp7\/cQ3JGU\/qIp3Ae2pxtMZpkR0EN0vepdj0CMZLl5BJ7KAMO2C\/X7PAj4Zry9uib9MYgpfnzmkJcOR5OikyZv1eMC8Ua3jcw0uNEuIP1ToxYPVzJEmbkcGB5\/u87oQTc+Zlz8rfetFjsX+JjX+Q7P+suhcMbywy9eNOIWtUz5Ok8aZg9+z\/QNo2NbsHh+y9keGBS+rd34oWXWHw+4eAn+g5fAf+j82YMeXcC\/u3m4qLYVdnD9VcItFSaS95BALEYn7dGqJlAw8RD4MTUINg83BCfXdEFs9sp9C04SICeX1JSuPAiRXSLVLuH5KPVb0HHCsh9Ej18snMrux8LIKIuAoVeoTYlrCfzRAhUq235kbuyEiWPbRvPH3qB9F5\/P3BNtQGymfTiWT4FgQZL6k7lESL4hMPI5lo3qf2IyLyh14C7RxbeFj1Lx05nfWzUfDeNs7oOYxVyLh+8omKwupHP7xMhs3hO4Pk5YJ+9KxvcnVZzpFkO4iSxwl6qcOesDAP4zPgD\/8qdcm8O3s78Pw5FL949oD7T+y73KWePstPwzB5rv7dSZ+6oVx82jCkotuzFx\/pezu3MHYc6R88RR\/SbM9wrcm9\/Xid91I3a\/U81HOVmj9\/ovMoHUPEY6YU8CSd55WUPBJWhqE73g5MU3EPLM2Ov4cwo433o0dVHvHeY4JRCirudDCpn+pPxQLyxHnSM6c1ig6t3jpHyBiISjesvHFhJRsFF\/UjGPAWFzrj1PW9OFQ0uHPvbGd+HUpde8HbuKkHnpY8MgPw1kYzi922WykCSpL5lgk4v3E0hH3BYwQDnm3YnnTQ9xgeFF9\/Clr3Hn7tNnTA\/14Q5BQdL3O70451tH2NH1\/jAWcanDragbOW+ct+eU9KAQOfLM3P4adEySi9wwpxxOD1uOvqQwkRH92v4wLxMaP33x2m1RDkahvkQxYgWmvVqbofPr\/\/wzXj1ttWFiyHH\/kEUa4bg8X3ZH6btSUOXbW6I1jXcOXnUfcyn0hX1X5GiFZRUQxECZvTv7ccfOTPX6JwVwe0me9QJFDqzm+h1xfXJwZ\/0+mZo29r\/rs3qTdTb+DnPPsUCNk0a6M71Phdu6nRNJZSBXv4Nc\/c4\/\/MzNa8P\/5LXhMjH\/cJL4CG7MsNPqu5v9D4cH7b3RR2Ry8HbahIvU82L8E\/jTIgv6cLmHTVfZNH6eEg8Xp55Ixye\/3XJqDakodfVFGnxsAvvW4FVt3UMQu9WpxYhWj\/Xq9h6V9wjQIH5gfJHUGGTP9LVQIfW8wTqnOnBQXlsy6sqB9HUJDZa2NRj9KirQ+WEjNF9hPVqXNwyVRq\/GS\/Jr8Fih2mh\/eTW46\/aLeIwNw7EP15Xsx+rR91KUtDF\/N+xSOrOEr3kIt1+MCbthFwqb4xt\/twd0QOMj0hWfzYOYdNAut\/jsDbgq62+s61CBsg9RWZWnD4s2+Nt7pTaDxRuF\/mNFeUg3Oj2aK01GWz0RzWOJ9eCbfkI080EyCj\/rW3jFiYLL31zPzd1UDlZDQ2u1Q1Mhkvo0a5VrNgSFTdhHPa6BsUmXhVpXCRD73odx1WsY\/SznsD6tb4CAGfwGi7n4rXwGv0HYzL4HpJl9D+dyfTW3zOAH4OIH5OIH+MjIPB29vAaYN9Kz1ksPoWCybKLdMAmindsi46fPRV9DRTkz+UG0E5YLHt9BhtDyFKnLY41Q2NO0O8ZzEFe\/2aUEw51gf31LqrBQJXx9pUdoXDeNcy7\/QTv3MjAedCNY6zfD\/a0urQv3d6PIHZEdl38Uwjorj1UxpypBKPbw7lV23Xi1pS6HMZQH5TlWErt9R1CVIXm6RZOI1z0tmqPd28H3xkWVR1QOdIVap8R6xICj9q7NNmZEPMK0GpV2H4KUCqlbR6pewpXSqT1KPD24qHEL7UJcF4r1ia8OeELGgo\/0fZXxbbAwWuV4iGUxGkvXXnEv5oB7xSXPiwPNWDyHudM+5i2ElslwmsgDmPB4mf66EzRseHSZZC+VAW2bi+etWzf0L5dnvdYTW3ZYLgQ8NCQ5WbJQWfSNXv+xfoysEhGXpBdALS99si5+AEvbPJwlN9LwJMX65XnBIgiae6R8KJwD69Wpc7PUqXiJX+MG62kpBOwR3fDTaxjY3NyTFerVMdGh+cAzr4JHcscAFBzW9iyVoGDYifZPPLnFMLXH00FZcQiu7fNRy7SloP24RWrxmXQQqA1SzpkcBOMrcylTY73Y88Kmsf9tEVwX9DlcNlgE7287OdIPEbD5\/XOCe085kDx6Xoz51cCEr4KApUU7TiN7w3GdAfRYuEdY7MF0nbP9ww0+ny5c2FyypjuRhYvOp2dPXqvEwrDHyWadRJS2HyzRahjAy6sdor+qV6Jf3Zds8\/ed+Ctpq7i0UA8onaKb8X+mg42LakgBjQUv89kn7GO6oK9fPZxjTZ\/NR4DfpQvFXPZ3AuF1Xs2+WzQQjFb4Uq7GgjXDiYf5\/DrQ4YjVG8JZCtjacNjU9DoMFf4rZpjYgvYN\/hJWQmS4fneF+Y9SAqa5W2ZtGqjHsN8Zy8gmvbCX8sF4rUEdbpVdVKLN245BN89pyfwhgihzjKRjUodk+urbUbQazJEpf600QIKf50r1fGi1mPq1h\/z6XDtksqryN\/YNIMvoI4XDeoNHuqlLQxXaQTv2anFAAxufb014N8gfCRLpPtnum9uhL6L+qa0+C+eeG+f33JyA1enhq2K2voaBzw9Sxtbng+7Zsb0Ox4cgPPHTYFlaCzzL6GzpfzaAodRtZqa8ueC80DrLzKcQ7Mvf25nlk+A7h6GiUD2AH6mp4+6N7yFqp3nXgfJueJEWLyfWykYZ+nFehcWvQJtPTZdhS4RQl6qNhm0cdD+Y2+qyIwsmgqvPHAklgaBMhKHXARbennugoiblEJS37NYZ3kqE2Lfuu6Nspv\/OS6mc0Io38NA0vmp8UxtMMfIPpRwcQMPjGw0XtbeAjH\/xdp4zORAlXN8T38sCfsP7rq7EJlAfKrUJ\/FYBQ\/ULWYJ1LGCvIz97faMa1qpk\/bak5cG7jVsWZbixgOvX+o\/vwZrRd8DZ+otfXzqxYH+lzkhDUA\/quxz8bP2oDDxmfGn++bHM9v3uzfjSINeXBmfnVtIGRaL0vz2o8ObFtcOrh5HN7Qe+ELQ9gTU9uOXnnZtJnRzkD2k02DlOxLAjtN+ZS5vxjPhuv1uPC6H0iK+KPpMFjZE5vHGqDAi\/X37vXWo9MFeelxsYrAc\/VXniU8sEoO1cO7Tr3gC291mSjPY3QEe1gWCKxTswy3DU\/fJ0AEXu\/Y1XobfAjlb+p\/NDI0D58eaoxUuHUHvyh6xzUyMk3bshUG3RBn8en1th9I4COxkLTfbO78d3q1jzdoa2wDHvt2uF4\/uhZPOUuT4fFR9F7pPTu9EMUnFlWmJKfUDXSWkMcqNh3HX2unpSPfRE96\/cuIoMl0w2Hg59S0NtG7nfMdksTLcSTnbc2Qq+DL2SlfIdMDUmfjHd4TWIQ6WX6V0WvqowPxoi0AnLG6RvN\/FFgJKkRINbKRPDLpx2UJLsAZLT9qAth9Ih9kDTnI1udFzOV77WaKALJDVsqpbu6keuDghy+D+O+10egKsPL0iF2PWiIDfXfpY\/RlKUOZ77kYppqXcVCCXd8DxcoYh0kwNvNz1MYn6h4Ndw6839It0QEtbo676DDatmdLXI1dUiN38E+hL1HlXEBKC3WZeO2ZsxnO07lYcNFq5Y9BITfz5ZHjA+jJNzz2Pbp1ZYsPfDgbF3bfjKbvG6O1G1WCDTrmblQIA54\/vytI+2487AJ3Obh+rxjvT97NWyJJg6nrLkcXE7BjwyW6ht2oanxlNzHVe0QfbisDypFUykt92+E9DGgflcvl9jb+CWDe\/paMXl3876bMs\/SRpc84OBoY5OJiG1HPg2wy8CpUcnRd0aaWgmaqj6mDkAbcN6mzNXvQXK+laPV0VRaCr47NVEBgupLpoqvGf6kYdCHvhqFIna5S2HFlay8KUTQybPjYKKoTg6R6IehxV5WwwUWoEvckl7s\/\/0c2PqS\/zgtOP65b7fhoQIEKzB89Ctn4VszrOpzDQCZu4Mzdva2wJdcroKe7QZqMq2G7VfXIwdmX9jjoU34fsnee8MXCuxvCAu9q91EgZRTqZ2kJuw\/Zg8pz2mHCV+ucyr\/xiPLPrfRWd7qnBS++4vI9t6nKty7rxI8guIETol1StTjRJzPml1PajFse65RmeEM5Aa5MicU9SEfTfKb2zPr0fK+qLI8rvdyOW5\/fPn\/6UkfLOdl4L3NV66GDJIs7pIeE6+aONZ2IWOe47hhe9EeFa6wmanzQDs\/inQfuAUGzViaWGHN1SBvP0JC1FdMt4\/UZJHXcrEZfk53S9NSmHfPO1f+tlkPKJT1T\/8nIXkL5RHxk3FcP+u3gKDNCI2C\/TTeD\/TcaLMecOnjZWgT6AuWKrcid\/C2Z\/EnZ5B2dMYv9Nd\/ZC\/oGRXcW8XfvpYtaH8TyH4Flc9ZTjTgHBifeThVWSsLDpAtZ6LEOkU4ye4oQ8s5jwT7D\/fhVvIt175UpnIni7rPy7ph+67B\/U5EWR8MdTBOuhDR12e+uAJ2X64F8G6d82HgokkJ0\/WWjq6ayp1hu6mwtbHi4z3NXehtnXvY9k9VVjdl37vixQL3f1P5Fz6U41Rr5w2VtPrsC5rgXvPYyY6Oh04mbesAc2025vCQih4yv9Z4ooNA+BlUn0gqjICFZmbHn7eVotFBTUBJ7N6IUr\/8ZijYTuSauXXvVlSiO6Vz\/PdZXpB0PKB8tQYEYlxy2uIsnkYMv+cnLUODQTWS9\/lrSTi0JNlpNMehRgXsZxY\/okBsmufiHom9cDDMIrntZLX+NN\/RzXhFgOMedW\/nD\/SBYTbp5d+F2yAC0eq7dZc6cWaW4LLfJy78T9zdqRw5+wT8QXJOXcG8brUXiliWfWsPxJ2GdwsaXEbwilTVNO\/W\/7Pp4t8aNCQ35eDDtvrChe5Tf\/\/LYvVDV9TMb3njKqZDwfP+JpKZKVW4os+ynmpI\/1Y+umdtfT1QZxwBoKHbg22iGmF8Dn14o2MfU+kqilw\/tZ6yXALIlxSDhOOu945Xd\/XPZ0D\/WC\/Y7v72zVtUH\/y9U1zZhdQAt8+2fqhD2zzdL5mmZNgXkfd9dDNvWBUOqawuiwFjs2R3G1dOY6G3H5OCN3p2WrBnn9+YrO6PMo6llaIeD9eXbWEZJbGBHrTlVu0Bz3Ik1hMNLvdgCusz\/gXTOOk5h82kptUuqDgk4V76goq6AdomPRkFIDeFgdW7qF+SKq6sNZSkA75xoprlz\/LAtPf7pN9Ov1wSs11p7EAHeatsHqcvKgC1O2gx7GDCq+CZcT6d9KATFM4+i6hEt7UmSetN6VDipn\/euPrNEx3Xr9tgkhDw2de6Q9DazFXozOaymBgpo\/x+rAMBopehMED81uwyEppSmh6nzzW5FG\/RpSJf8xVGpWX1uLpqcGf1g5MONW\/O6\/uav\/093tVc6YqwLXFxTRoAwO+Jrk8Co6hgoCjwLW3r4vAdafRu5VeTPA63avJw6bBPpMqmU3UYlDkf608L46MV9gtG\/YhHfpeNql3D7eDSDOE7vrcibKvD6RvkmdC5OtHcunyrRCQqi0dWUbBlQ9untjkN\/09Caedf2whQLVgRTdRtQcJv5blWXxhwnfTDG+j+o5Z3y34j+8Wcn264D8+Xeh9LCvEmkqF8s+i6aeu0fFy+20nXVEayraPLgn+3gGtT8ojPz5k\/\/O9T\/6tfcHHvBMq5ijNHTRnoc+MbheDL9Q+kglsh7Gj95PEWQyktgx\/3N7BQHc+hd5NRq0g5z7fhcIg4fbO1rV3hgfRd9dujbDhVuD2A\/\/xcNJ0Qfw2vR6OZfBGPkjsQNPhfPpdvmGU5Kvo62TSsYHLf5itp4LEUPjHexJYxdfP+wUdYHFkz+DazSyQjQkpuEJ5DckM+x0qISz8ytYz3zpdZ6V4nVzS4kqF\/M1\/AEaGcGLGDwo8Z\/SnUM\/Vn3L1vzBhcnz1ia5uMCtzl1zVOoi3N127uu9ALSTYuTxK\/8NEHxMtF\/GxIpx4Oib4jacF7ex5tZo0mUg43Ot2efqcqM+xsRnVa0DHIFr6k78MdFSZf5XPrwy7R8X2X4uuwTHj+6scWsvwgSzjfqPKKPDm7k1KVQqGPqOvSntlp+uQvBbZtoDxf3y\/gyooYtlUhuKCmsHFy0fh1d+Kk59KMzHVes3dRZZE\/CqzuTRnXz7oxaUMq79Jh8aIgndO9p34VYJkfU+7ABpfXnFR9fUAOdL26vFTRJxcG2F\/5EIFnLjobUt+HgovH20TdBTvwBBZzpMD2dmgoyAsVb\/sNTr\/7zwdZufpvx2YGWmTmRjO9aXh5lSCqtIk74\/VIf98bLhzfDB9ruXuLFiEMWHnN5vR6bDF\/dgYkcKGEufYRX7aySi8uLnzdxgdnKKWTd3aPgCpMoc81c1IIDZByE\/Z2APSOd4FJeO56N77vSa8uR2ic1aM7frQBSO2+4+bSIah97krczOM26HLWuXm3YkO+FBosCE4qghPmytF8bi3QXnRWgdV526Qc1giGvs1F087\/Fml9IINBO57PnufFb999N1RPgDl3Pc8e4bfhQSunnfW38yaq+f1OjjquvvNdF1YylLI8GPiaWpm876CbEyI+r5jVQYLTpnwGxPf1kGHoaBlmBUJl68wHDvey4Yvhd7H2sRqwO7U+exdR6frhjNSVIkEJkj2+woUFFfB8S08bdILyKikudTXLo8NU0vTenc9I4Bx7IV05lg3Vv\/cInsqmQW5+eTrV3Y3AemxrcrluF5UeJl\/rk2rC62Gn3VbphVg3GLWFo3WASBsuLJ6fnEb+pR+G9t2Ow+HHB1pRpdYUHXDVuIUk4TLHqlLPowtRitlGWuJRUxYKiRX6eAxjcc2Mj\/k6MRiXPr9+ZRzbMhm11\/7rtiGb68v26YgnYhWDZXKZXF0ELRZWlj2qhPNG21ELTxSUNhp2+2UeSwoV6j78fsKYRb3wo1hTQf5q8V42lrX6UduMwbl7V1y0nAEyttG4tNNS1CxJO3Ez0Q2Ljtm2Si2vecf3qiNHiMpJw1gxKrrV24xyTCbo8rzy7bNavcA7k1SjTs6SAT6fHYf\/1MKejcV8cYub8PXbWOWNS+zsN53Udu1rEGcGirM\/Pi1Axd\/SnijP1KMzSpnnxWJcPC0N\/1AN7TC7bEFJfy\/RuCOVi+9aWkekHZ275FVaQQviZ2Z5+xH4WHE2O3Vehn\/5XtDEXc+npC4xzwosRXq15p0XkgdgvvRKf5uIlnQJmm\/VGBDB8yPPnP9p\/QI9OynHND0uAMLdCMcxKfx0A9nnV99r9\/D8yZlndQFTPx2PzVHfBqHpym3dn7mywdrFZWO1kUsvHZD15ucwMZTzum\/Ou\/mA\/9MjhueNqbKfuRh4kTJ6RW5wR+A1vTkXk0eDft1HQczU9gYP09\/23ORAggKzJ+M\/0NHy9cDBfqKbFSc25ZNUuvA8GuplSzRJIw7vzLYNpOJ66LybUaN27GVf3He+W9F6Lrnwto3nQNoZrSxLS+tDRc8izerKs9D+5K1sh3LmCiRXXleXo+A2RnBSmZrUtHf9m2Qdg0L740YLJjv2oQrtML8fu0vQLrQ5yfkz5VgHkPf+SiUhSu93+JJajz4HxBJPOvQBN4CNeKP9Nl4cbREhOdjLJjRDSsqrzbCWP3di63zWTjmfXSscUkUuje9INoc7sYQQcEYyWIKnFrn1nlWthPO9YwHX1jUiSXCi6IvvCBDeeLcQIs77VD0+jPVz7MbrWtffFN+2AWa9XP+Cl7qhowAi68SyVToau3krymioEIf48dvzVewMVNpvQB\/P+zbITAy3N6PHH9HtdPyeRCYf3thqGEfaJpXaIjI9+C7om7t0KwCKMuJ2u2iUwYSd\/kvnM+sx6znyQUBeQz0mViuZSCZBy2Jixxk1Fpx+VRt39MSBgYbP97QG\/8WGheWM9k\/G3CHTujP9fJ09EqvuvE1oBbZzn5GWuGDsKXz1a5H52Ow2oyplRPSh42hBoy71Y+gXsRky7Xt8Rhjm\/UuZ7QV\/D72BoitYIL4hITUhvI2UIzyFFa50Y2bjpUtHn1KASOP7WfPnqSDi57GgyBBEnpd1Aray0cBhYTebvL+fnAqelSz3awEI28xdJcWDuGZIZf8wufd2H64JuGIcSpqn896n6A4MuufjxPe0SdG7xXgsEVJicxxDsZwam1yA7qwh0Jvy8t7jff1gjUyagexMcXlm+cIBW\/mExJteelYeNvgocX8UtSP2bnH7jMbs81WJNSeZeK5AxL71zzJR27djWI5F17PU6ai4q3DJPHD7zHzXPKPdbfYeHlE85rXMgamvgpURJN0VF9S\/DCSzkbJYds0Yx4aLt\/5otYhuRNNS\/lrsr8RIbsp2\/zzUB86\/arIoBLbUNDk7qNLgW3AzV\/D\/+SvoXKlP+N4by1atHxv8XpNxzU\/RI8GEZoh7Vj9+jNLmf\/0sAvW6YlWfiAj\/f4Pcm8VDRInIm4SP1KQHHkhfd70\/vxUrebgo\/tMaLN0vrb3M+UfP+d2iuq7rQ5VUH6o4d6qJgbO9hPGVvJbn4yZrgNJ8V\/XqdFw27xvslNGAzDP0nAe81ENuB9bMTr2hwWR3coTX0rDcNRmyHuBeSU+ntPpQPUd\/8f\/Z+qah2ur52NmdGmPlPIwaDrZ+p+UyYSasob4zSpV2K95IfytwSh8NN\/7fm5EFhiSxIhm\/f0gE7+31VynFix0B86afWCB35FjJjvS6TDEnSfOnvvPv7Okem0aoNtxDTVr6QuQ30U\/MXeUBpNWmnv9wyvgdnyeqKbJXmQSvTJfT9Lhvj\/dpmdjGRxUXH+duTsW9xpu\/NBC74c1rTnHVojTIYSwj5Lu2Au5hSOJOeFZGBy64jaZToPmUOnmNFY36L1oVo1TL8a++fWeR4XIWC+mc2nwAB3XBpiT954m4Z5q693f20ngPKUcsjGhD5S1SOTugV48gVkTRfyJ0\/UmH\/2MTBMqp2z\/Zij\/Hr3sL4UbsQpROCe+fZjciE0VNXN89bIwrmfp2MhICnaX3iEqyLTi16ouTYdFBagqbxwiIZSF4VWspEYqFT0f\/TA83PoBo+QnwvwSX+LzgFghFWYvZov+cYh7noJSjvff\/1iWifq6fIz5J7vxzoiW9A67PPxFelcttq4Au7xjNjVcoeGuc9V1b9iJKNHrlZSrXI6H37\/UcTnWh8bhUU3697NRITn1yt5DtdDPd\/Pdb9tBcLyy+u6msi408zZ1SbtaB7Y3XXpy1g+B1YG8CdWlRFQTWSbteLIWeAy+vVByH4Gf3LyPg+ZChVm85XB66nFahTcHEvU4h7qOtuMGFuHs1fFSmFO57PKWhiHY1+BAmZpev59+OAtdUCWh4aELzqum64g99vfI7vZEjE08JB02vd+u0G2s1KawkExQEvvaS0Ku\/+o\/HtTnGf9V4PIbkYf+P\/xGKN\/nNH69aGh6X5nhR713a9x6K50AH6xUo1YJDOKO7S03jxeSMS3LPKxYkgB+PY8PpgpM\/w71ES8Lo15YOJz9cOnxPvxPnuw\/\/bh0g94C2lkWvlq7P89kXS8c7161x9+Fgvax\/JESZe3gLP3lmWgeDep2fUnblJgCpranY1+ebMcYnQhr2JcNC3ZAwjNXGmwfiw\/y+N2BexasvhNYXAg2x3Ic6NU0iNpwxvvWPBKuZPWvrKJFQ\/JtrSwPuel686enrsc2Ao6N2syVUcyAy81DBq5jdOiiTynWiFLBS9aXHR\/OBG6OJFhIHTntLkmDn2P3Vu\/mMIA7l4EU4UlPuhYV5G6+onSy6PBVu+fk5hP9IKJbljeVw4ATUue2h5f04Ni9ZLklskUYLl5nGvmlH\/Rfrh208aWgaNmFuRTlYjSsTolrKKCBwon1I1tTu9ChKqiDwMnAYA1jnbVF\/SDrNXf44MpeLHteGvfLKhYFrQxjH3oxQO+HwY4HVhScMPUraPCNwrMR4xs2Py4F1anS8gETKmbJuXpN7eqGMxvWLg1Qew3fBEPpp8714\/3IfaneQmSINZVRM92aAIx1626TVtJwX80qXsvDfUAYlnCN3kdDnZPO3uyuQri0\/f06iXPVmHyGPPpAko67f1R65wZXQFRvyLZlRjlYLXyxP+UzAwPLV3rbX8yCWM9vLyQuV2Cs\/4YjLyqZ2GOp\/mfsfQnwp+sbbshMQ7uoM4JLXzEw5EwzpzK1DFImcwMSrpfi11hN\/2uuLDB+Mbxe\/XIPcn1QIey5\/TznC0w48vaYSPTP7tn5MnBz3+A\/uW9g966h\/aYsE3ZNJB8aJ3diup2RRSbSYFmaabX39N8x1RIsiwrvwGzprxdfeNFhnXvWYoukclB+Wrp09Qc2rl\/R+0VMmI5z1l1yllTiQErYr7PzrXpwj9z8j5eWVsGxUCGdgqwBCLDxT5Wo7UaWfPJ2o\/lFELq7alIvgwMChf7H+MT6UbeYcVNctQA0D61tmNwyghNcny47bt70iivhQW\/fD+Ofjxc9P49TsMn\/yqvQpHo8lsgne8ZgeDZPB2d9REM0u\/LfWg9h7bKjIRvnkrFXa07zBrUKzAvMXiRxdhDlsmN2cOopeMSrzXrySzW2OewyPjMyiMsjXm3M7+nGTwfFhk0U69GnQrPFMzUd7xtfFJf43IsjE6OhZKU+TBpN5AxHDc360oDHDP6HroykVuKqQdwegRI+dlTQjdIRtU4uhk1bJ5fJR7aDymHKs7\/OSXBO9nqj3qERCDIzSvOoaYcNvF6v2i1i\/+UgV6jol5TNbwN9DfTO3PsaUlZtUSu+NATSu55ardBp+6dT9lsT2smc3hePDXDOUJ43g2Mfee2R26lw17ZvL21wBE7sVHjtfL4aAtOsSO8LM4F8K2WXFg8VxA0d3oj\/qIFJ9M8JvFkEeV5fVDeNdANl7xtD0UuVsGWl5I1qnXTYq3KQ+n99Njl\/py2Tgm8hfcZHFKciOTbHgsZR8\/eazznt98BRYM3TlfxlmBSvmFMxMoq1OWfv6TPfgWN72oje6w94vVEmcZ\/YGM49pZrxl0JFu7o+m0BNMjLrfRxknfLQ7kvtiS1zqXjwiMFvKj8JVX9KHfYhp+FQ2NB2v0waFkY2refN6kKa8w3DV61J+PNsc9BoayVGzOhPgTDzPsD3pfNzzaUR8ufdub5yAwXmPWi5IN9NgEDNwo\/a4u9B6v4oaY8+CTYcOq45wGmFOzvLx6+UlUNQ34JbfN9L8fel1adai\/rgp8OcTwdMMuBiiXl9XEM6XprSJe41pcJZ20A7O9N6cPYo6qr5PI17\/YoU0zg01EiJu5TMrIFd1TtOjL3vwJ9b06yFqqj41cD7bFx2K9w8pYB7FnVgpabpOUymYfCMDgi4OiCc5Utw9USwY0ZPhO4zeiIcETp2Po3WAaZuRj1yc4Yx50\/0Nw65Fh0THOPFvnegtK+1RVVVItqZRv9879KJC9VH75Q+bMdr0eQ9q85mI+e4WZNURSca6u0K+9ROxN2jgrwR8dPvdyNsbt09CiOVQkFretggnr5\/F79LOsjdaFW7s4uIZUafpKuPcuBU00Yd8dFA5PHqen2orBV\/P1wmseoAB9y9VS7mq2Xh+aqRiY+3O3Dtwk13vRrZUNq24FD6r5MQUM66KTe3C6NuCcbk\/+nGpDbzn6Hr2XB\/B1XupXYjhF8h5urqkpHfLvqVbRYHcuV+CZXeb4KkJnmNSxbTuODWyqaCR2zQqBNYnfykDaRfEPlK+Ih4KyO5bwnvdP2veJojv7kF4ko+7h8P6cI0ETvXQPFB2FuwLLxArx1+OtH3abXUYaKCyVePlGEIWEx2EfNuxtQkZ1He3vJ\/138njMQG2rXil5zoW2k\/ynFDwmYv1bgxmOD6rg81FzwW\/VGDPLdO1P4KGgQtoot6TUoNspddrw6UL8O7U4YH3\/uOwKunW19E0GtQncKawmW1\/65vOqrXFBlRgayn\/CWdXgQY4jUMaoiohJwlS8vz1elwV65zTYJnKwTnVMT7xefCecvWfHMjOlx38g1ZU9gGF6PF7e+2lUJKprsv2YcFymU7NS+Ps3AkfdPDTRHtEL9fOKKCRgChRkPVHVcpyHrB3LDuDgdlV41mLuIpBsrT0e8R57ohQF7dPKGjH9JO1cpbqxFgL7VKabCvByLHPy+Sf9sH9kaTf07ndcDIh18LMwOb8Y5FZ\/Gbb4NgaqPw7MwkCRlSBJ0dJwdBKICiPMeoHIYOyKfh8xpkla+n8RtzYG2SUXI9OwNEd500uG\/VgMmfm\/hzFDjwSfBIQtFIJTRvu8TovUXAK1MBv9LlmzH6PflrjigDcvQrHha4N4D\/i0+nw+M68GBnb1lAGBOiqFeHN1o2QqXaw8D9Uq2o0Nu\/Q1ySBcLady7+uFAFMis+HKh+3YnuIZa+uT+Y0NHvOqRYVgqtvx\/YCy5rw1p7szyGGwMo94JWnKlDcKa+9XDTo4FBh8dqElTDQZqmSUkLBUvrjwiYWzLg0XGJ9zS9UkhdvmXO\/A29GK74lvNKthfY9wghf+oZMOvn+dP38Jsoag\/UvNwUj2osmNXXf9p9OwC8uoHtpbU4hYcORkdaRxQNGKDJR6q2c+oBr2WDdmaNdAi3LO6YzKABIXGtoMN7Crz4c88s5BwNRMvHU89mT+OoJrmlBcm5qNQixNSdR\/nnV9n7dVGEgGcBao7M\/+LwpQ\/vcfmQ\/8mVw1ne48vBhcqFd\/NxQ9S15mzBHvzO9avca3aoKCC2Ao1Bcu7X2h7UPxnuueHhILRotZQNbCeihIGz86nnHMiOzt0rx9MNktJ7zWOWt6H9W79E6wQOaH26a1LaQ4awkcdHKiNpIJ4x5\/mapg9oXyPlPngxF\/n+6ihXvOmFwGv3T5r8pcNJQV3hpb8JMGywiu9CHQsvNOkdKnftwszkGuIRuQowyp+43BzPRMH2xdT3NkTcYDAkrVycB1rhJ5btmsfED9KMAu9vJJz6tqigw70eMmJa73+RYQLlYJUd\/XcRzH00\/yvFm4TXfReM1wtTgHLshNO97f146sZDVcqqbrgf6Ek2jekGp\/lrvnm87UN77ytbvpaRQOp\/59qzftEQYvFl7\/wDhagwo5OFfoEp08WSJDDMOPhdIYqEu3nutxSUDECl5otXAWGIk5EnxXsC2lGx8d0gwYMFG+a+L6MfLcTjjo1ty4OqQcd98dxzC5NB7cq4PdFuHFmGDYN1L5vgFde\/PapjLp\/1\/HFca5e6oOl2NbwX0fQjHEgHwtybO3sWj+J1x5ZNZwqIKKM2xLtHPxIOnvCpMDBggdXHUqKcZwtOjl9Wm69yHb1X0ImDG1hg0W1p\/ltoBA18JyLOXSzEM49lj9jnxAA35xS4OadwgTsff7yn\/DVt+n7aaJTsM6jmgELw52tv\/8YCh6\/81+5pfGhGHz1YO\/3cufMyiLpBfHNBmwYHVz4aFYmZrued7p2S3xoJhPNye5UC6cBjkxNFuc2erqO1FLeuSoWVWNDbIV6AZrcjVOBECa6Xf7ft+opR\/Ch7MKyOtw\/3RCY2fuBrBddhUWvhMjbGXqnKE\/fqB1rgmkbOcQbGPkseKVtfBZHV63TGonugKUjmg\/ZfOvIVPxg+ndYM5Bn\/OvyPfx08XHinnLGrbfY+Y+5waH1+8BiePPDIExzbgJ\/\/M+NFWA5a\/yI\/Gf01jPNXByguDusC\/RUmQfGcfkwP\/SZ89VIfNscviLtxqhPsbP+2Rb9gYNQc5ykHlV4c\/qx7sEa8EHz3nt147ylpel+Rsk2Rr8ba8NsdlzyK4EqCcga1nwiRd1YPHw\/PRLrV5LNQuw9wo3Pd4tVaPWAfHD4o96ocP1jPN72omwbMbHnZCftOqL1NkDLfWoKjXR\/J2cJJMDYg562BFOBZ5OQb7VKL1S1j+XLF7bO5VMjVPUG1p2OWsEonxN7MsPnTyQZ9pTQVA3MSigU+vn\/ZsxtOCTn27QnlQE+JTaJ\/OREp5la6xOpu4HEO0bj6mQWFHkm+10MImBAxkLry\/\/R2gvF7AoZZwPzNodEJceho1up7bxqH7fkuPJm8nwXzHut0S0WX4vahlYK3+8mgrKlseUCoH165NjZfXp8F+trXHJs0u+BT9iqRUzvpsJrxM9DyfipwfVrwPz4toFBlzd9v1Qptyhd8a1zb0H\/MXWXt8n4wqxE02s8h4G7vIxc66WnA85mWkRLfiXqC1pLlH9vwZNsDZ7W6YvDtUch+ubQDB0Q+Pwvb2fcvf212PxQ5s3fj6fMUjJ\/JW\/+3r14JsFhrm92P5po3UnU1SfCHrfAtLqwDzIJOd73pomOU64Y7qYc6Ye7RhXaXp+ttSoXj3vG6YWzr4BtVuN6OZzQkvC\/bJ8IJUfG\/heQR3NnWPjpEb8EN37QDp0LeQ+W9XbYwPxYjCo5k\/piuJ2f1vDefuIutXRIDacm+XnWiPf\/0faXZV2\/wvdeFI0a6k\/KqXTDknT45UDmED3VVed98YSODq0udzUtdtb\/yTNtbFlobrTc\/7cLA2T6JZI3osx+KLDRczOYZHqThlL6f6p0tXXiqXcf80\/5cVPUy1PX4XoWNmRWyt3pHUEIkkkCOZKCV7G+ewiHaP3\/vBUUpq4TJTGSSbbbbHeufzfWGgQVfz68KYuDT\/on19u\/6Z\/UjMBTzguX2ko63e+dtTH3VizuuPuo6NNwP1aPMjfcO0ZDO0V6QA32oJCRaS1tIB7vMFVuWF01\/\/5of4hYtTRg9o\/sGLo8d\/8NjB11JeSXywnL0ORvnKvJiFGZ5aMtLtLSHTZ5AKd+ldfradJC1AeXjpR+As0BoaIV7Glj0m7wLV6fB\/ak86lpqOYiQlK6c7TuKE6zDCw9m9sPzraOhF3ZWgwRBS6ZtyxPYJt8TZkKhod1ZZSHiWyIE\/BFnMV0i0e18aYjyn36cOFV\/L6yuC97dU3tw4OgwkoakYyzCqDDr6+X9QfrZ+RQ6Jrud\/mwtRvrHy6pzrbzHK8PEApOdGYwk4uy8A3SWSDa9cqJhUfxeE\/UnrRA6+lN9oQMbfi5kV7otqUZaaeynyY\/vcfYcubr0yVTu6VL0Wig316gl719dtig6NxGXlOPjrZGxuwreoP\/1d62\/pEfRmvhbXJa3Cr6XKFw9SGQi1w8TJc2zDhuV1EHWhGdWZjMDuX6YaOVA9ejfVQGnuXmdxnYqa4LJHLyyPteR8S0fpO3WFOsJMbDFherf9J6NYSfln\/Xx00Bij2bWyujp+pirizlmuTdvbXwfzJNaajmhOIh\/Tn4fgpEcbLjvu7hPizbri4gGXD7G7hl9BExw9RG2XD0OJ0zhnK1ILe547MzBH5x\/PtXphA8lsdn1mDvp85jYPQCzeiXBeTceJ\/4un9ULw6xe6ZvjWpbv4no0PuCweZMbC273rWtVtqeheJ+nSO2vSnzlr6JWQmGCFddn1TSOnRdweLoukJe+l\/SbBbnhAUqrLGmzcys4MTO3wtnn+MjHMD4qkgU1VyeUnY6mYy73uVuJ85zgnGFA35anTXbi6eh2fEKAuYgFhnoJzmv9C\/BZ6eXt1GNUFI8TMGn2bUDG6uPnXB2rMPMzWSXfloKxXitiD7jVYnJY1nY+kVL0u2Zg0JxOxeFjhn5PhCrQfEXn4tCYPDQvd\/UomNeD3iVRtONDdbh5XcEW9nMy9BGfiUUE94OMdGm58HomOES+uvE+rxca7u7R4qujgpeg2aaTTxjg+vOYYLARFZQUTajdpH4IXv2+Y2ITGwaOKmf8tqUA33sL3viB3unzeaPctmm8kzmi76Sxqxs+d8Dnpq1U8HsZnTWyhA0CGxskbz\/pATlnwaP+kjSgf4uKe+rYB6YCEofXnezFS6sZqGeZBcviPRfxSTCRtfN60of6XsxMV5lqibyLKWGnhqrKmMif+tj2QxANeRWkq9oIMVD75endiGdMhL0qtS7mZTCwVFQvU6oftB+1fQqJ8MUKV\/0zi0bL4UCow2be7n5QycrxO5maC6pWjgQhk3ZMS9tndjCmHH8GperdFOdA0a18C\/aWdox6V\/Z6i2c56spQTp0NHoZxWRsjtegmpLo0j\/31RLR47165zX4QFnhtXTJvqAGVD9\/YrTFRg9Zecmd3VA2DZTb\/ll2fSzHs6ad04mY6zOoTD8+sI+Tm3sL+mXUEipeiRrY65mOX7XOnq3oM8JrJbQRmTU2qfBsBwHr7neN+PcjuHnO8fZUMvPoa+iW0TDC8wZPMpziKZxZGTCU\/zQDe3hWN8uTpOoCUd1yXrwL3ewweyH+aDoqMrupk2SEQunlwGelUCdIWJV5l3y+H6GvrjmUFD8Fc27HmX\/ersWjF9bNVTQUQ2ePzI\/7+KCz3UCmYrKzGWxtfSqfrlkK+pPPnT9Z0iLj9ytjqTy0G\/VzzlHGRMdt\/g9k8a27\/Dbj9Ovg906+DRm5\/htvfA64PP3D7e1C9dOySscQQnKkJ4Kip9YBH3lji5FQjhPN+X1PNT8OOP26qtqUEXNYolXn+AQs359fKZJ2jQ2P88MTzp08huLjSX81\/AJVlb6LAPNq\/638pkfQgNw7OW6hxqvVGGYTPzNmxKuWHvW7cCLgvX\/Zl3sIaUBi8eLRgug607JLRtR0dBq+U5sYg1xJw1lywrEqs79\/1SdB1A\/5K+P6L7rwssQvPPV35Ma94EFz\/SrT+OZcPu418NsgOd\/+7nnaAWLVrOwNkl6j5y5wsQ+EvqxjWRgz0s1FeZfeTAV8cpD8tf5uNSgoCu+5Nn89Cm8+E\/Wkgobf8FXMiuQ\/qzx2L+JpEgIMpNBH6GAPzOw7m+KZS8a5qktM2\/14QcvL88WOKgcvjL3u+nqL\/y+mgxN793P2Ghvedll77\/Lcf1eRWhR7I7oflnYLEZz7JGOjpUSjQxcbrnp87nTy7sMjbzDnXnIjXuoPHHvLQoEbPprK\/rwG\/az8wXHiyFfesJfIJudLAcXiDaVBaDQreT\/OWft8DodV\/BF2lO7F2R71I4kY2nqffnPxWQ4IJxpEvBc+6MC30vt9FTSZOfilKbBFnotaOph0H8uuA583r9RQbGkoW704p9Wbgkzknnz7ECrBQX1xWU96HYaeF+1zuknDHpjSPjzKdSJ+0leJzJUD9jH4Z\/qNfBgubVQf4LEqhhOpx\/JUnG\/m4+7Ac3f\/Hn0wGzJ3RA+Isn+f5wt1rV3Qz4SLX93V2fzvcIGVSaUuHLQVLpD82NaLBH\/ET+eosiBK6\/enZzw40Kd5VFDJOh8+rr5bUvWbA6QemH\/s1OvAQ+bxe1fR5Ebr\/vM3iQjp0\/Ti+3amLgUNxN2LoS8twy\/wNxZv1qJDidMPMrZ6B7qWl80nLspF+44lZ7XQdxcV18B9cB9IzuA7+g+uAVZh\/sfBBO8x7kKG45lM\/Epzi2xfCIEzN5JUAN68EZ3m8AjNzYbCemQujHNfP5IE1T9bKV21grZ9sZXubimZBxpcu3R+A1MiijWZ57ZBwVXaHuQMFEzLrpBcf4kCYk5BGnTUJUsx+El9+68XIYPXGOVYDYG\/FTI1THUJNnhXXT4vkoZjwJppPcDfEbfc4LDnKxtomqiVbtxBzVu\/Q6bUig8SHM12lhmzI1VyjhkL0WT9k4M6\/4D\/zL7j5v3m4OJuHqzTjHw5j\/+sfDqEzfE7Y9798zul1\/dUgZogIhntO+5tdHkTNW09a3PZ3AMHWRuTv\/G6QXOKh\/3WIg+SFCQ81xNshUHT44nb7YowdORs\/L7gTNz3VaXWypmJiyRXN4U1lGOd80MCC0ItnvtccXTE5ff9Sr10VyWaD6FA4U5v1AfyZUSeubSLgJ70j0r3T52Eep5S6SzcbxNS01HjDqrGdbMmjJEiCPDnXk81HmjEo+PTiIFMiuv7RV3hH7YDDhxvqxgfb0OWC3Wnje214RMC6WeHpdP1gElhwJ7QV7xJzNdKVOxCDmsoDHdv\/H1dnHg9l2P1\/lSRpsZWkVYukKKKEoygqURLaiJBKkoQoS0m0SBQlhMiS7Pt27Ps+jJ1ZzBhrZCkl\/TxfM57f05\/u1xjmnus+1znX+Zz3B\/7Wrq9uyq3Ajanjp9Q76\/FYRq2X21QzfFXPpqzwqEXBP2pWlml1SExzI+0mN2BvmIDsPqMmaHhRzV5DzsJWq77xO0LdEPVgZOOp\/SRoXE\/Xeh3SiunPjO6l7COBpXrgxlGPbjjjk\/3Dak8Xrj9bJXdTtxLPaTcFksoa4IsC9XjYFxqoyZVd6hasx6Gj69v99zZC54uPZtcf0uGnUtvWFM5yVE2j\/sx93AD+Gyn5f2f3QZ1Tn6e01tShhavl4GXlOjCOSPcNDegFufvu1lra5Riz7Yy+ako17NObtu2soAO9PyVZ7U4pbrE6VLmTrxT2uUw5b1KkgW\/jWKW+TCkG\/e66j5Rc+MltvS7KqwdW6v9ct+9JBU6GapHy19biuKzExb4dFCwI\/v7CfkUNSgbkPDo4UIWpngZnraq70XSuHgGhuXpknkPF9rayT\/5yPxzR+OM0daQWToxcdSp4QUROndtsMtEVILr12ecVKxoh4Ne9\/K+kVuQu5ytfE8WYr6eKuvrvfBMlwIHsrpReg975uG01OW16X6cJVgwu9BkupGN\/T5S\/igQJT\/EKzqyYJoDyjFzzpC4J+H7xH0y8lYE0RVtVz5RO7HU0i6wjUUBPya9Udy8iL0XtppRyNx7tNNB5F0eCPxHRz5vjSlCr6cyB9v3dGCq5Ry8gi44SzH7TDyb\/wV10q1RbaS+zXraUP8rkRbBev2vu9ch6PUvftWqS4eAqfwVZ+q6tR0Jeta7swXdU+6TVoUGg3lfW+3i2\/mRr4YPnhlQctD\/mc2QhHf1VD7HvbswE8bKzlFPNFPzl25rkI0pF3dRqTx3fHHjRLO+TGUDBv1uSonp3UtGyltM3cTIQ+hXs24P6CXDRUfjPjr\/pYLw8jW3A7C0Y+yerNcnVw\/KNLy64fAyG3MInB44K+8DPace6i\/wE0PFo2ixilgqePbeWKOSlA5O\/BNJMrg6TvwTp7+QL2v7jHzEZc+dnXg5oXSdLvOujQ\/Si7\/788bVo5bIikdrajzYXo49cfVCFKmpsX8QoVaiR\/zEXzAdxn6D7VmWTUlRUO\/F7c\/s3YJ4zzPNnjJvlxLeN\/H9+jkxejduJhPwJexK2c\/RJcWrQIJeWGjS2m4zMfjr+00\/H3+0JoF9JQsFRk1IbfSqoSvYWcSR2YuFiNpF3Sd2YwfX3Pm8EBdiKOXZ8cyXh0bm+D6j+b98Hh20s1AwSGoHJVUCLFknqgqohXHVJlP+wcy6sfrlcbZFNP4xNmQhJPyRjLXPukjA3dzn\/\/+zVipffUpgFOr8\/G0Wc7YNapk9u3qKDKqPsbdgscW5bEmcd5O358yHKg4CJ1Tev+Hu14rf06U0OMmVwQUT14bBjGXLc0xFobyDiaepK5UbXYriwRq94xrwOF\/rlpNmGdID4XuHKo2kdwK15sZNwOQe+L7PKHvbsAu2uoZsemi1AmPiu8Gx9Gax1XCAl3EECoUrR9d072sFSKb3InZ4LWvfcvexVGvFD0SHb66L14L5FNlXfrQU7Ni45GO1CgRlHh61alxJgzPn+vTBHCvA\/O+mon9oDq1U2lKoJJsA+UdvLR0k98Mvl8PmAAhrEqHT4JR7JAGfu1liLIioMFcpLXEqkoeDTRb6vvxYhfl6qZ\/s0BxUHC1YKve7F9A9Wtea8JXiT\/\/S1lxLJaK0vc\/t7ER1ruVbvWv8gDEvO9Pb4BHXAijZ6FptkKUjeJQ1UbCLAiyP3ft25wACxR4XnjWfzjy6vs6Q9jnSknKbKi\/16iRxZo6o7JymgPeoV0XeHjma2vp43bMKB8Yek136dBm\/n\/FLRkcmvJjpy\/XWY3XfN997YreEw+7wWcefHXfHHN792zHx36wGRxBynu7Ofwzk2zXRkSBuTe2V3JaVYYuJur8HG\/B54H37raMi3Guij\/a7WX+SN6UdPnO4\/QQH\/YgVNH0YlfGH76H7ALBmtfpzcm\/RyNk9XzDR7wUGABc8yGxWcqJAcvzJbbaQdufccPHrtVSnGL3tVf8ehDPkl9INuLqtFRtWmaL3jxaj9tffH5VPV2Ltq0m9AhIBvgibOFXnW42K\/XuWX9ZXYs36neXYNAd0Xf\/fav6sUufwOH1NaQUGFtJNKFreD533cWNfl564j63qx5OU14zkkdN4fXM+pvwOKhvdvu0tg4Ms967QuX4xEHb5KeKzUijMR+cPV5xtBNH+ZwoxvOIgfP\/XE4sNs3N\/FG38vtB5mROkhnNfbgbafXZ6DuxEWPJf\/LriJAU3Lj1soKhFh2XvvneNVBNga+4Pma8IAS0vlnTTNJgihtb4U5GkGesySzcSh3n85NsDi2KS0On0Z\/kSGUY8Vox0DlZD8uaKSkNIHbuXeU\/3nybDhOl\/WksR6eMisH0vjulZZK3RDJSNNrulhCayTUhhPsGCw6hr8p67BA50\/Sg9wZ2Lwqfpum1ckZHIO0fdSeMqdQgZOsJ87SCiJBy\/JdaOt1vWgpHiH0+5gEUw0Du1w+NODwi8K3jqG16Loryn+jNY8KLD1NrpkQsFL0oq\/+N6U4ufB763tAingEPWtMU2BhpHf4\/O6ZvOff\/g5rPn3fzkh87yCMD+di9PKlRhZcGDq5ioGdhexW6zs6MSaxU+0tVeWQr3wrgucb9qx0FkqLn1VNz4Y5DM75VwMiekN+cdJzZi8bWHm8m8dmJBYsnvPhwIY9jnkx27ThTbVBiBV0Ib6788d3sGdD7US1Jmjsz+bWe054R7cghnyI+xLtmWC7HfVcVF6CxrfPd+Dil24XbxePncbYZ7zeeHmUWv73bWgGdyqu\/hxHfotnbJe6ToAmrdOidZvK4ce3nt9r5fkw7B\/soFNJhHkp+U3d4cWwR5xgS79Z3mwJt9v6qxgG2wfP7d6fV05vIq7ulf2egJoV0VkFKxphf17n5fr76sGJgcM\/uGA4ZbJLVdti0nA9FuH\/UwO8FTEpnIF\/S6IFdieoiw0wKq7kXKmwG3SpAtux63RSSzrhcRrK3ZzZlWg3\/JAj6MH20HD4QSXuQMDKGa1J7Pe1qAarLrtQqCi+sEnR4+dbcMFk7aiC3nJLD0S\/qNHwu0T7J83Z5HxWJxzVF1DMx7dH9qdKE5Cgs7OHIFLVFTl6X2VPdyC9t+JC8iz64WdbBNyaOlsHZ0msnrPUwKW\/S11iVJpgD\/fc19zhWaD7HqiG487ATPMDF1izrVAXPFGkktLC\/ScVPCs0J6tM30rWwflasD70Lhl0fpW6PKYoJLGKKheOCGidKUI3mTqqj0tIoD8CpGtj4Uo+FMg\/ClBtwweZBmGjHkQYbvmYs3RIhJyypu8P15ZBpseOwZsP\/UWNm3aJJgwfBcffP2unpVDhT2quQoK9snAmesSm3n5EYxPMqiJnhTIk\/MKXPrME35SNeszmp7jl8ChmJAhElA+XNP2MyWjRX\/cB8F3jbjzNYehxKYOvOfDKTmwbXZ\/dxskFHC3YUt6Uv+DgDbcufM6h0AWCXO19hjq5NbjJ+jyFSY2YdYmLorZbJ6g\/u3GezapZtS69nzTDa1G5LwmeIa8ohPqvmiU70zPR+tt+aX2K3rB1PTE2OqTJOjZFRMmFVWGPapPpALUGaDbp+Ino94F4yIyhjmBRThyU9gtUrUP0uGvgx9HKb67JmsZM0jHwuhH54p960FWjOsom2IFxvyUJhU2dKOvlAGbyfcmjHzRbtHCNYBD\/+fzks6aX4AXPVdMZTnpqFj1SsfSJg3UhMR3lY3Qwe\/9HfdfL+g4YyC5pDA9f\/5cUT9EIGfpdypCTsBhqcBMKGSc9ft7ngaqx7QSJ3lr0Fnp7CjPrijQSf27Jdh0EJi8aPyHFw0hqa154oQ6LBA2+MrhGYbvKleO6B0ahOKgiB7dA+kgf0r9450jYTidRpGa0E6EK7QuNu\/2YvC0IFnmuYVgLPfbcbmwCOB+Wu\/VPhvP1LJoavczatD4whkOze4BdCZfM7IdCkAxUiJxjcIAWAivoUu8I6IlGxXIo3agmRzpqbmhD7TjFjWvv9OEkzXW4VUXs3G1q7dhXGk3splagMp\/dMBs1c\/\/Bpfiru1Wy5pGKJiw69MvnTfdmDcubdA8Uo3HboQ3TW2l4vXSRaJ1hSRcVzQiMHhw9vrbB\/xRWt1osyN+14YuEr45flMhxagFLl8hnl051QiDrw7\/uPOpCbboX9+svrENPkf3m49MtoJA6wFGT2QTFMlE5UpZNMNpUfMXyzUa4ILtJ53nNm2gdTIitEKsFd5ZOYcPn2yGR3n+qjMObcAw0MuM6R1Ca8q3g34WNfO8Qc7GLQFfjw7h3vDQGV+ZBjBmzn2bXY0JWW01hJeWhn+wcKsG1px4uvbK2zs7B7D2fmoAh0AtjDqtCppoKIMDeld1fK4NYFrwzZlO8RoIyixt70urBfY5\/0Fk+g\/+lws951eIIXN+hajI5EjfzHDurvvag7FaxVIaVT3425\/TzdQsB5h9DfynrwG6c30Q\/KcPApJnxl2UW4pRx6O25s4gBRUPk70Sx2ggMzHRWeBSjOkl4Ysf+hXgfVWvxyoS7Sy+6zyHijUXxjp3YnGoWOdOlMvgtIpKBsVNppYLeKrAaH3C34Z3PTB12ZQjfPUQKsz5kAKL387SQ47873kpKuquvBiW2Y\/KRS42ktrNMOB07rBEazFW+Hb2vd9Eg9jOx9LSa3Ix\/evmvrFqEhy8yi57azEV7vMkXjKgFWJy4EsVT34SvLlfc4b6hAYfK8R14gNK8KDayFPFs10gI\/xjdzIxb3Y\/2Lm1IrUV\/RdVB45ZEsHdXf327qRCYB\/9aGza0olbLVQEs082wcxStR3Z9uUQdrA6qNCqExt0RC+6jrTAlt9h15MDqsBePEbpyO92VA79OXl4shFWfdSoTVqcgT\/bfviQzapB7s3jx75AgVh7t7ChzwRQUTCJf6ndBUtoJ1ZJKVPQ7Lj0W\/Ul9RCZKXBjX1If1r+Tn\/hREobHbx3y8POrgUxPfd0XVwbxYu5YQhMtBbMV7AiiglXw4uC+4K9HBtD7FCO\/fEUgqlwNtxZ7VQv2Jn2JZ98y8ID9rXWBv7xA7BaX64OztXAnivBCZqQGez+MHtSZGYKga4uf6xsPApOfgBeZ83FM33nwnPOdx0zmPB2T44TCcxwnaGNyVsXYXt52edk7H6+INn0HG71pLB7U\/Ot7mXpdW86ftF9vaKjRbInexQGw+M8TK45lPZCqabxRkUGfv867wVn90zsKVK\/dUvt4Nx2NtIdovOuSYHXLHuMX56jgZkG\/u6d3GMt+8XSVHC1g6WYhiL1qxuTxMHruuDat\/iyfpZuFNk6qrxp0zXNgWH61\/\/TrgdWvZ3KfsOJ\/uU9wybV2UdtdAkz\/Wfjd7n4L8ry03axiTcYjd0beHd5PAH\/3DceP\/CKglPVQysSHLty8vHpJB9ZAg9ueWHpbM\/o7CE4khpHwdqjwUOjDfHSV4GwqutyAIUeP\/LXoT0KVPlmplO+FaPCelyAcXYWDInIm972y0HLDGt9zPwuR81NBavz9b8CaZyyf48wjkzM\/zw8UatK9LjAcCUc+Bd3\/1EJH0obFz69452KUcf8xV9tPoHRu76DMIhput+WvkmqowFulvj7ashkgPsixzaeKjnvYtRiXTcpn61wqZWXtHeDQJHltCaLjMB\/99BO3QrQdHxcnadZjvFCVZVJ7M8a6KD9P6y1A4Sot64jrjWizaJct6WQDbtkUfxZvFuC2jzck\/piQgXvF9FO7iP55TkUN9Uar3+x1foOqx2Nl\/cDL5F0IcfhOZQd2Q6ZrYdOLxwxwt96o18kbCQ9rTr5vPjiEOQ6ujyMXFKB0mbSVtWQLcEmXbA48gsjSI+0r6g+lfPk2+\/7D5DGlovn1yewjA1O\/hP\/olyDS62KCtEMxRu7ykxt4Hg5c7YfXvd86BKclLggyzGgomtHr8rj3DsKgsENRSz766H+nZYbSMAHaPLQKQ8Dnjl\/UoZwUbL23TvaLczJc9wwYcFIsxcbjx8Mvru0FtvHRdlLyezA8cYGqOFvnieoFb3HWpcGjmekUFftvKDLHRZ\/\/fjntDhjb9dJxdevj9WMvimDk7OOLVS7XkC26MniXBR0jzbs4FN1SgU3Zhnyu4yNmUrSzEsd6UeHwaNuFokR4ECCnfjwwCQvi8x3\/mjPwivLLpwtiCiBN3eqWa1EkPkukjPEMtcBW7gjZtjInUDknJWZe8gVX6US6tQe0g1\/36bHxL4lwJ17o2NrgaFSzN8hOIHTBBe8QdWOjdGTx4ad+7LO55NsJvKENwgp+ieho\/sdQ\/V0fmC\/IzRQ52YxTDcn7XfflQdsnqfGHzr3YP8e9Ryb3nsX3Y\/HzkcnPn9dF7MuTlRYM6MZHrxccjxWio\/iPMvmAkGYYf2dg3rWiGS+U93GnHCMhd5XE9oH3PaCiOLzt9Esixlv+4dGt7cQZhsmLG5mzz3sqh76lQAv+dFlk621BZnHLob\/8TZeyahPq5E8al87GvWnfU5z+mXRwFnRvvMxBw5P1Asva06pgUkyaMnq1Gax5aZVbW2l4UK7frGh5Ndz4vEVB6WQHbO4J\/evkSprXS7D65rxHRhxdM+pwY1z8t5ktefN6LXZypXRkHAFZffbb\/A\/PzcgP44iHRoTiy9n63Ov1Rp\/lPfPxaqWIuuTjuHbctTF1UVTafzlX5PdvJXSlm\/HFyTiiXBQZfGW7Ne8r9MBq3eanvFQ6cJweCvPypcz7SLIfuba0So8Oh8y5twjto8z7SMaG7Fq1nI8GOxKd6mw\/dqHdvQKvwPsU4G4KEIkboUAYQdP1tGknbpde8f2GKxnqnrU\/7811g\/FXtBJuoy6UW3dcoGqAAh\/pZxxNBztg4WIubm7TQbw8t57hcyMfgWO4gzX3hNJzc9zQM9f3QWbfB5h9H7yyOPbBmUvtaHNZlU0ktRJGwtbslsqlg2yC5tnuLx3o9uqPsvbmBhCpvFtBu8AAotFXiacmrWgWlvnqvkw9uBKeU3foz+Y5z3KeDAXR8P4Zx6+L9duBb1r5t05iOEgOT6peNe5F96g1gi3LOkA\/snedWG4yZKfcKtIk9+Bm+yexddJd0C80SpYOzQC7nV\/vnDbpRctGamE8oxMY6xYmy51vgivuDpE8P3uQ0KT0ZbdnJ2QfW8NlNLvv9JuJdzZdJ0H18tCqyU9VyBe3sCBPkYwDtTmLjBPawfntqmfTZUQ0nziYutichMf8Ql2s+brh5EycR+auSrwguKFskVsvru4pF7+xpBN2drdfyuvIQxPTi41Wkz0YwWtnnRXZCguP5R\/i4s1DY+27YvqVdOQNiQz+86oVvczU4h1oFDSM1D9m9rUKeySehb4bI+J2p4HVcbwUrDN8TrRMrUeXw0ahWqMv4dcn3wvU8j5kzj2hpBpP3Nah9\/McBtb57YtS0e3qZEPMkJg65O7Qi+xaNrvDllDQ566CiI9N07wPjnhAW+Lr2H4cdFQwN7ncByw\/L8maPbzRvmX4bM5PAVh+Cgvn\/BRw4urHDnUrBrB8vuI\/XfIJnyrGrafH7o9tpcPlM+r9D29T8Em\/8bOapZXo9vDHmXe6vZB6KinqqzIZk39uWOnpX4LefVSDr9cJyPQXA9ZcQJ44sVLfoQm3c9OjNniXQVf90utHJ\/pBtLtmkbYODei1FqVr46vxnZP529x9BIzeZ2jepFONNMFS8db9s+vho1XHp+29UDTnswksn80Jpu6O6bMJLJ9Npp8FMH024R+fTRBOW2OznrMBwvJyj+UGEVH6YpdR6K5+8F5p9ycrugZyS0KP1yY3oinb9ZTKgX4QinncTh1vgMip48pEIOBgOD87l3c\/ZP7c3Xf8YjXse2dnahpJxj1aRdVrGT144QHXqtPby2Byw94t+WwUNN75UV3Fh4p\/1hMP4Lk6aLgvSWwop2LN+JG\/6R49qObgrT9VZQemlXunoq1L5\/W9DVtlhnOqnrD4nKx9Frcy52gS5+ZogKXXsvrI1XbK\/D24By9ct+phGViZmS0mfRvEJZYtGy8f6cEHlKQdwvx0lg4ZGfITuIlAQcuY8K9tTlT4Ptpy8cTfRvygs+7r4HkGKFXnXli\/mIR3\/hyyjWQrgvun1T40rIxg+exA1WWT9SGUsvn+6be5\/in82z9l8nDgFLN\/utCBZ7JCtgUoq\/rWLbvMgNQIS9dny5shtjh25w3BJuBWqze4RmbAqnVXSmoOt4CMlxDbQZkmFvcSmHEVvOqNlwo0lEKE8alIgYZudDzwWkR0LxF\/SXSrLZGtA45rrpEblpLx9+DApFRwI\/qGct\/\/ees5vtF6svPwbSqu7uArUxLrBmeHyfcJ9VHwIywu3EGbjHJv1Q\/09pHh3WMeKWtCNNSrTh3jTMsDQu5hi0GHdrySe1u3xdkZVq19V6gqVgDmAzU1HR6tqK769pbE624MzRxdTt1WC4aKf3nTDKjwVI63hvG+De3\/Pmi6frQaFgbxu52f3U+UgtL2N50oBnXm\/WHpJBlmP41qF1aDedkFcWHHPqAzdZKWl\/hOZq8KwyUk8X7fbSV4S8u79kt7H7B3lcoY6bmjdckUxdOrGm0WrPtwUawf0h\/Rn7q7JGPlorTjwqM1mNfchdS8QYgdS9sYNFmPIYS3ltYRfTjzbsnvesUWvLCbq0j8LB05dx3gJgyScF\/oe\/Zzj4m4tuf0ubzQBBYPdn4dzvnT+eOeOR7svA8dpdSi72dkFLb5hqQHT+WCdfZVGJIZQtKvzKjS430s\/Sew+pVM\/2Vk+i\/Pf7\/qllLEyOo+VBof5mF\/2Tm\/ruKf3n9u79eLm+b2d7gaoCq5Z9tsPf8Gr+x70o+1i9tfSRQnYX\/eIzH+Wh9kzkHAP3MQeDy1\/JXW7UQoktwV2kZtwR1MH16zkqKuUduvkPoXzQbtmnF7xUPNZu4BFCM8inYP6cNGhZfXCb+r8ZKNwX7dzwn4+XY7h0\/OAFYFfVgnV0DAZLMf8pxLE1E090m2Qc0gCiW5hD9TqMPg5TUWLn3ROHzqbNf6RU34621rxJ5yMnjmuirKPaRgMNffUw\/1G9Ez65Pp\/p+z6y\/uzdeLZ2k46CYb3\/XeCnszjx1Rlqejb8Py\/mubWyDTvOPgtFw1ColPi70To7L4e\/jg+Re1882l6BrZorxstv56bp5jbXO3D9s5ZIl2q0iowq9k4qdOhj2v08zX5bXD7qS0G6Hvh+EX08+OOa8EwbceNW21HYbcrDhBHs8K+MbkAg1rH4lzZfsGAnUvllK\/F4Ijkwt0M97xqVDkIDAWXR+XrCiA7V55IsPUEohUETFc4BcHSjOH9bTSC+HYzp\/bzTP7UXKkuSfRhwjvnliwX2FPhf4FThtDOdKxcuD80xOfKPOfi9U3TOQVPZ+eQMbso287pe5SoI7ZH9RrcJIJMiRjm+rdx8azz+3dVg6fh5+6kanLwn90Weji1MXe8m1o\/vzQ6+e78qEHjdDypkxZ1GAYgXneyNL\/s+pcr7k6F0aZdW7GmifNpIkBXCWko\/bLPhpWR\/R2ftrdCMQAq3oLj0HUObB3\/Zb8KLD982pslXMdOD11994gNIh9r66XfG5PhwJ6fLaiYAMcWT35jI2Ri3nZex9Ln\/iK7FLdH\/4+ooG72IOrf4XLMSP4nhHpcCo+o+kqXamgQVN+56WOklx87PPkGWd1DoaOn3tMftUDGoIu94zzanC9px1njf3gvP7Ha+uVfN2gWlxh6DLts20IhQRpeVu7G0HVLnLYT7UVLiTLNm2w+4ync29c0pskobLUu+DUv0Rg19Rdor88Cb06hC1HKB1oameSpcHbCtp2nvS9ls\/w3WiOVltJG640XeIsyUWAzKK65ZbnP2KVa5jBIadW5PuypoZHqwmcr4xS\/PfzY8fWy5G\/3bvwQNYhb7MJErKv+XI77AsR7qySOyRalQYrU5ctqTZqBsM4OEgubsWVH0O3S5Q1oPP062mOlHbQ\/iApRHvfjHv+\/vEqbmxEMYlDaj+PE2HvSo6qw0eJmHO8\/1YGNwHjF7hr6Xq3AJE\/4LWQVws6vpOwW+FMnPcBYfomgyfTB2TbnB8QsPS9VnN+QLB7c+yzepNK5KhP3m1+rwXKS5LiOLa3Q1TYk6MFOs1YZNH3KCK8B\/JWSF9McarD6RurzT1\/18BM8a9fMuuG5vUYbXrbhEqIDZDZnaj\/4M\/gvH7j+F77A90ppRD992M5ZvXjo0cef0YTCBATk7IvKb96ntus06g43t3eCOpWwL5tti7oT379jNBKAxHXvoAnS8tw0cL9S3W308FM9lxY+2E663nEn\/LWY4SdVJArJZJ5ZSkQf2rbsWbdYoyruv5z8RU6pB\/3\/y30kQLLDp1R8Wopwo3vFv1JPkaDezXAG9xLBY41RXWMqXwc+rHbUnesGwycnPffuI1ge8BSw8w3HxYHP9TbZt0Ov+Lv5F0uzYPGXRuP1AdnwdbYXR\/ObCKBgtfZzt+fS8G+2SwbzYqhKnibeNtmBjB9r0Ax8cUHESIRiocJ0RUpDKAZ3NDMFyYBa92OOfbxrDOhgxhnLKd3bTdsSguuTopqhMEqP69lU3SIlH5ZueVnBwzqPv9BvkQE5yDalYJjvXiX2ZdkcQ84A73fHuBmYHJtTGOiVDfLR57lWwH\/+FYA07cC\/vGtgKq5uAT\/xCVgxiX4Jy5BNXHKqFCEDMqZAvSdohTQz49j59LphpYtixfSJqqRr0p61dqNHXj980+Ri93FqJD4nddGNw8btP5e4lvWjJPbrwXHbizE7ewTolHbSjFIM9SQS7AdZY\/d2W+YnoOcwpe3NXxowmDd05l9aXFASZEyRGodSru014XxzN7\/s20hOWdLQNq+jUuC3oK6gaKRW22G5s8JWfdZ761MtWLj0Py5Det7yV7SZ5G8c3j+9YLMuPGXc\/Pyyb2EeV+k48y+TDz\/wp0LNlXjQ2+i58A0BQIKNpUNy9HAIsGeO+JgPxB2lrzpkmoDFhdxi3TnwprZPJPe+tZwMqAJdG8\/lHKQacPsK9f28rpUgOjQITlxmU54q6TXE97UjKeIa4rF7nViXqu5c5RCE9g4Sfy9ZNcLLI59MzNPvsXk2MuXZjo\/FxtEVl7NZ8W1JDSrHbtOf5Bu6x9E5hw6Ky\/F6CO\/hZ+v6sdPAknpsb0lEJNnLI+02byuqr2uta4fh21p7\/elFgC9hpR8\/G0zmgXpJ17qJCPTR5VVR8PmdTkLVS9RkemjCgNMXdC9SbHpHA0KMn1U5zm64hkaj5X+kPBLa+CGjb+rINNFQP+7ci+w7bw\/ZdHdjR5rimfi++vnP28yW86BhzH1uON53EXti2Rk9etPnqcljZNy0HzHqZl3ZTTcElzYSP7cjAGDnldathSg2o6Jy\/27ZuvbFON1qnwETAs3G6ATymHCSqOkZH8P3Bfu833k2gMGiy12P\/hdCywdEUsf+y6nPn4VoRYGk7jPRq6gQiG5XXm5Fw0G6u7f0eSsQ1c+I\/Y9T8ngH+FTeVUIoawgdNFxJKDNV7tpO28y7Ao5mVDAng8UXy\/u\/\/hNGsev8nFT7gauvZpcyl\/z4MB0PN+rY7Pr97IcdF0dhgRmHapTreCap1SBNu8JNqG0YWD5N\/1p8+ly\/JMKK0hBr55KzMazZaqpGgKFeMSha7O0XDBoD2W+kh+YvY\/7w\/4sflSIH\/1JcgbXg2Dvs2V3rDl7QbDRnNhRU4F+HzqTncq9YVGShJcZFx14cUJmr1oudvurHfU0DMftlwPunKPSoT8iOOtzZwmaTueW58R\/Abp36ck+WxIqlMZee8xLRY7FXw6c3ewOKbfxsMVmMq7gcy0ZH+7Bh2S9LPahLJQxWfXlkHMbZMaeESkV78J38eQ3sflpOLzc6kn4pWbwPGZ4qOprNyZFvP+4\/mYyjgTfTdRw74Rp0buqLvdm858\/T8ak2r7i6qLkot9bO+D3L5FrPY0dmGZZnP+SuwM21Jdcj5TPg0dz3Eg4kLN4ERc9A2LS9ztGvbIFR77zA8\/vU\/DpqT8+742CQcN4JGfdjWg4Lu2213pzD5K+7LnjFpwNF5F3Tf6rdJCMjTu+agEVP\/aaW0UvICP3VOOpzNM9UOKf01u\/vw2SBnbuTfPpxAPP37\/6SadAzp+ba3nXzNaBR7rfkx07cbrok7KEPw0YjFvLewPbwMzlrqFjQDtKk1Zc5PalwOnua96Soh1wP\/E11woOEnJqnFhb85cK5x9kXBk51gW232SMQ3\/3Q\/bbjwWi5wlIGXi9+HtMDayjfIp+\/isR3wob8r9NJIOGu+NIxFEqeMs4Pvj2sg17jlzmXilUiCUL63c70YigneaXFL6\/Cy9smnCuMyvFNtdThEOfG+Gle7sX6VUGhHJN7jxJpQJx6KalcwAJ6OevGNTLd6Hxmt6HO5IawGPPU7PzS9KxYPLi2\/uL2lAlBxgjPg3Qwp2z3qY9CYuat1JMtTox90Wuio4bEYbOPfCeqktAAUWlswsCuzBH5LxLum4jjCSUneVStfrXz5HV70PRUNuV1Uo01H5\/3HPv9jIWP5\/lI4Ae\/+sjAGJG+pJuioid\/RRVvqh+4C4n5FgodLD8nfE4My4Vzs1PwfI5H+f5+BMx5+MMNXO+zxjLjFcyc31DkHdeE3NUg4pq1\/IZbQIk7LO0z741WQ\/P1z+Lib5BQ3UhafENYmSc6Z2K81lGhJ+DHNMyUI4GmsVS0fnJGC\/fwLh8pB0e6FRfXdBCgxyr0tJPMzRk8RBSVNhdvMh0EPz29sC9\/\/Rd53hHGGQsQ+q7T4NdcV+tChJp87x3LsaBXPnUHtD8KNTydGXP7P6hJmXnW43ikyFy2\/R6IKed7fHnQir+PbZRQ021AceW3Fzvq0EFI4N9vE38NDyR9sk5a6QOb4eedOPdlIFOa7tkzytHAK\/pFJnqxQASabtu50QPXlpqL1Ozsxx\/Hk\/kq1nZAw9uB8Y\/S6Ti5DKpY2F5Bbg9NOWe9noKxDmkOnnGpKLzNhOF5Umu4KH8rFzzW9js9yn4p1swFXtT+MeDohJB+mDR+LuP7\/HGZm2lRy5paCcSrOizNQ7MjpE86l9mgFlLEp9d0A1sIR\/7VvsjCtyVZU6cFY+FrqmUHMJQKo5tSR9wC0eIFW+sdbsUAsZ+zTuq17UA5\/OpP2+\/VYIisV16cLbesZ+7z5jNvM\/jzDpu4Vx+iNfm8kN0YtZrzHMn\/OfcCZjnTvDPuRNM8x\/Q+LbpPdhfTayoOVwE\/PXnu28FDULery8WN35V48dTD9mfrciEQ3uWM24H1CN9RWzQqz8V2De2xPxcGkK05cbXTiKVqJVhUHjyUB0mZykYebkHw1b2x5Lxs\/nz0tf3bXgFirE+IfAA+UsWCHLK2h60r8chzpee8LoUBV0dKxQLP8GCrhi8f7kOS8ef6Qt5ViDn7YZJTaoX9J4V695p1oj3B7J\/uIcnoanDlnXnDzHwhtebDY29BHSYO3dF5rnrPG+q\/A8h4HlyFI7\/emvrH8aAggUvr0b97oYV0eYkv7t0\/J2S17XsUyMsCxVKl3crRGb\/C\/7pfyGbG\/HiGdM8WJxysk76ZTtMP+aRnPHoBf5wmhUN0kFs4xN570ASJLEtEI2KZ0C6o+GlH+pF4OqhVvVOhASN36ofVKozYHUCtS3nWyG0bpJevpK9A6Im7hTs4aaDzM+Sz6FQgpJS3B6dxxKQ++PMyaM+L6Gh6\/LMqfx8rJsy2bdkzzXkiP0opfvyHcbcOmrkfrUKD5wYvLc0JAwXSc3E20t8gbPVgyRVu1K84U9RTpeJxwZJukPdRDSm0s95BExWIr3mazmvUR5Kll2Q19j5Ej9Z3u+0kHsD5U98eZMO0EDRmnPJdiEafB\/QkR6wtsdrneSeFnUqBE786JH0oUGMOuFQML8X1vvvbb4+W194ZFcccLXoAWmTvA5yfz2qDbg67b7WgJJXD9V9tiaCzlGejVN3O1Ht8bLVN5WbQKzfRlJqOwmiVl0tH\/7GgNi2Vqs8RhkSX1lMGvHkwK\/SZ+8vxqajWaDR9NN9ZAgtN3DRdCDDyoFA\/w07SoBfP3dV98kybNmTs\/UlRy5mL1btyjUpAd+qBe39mytQb52SvsSj2X19WuRH+M8qSOHlvqb3oRJy5fKcUmzawapnY72e5iBYqm+UWqYYhNMCNgOrs6vhx0KToP39BTj8Q3GNSSkR2NYvv28Rfx30C9fTRmuy8P5Yc+yLlc3wruShWFRUKnTZXzbf9acW473jDCgjVGDpQ3Y5fb3AVUjAG3co6\/iNq9G\/qF8wwZME\/fsTSrYENaD5F8XH3LP73bHcg5F8qSSwX3\/w6gUKFcYLjCJcTrTgZJJx04t9H8F0f+2QrwQVTqtoECviiej7S2k0lZYBJQu\/6Jq\/md13V39\/cHpxM5a+YIteU42w5K64Su2TeiTKnDmX1jRbryi\/7qwRSkAn8aA4h9nfnzJKNnj9mQwBV87VbJtKxarnNMMreXV49h2NY+09KggWc1\/N9clBlaO61dwDTWhTpMYzNrvvTlsyorgy8jEisun6Mz4SPHhxZY9oaBM+emYMp6MykbKrn61qZxfYRcvtPrSyDe14D8j\/GYhHRY+EsH3J3XDhuqLkejkiHrlovrsswhfXEVL83Dta0CLudoTx9VDoq20SuV5OBXpptntsXiTeWJUQLD3YB93aGbod\/Jn40Fa6OISSgWI\/c8pifGbz75V1jd\/YitAq5lVCx+bXIKphP+6+oQYfOsGYjdEAtq3NCEGuMGix5zmgYNqAacz+4IYrTRFOLd7Ykyfbu0KKgJbWd1\/\/nhzAP2bXDt\/qaoDryqa2U7UF8KzAWi1IOQlmjgk\/t40lgOjWbbKMZdVALPQ0O5iP0Nncc6FuWw0IHqgR7eotA7GXbLJ7slPhjV3IqScnGuDiiIlU+roCkAtZFth5vxC2Jm+KuJVFhZFFW7g0jBvhjvphw93eVGg7PLTt60Eyy58IKpnn7edO7e3wiafM6+RZ+\/hNVZkpknA1iPF+fmlqSgemPgT9vQZ5w7taUWVDq0RRZR7+WSQUnSRRDw+\/H00qjqZA+NpVIbZ9UfjgwauZiHE6ytlWTEdcpKPz\/b9do6dKwOfugv0HEmtgm3txU8IyGnoMhYn8Fc4DKyF9es2xQjCMXt1dvJqOSwXyN4q4JoKXYgWBn1gC332NPesjelFb5zRn5UwFfBw5eOB9cykIVcRbfjPqxcQaI6smWhbI2i6OHZhECM9QzmbL6p2f02fxcLZovw0v\/cJAlj8dK24bx6cK35Kig\/LKLc4qHFXz\/VmfN7fSbm2ks\/o+\/9WfVD5xXHe2Fyzn9DnzHB67Lfeb+P7zfMl\/5TBdXA\/8RnHfO3b2wJDe64B8ARqol7V\/WLepBuSD8oQnDlMh5l2UVcLVXggLLu0ILKzH7ypEKW2RWth6t8XvnQ0dQ5evTrtJIuMHZSU\/+Ve+yPZQzTD6YS92f3CqF\/AnYd1T1ZVBw8chObHPokKwAZQWnX1YlvsUJm5ctstxaEBlDvmVvqYNENXrtHthyFcMcl2VljJRP7sP1e4x\/lQJGxrf\/J0ZC0I3gQt8lX0NKHjZ+vZvxSpQ8dCkn3+SgRISy7UKrzZg3ZJFMrvtKGhNstWQt+xFHbRdeL6RCP9w4+d9uIZ5xixXfeuGn0cO3dvqX49t5Jw1iRV5kOmAagu+tsNGnoArcV0NeLukJW2FVwkcO6jn31jQDgtGyjov8BJw+94dTQs4s8H55PobN5d1QEH\/reQpj2a81+6gGNWZB1tvPQy5x5eHSpW\/Vu7uoM3rOW9+v8bNy\/MN1ebmSkBuTo\/H8n1Gpu8zy+cRxp\/oCY\/uZ6BYDKRmH+kGZj8dhD9cK9yzp3f+OssHjTtZ+uhtMh17eTeeH8xug8lztFMncttA\/2bPXY70QbhgLJ6mKlM3f39k2Rob9R8MwYjLJpGFWyqQb86HCNhlOSX7Tw5B0i9yYejFuvn79qzjR5GEyQBMcx7ZxpdejgcOBd6WONEEHGfsg4fbyMBQ2nxR50UGRgvU+r23rcALBjx\/V5dEgiOhapl3IZE1LwNGLiN3XsanQZWL2+MtpJZ5rlrBHPcDmNwPZHI\/IC\/+73qNjV\/gzS3rJqUNs\/vC75SisyoDoLU\/r0eU5xEcw8zL8QuI2LMkwsq1fADCbuQV7v0SA4a7dup+CBman0f7u2pUKuldMFy67Z+SYTgAFY8vct8UacHx0ajxfT8S4ZGrK1dpZz\/EyjzYVn+mDenxXm5NqxPAWdnr1uiRPohfrfZHb5qIdefD8tJ4KvH7+q2nF30ZRts57hzYnRk+krm2HT0Vzwy6\/Y4HGt9YlMLzPjjGmCyT025D8l1xyfrTmSxuCaRbEawj65PxNHHB5\/KLnSB+0YHc8rUHtJvk6jfv90Y2ts3hl1U7QL3eZ89SkR7YIasd\/WJbI5pLrJWs4i6FC8pBlmmzdcgJca2Sv3vrkHuIZ8pOohiqGRYtumeKcEvCrXcL\/pDx0pyuhuVTgz7jhRHbOb6gzQObqauFDJwqbfKo3EdCJd3z3WY3jqDmisDwqC19uG9lv3wIbzdqp3nc4SwyhJA+icHgl73IELu26U9eNw6\/X9PX1x6KPKvjqDetuuDdhEp3p34W7GFsrXhdVw5BIvX+bE86QYyt98gfXgauMRLWXPipFl6FTqvtvtYKmX1vrMV\/MdBOy9Rq48lycBZaT+hn74QKy5LDH4NpmOMffra1qQ60FNbd3HOnG8bUB65GDvfiP+eryDrHmzzlSrNflgqKBf5fi5IzkJWvbtoUVv1NyQPony43l3BR4BXvnpPxSbPPo+CNydVsn1Ctg41H+Btlfk5EhiDzMPY2Da9c\/KPkujZiPp8p2LJi982KHnSlXqjbnpsId+lr1XliemAkO6dh9UwZpl7T0Qj60Y\/Xj17zzbpZh6qLmid2PSjHfr7pRafNB\/CnZEuhfvfsz\/vH39Temq27frwqebB7mMW\/xRaF6VThvcVoP32qWnPvIIqFdZ4tfVOHPmfDmhyFyXhltKHsh48fTKosLvsxmycsrIrv\/alLRb2yaL\/tDffxuDTpjWsxGfj2FTbc2VAOvtNnjb3LO0FS9YdagXUbPP30QOrX0irQ38Aod7\/YDg3Lroa8qOiEYvW\/xPe5+dB\/hJF\/53U7oHY528YfXfDAud5hZU4xUHwcvNLNWmGDgYxsz6V2aNbzKt1TScOE\/menjwaUwZ43+4X81Lrwya7K8SF5Kkb61ktHn02f5zOc8T4QQPOjoMrkxEKN\/Z9AVvZ7SbdyL9RFc9eeW1GCP+tzxPhj2mFF2A+NI16twN3joDDVWIxckaVn+AVaQMw9mqHgQwTeyowvCqe+gJrM9qPnGxiwkPZ2381PJLyk+PL81C532CNj6nj7bR9wj5Ykjh\/uRt\/\/1Z+w6iBsuXzz+q3CxyA4uOvO\/pW98OLjRp6x6U60KHlxZl1eIFacD3BDDgbo\/1HOGJImI6+hUmKJuwf0nL90Kmr2\/267buOtL0tBsRurVetiGBikcjPfKIOIg43niyZ7E9HAW6JqyZvZ\/OJ1c0OITjsKxB\/K\/vsoES\/Garbivl4cmE5WJEm0YGKkdLMJvsfxYc0tQzIM5Pn6RDOFqw1fWNY\/Qt2PuE3KI7kjm476JrVV+1za0VrOMC3F3RtGuCwlwpsYWCB4NWuMSsTVEQzf1nEvaN68zXLjZCpu6FjDUzrGgNBdh09aLa2HTL37rZfzgtB+Q5rkktxe0P4rYHVDuAUkvpQpeWnGYDBh\/U5V4T742fJ8b+IEATxvFrkHSdUj\/1zfE1mcVeb8Iyb97\/wjTFC+OEWub8KO73ff13NQIPHXuoLAex0gYdzubNjThG1NZ9YGriXB3QiJF7wnu4CN8uTEb5lWjCckj9p8pYC\/yjUju6JuuBLWyWO6qg1vulu3LD5HgjZRs6MGjzrgxp1NQmNDVLST3a+0VZgxr\/eWnFxQ5ShAw71ONOyro8\/rva9q1GYUp1OxZoAjxDurd37eh+uWcEHMaip6BorRb\/LRYanschc7qWJkP1Fp6ESmYM+Z6WNtiTSY3WyCPuysQsXivrixDDLu4lIv5Z+hw5C6vhNDowx7tTSjQonJMEQ+cvcNZx0qGW+gX6kehvqZsG931+WBXaG5\/s49DfP37dz4keCWH7PxareCsYoKgmOky6Y3jl2seRD4Zx4EtYqd22pt6eD4+slkcnMK3JYpddLZ0Y3hl9dG1T5jgMdJr3Or334Ftthj48NcZBxrvTis8bEPnrKuv+yzEPLrwnA3opcXjYTON6NElkaU4\/f3cGrL7QYQdACh+EU9cP+AtmpvIB14mf6D9pVrUrfupwBjwm7stSQNdu3XFzkz0YAzV5Q5vTxo6HbOfqOBKhUyMgf2CVwpBI72LQ9lw4jQP+I2FGveiiYnlxsOqHdjz6EljFvc7fDZLayfGNCO6z425Xb1deNpZXSXP09GJo8CtBn7N1dRunDo6EIr7rsNrH73PP\/\/H\/0ei9uA7CNbLURt6\/BZ81OPmtn3Hb7LNTDxko71Csbhcg+7WXPELN4jVvwI3FejSYHcnftcJt\/3wee5OuJf\/hIUMPlLj15fMmvtJoHXktOKX1t7ofOlwIiDQxGO\/7oUpLSRDK2LX48orGRAo0V\/xaBDJr77XhhI2NkNA9u0LOs7GDBlWzS67Eo+xgsvOyPpVg1BJYsI0s8TUV8i5JfaUCuar+ly\/yA+OD\/XHFYef\/k7bxdacCR2f\/syAIP\/tx4i53nm9eR+wTT2fhDPoyS0RXrhJF+NRkl7B47nSqaMi7agvUjLQ\/nv+aj+K+GSiDwB93VXhlVkz8aLUzobF9DLseGR91LpYQLaW\/pEnTLoQN69dxam6hag0diiW19+1OANw4k+Kc4irHM9IirTQYau6MPR1mltQG+r2qBynAAqc3UHWhwOdH8TNgTRclYhm4PqYVXqrXybkGqsJbt8qK8fgGEBka+HQjpBqHlHypvd3bhln77Q65\/dyG1y+P5mnw74xWNtaPipGwkZ5IUbjdpRfXOntVY5HXjc3RNvRvliz+Ww1HtleZA\/tP5PWiEZOGKCV56x6ITcvXnh3zJn69TjBy1+a5DAI2i78ds3JEhSX9D9\/nk97j+YHJk6G1\/EYZm\/AXaADfeNbu5VNSj57EoW30gLhjLnX1h9zKykL7xLTrbPz8uwuOv+ra1az2fvJ8vfh9XfLBi1p18yaEHzBGvuERsasu19\/cYpZvbvHR5\/2OjXjO3+PPWuej3YcXnr+Zt6FLDM2Sa7IrgNaplzhUw9OW6ZuDqsvrwHMz2fuMyYMYDF+9Keq3ORVeeGM9cn038B\/\/FfQOZ8K\/4z34rM+Vb8Z74VRb9+50106oWzunsEDruUY26VqsrDXSQU1P2eqUPqnfc3F5BtJLbXdCDsaU8UQQakmzous7hUjdqpvGx0h3bklKcNcsaSkH5KYT0hlgyPmP5fyb7VVZuNSLj9wgSfU2o35InoVKeOUVBNYPc1mehGbJSNjFqr0Q96A325y75Uo1cqbdeDR81449Su68dv9MGF5U8bVy6qx0qDtuJNC4lIeNPp9+T9IAy\/2O+w4G89TuqlZTe1NmBxRM9VRZl+SJQ2s1id1YCxaTM\/Xi2oQwlvw7AVQgPAvl7n\/ouXdcjX6\/dj0clmSNa00CLV+8I2wtJc8ygybprjl8I\/vpy4IXm6VW1ZPCjdV+ttqhjGcOZ+ERyTemK9bAYUybKn9awfRM2P7VqdxHpk+hdAI9O\/IJ6Zvz1b4zI+JTD7vcY061W4deNTpo40TGD5RR4HBvKvG3wdap8HZlW3RsmV3SDTnfpIRqIM7254IH70Vu\/8PAvj3BnHjucl6J2rkBcgRp+fi\/Hd3XD65EAnGFebE9\/7d4EOP6Gtay8RpNZM2z+5WjfPq2f6qcFdW+LoBh4CXGLy7VPXooOL7wDkPX\/bURReAyeZ86csvX2Ziel1+x918M7BsHkVtRW\/\/iLmts3mUzzLBGn5PlXwJvGU0Vm+FrQbt13ywbQfuqJiIo1fDYHSXL49r1tr7X6w2naiH5b4Efy5tZKAO8xD9zpPI0RfPFFh5kVD\/vEHXfnPSFBk1BNH6yMiv7zYjYzlWVgjEXPtwPme+fjP5KjjPxx18F953o+zzAfOj3y+G0LJx+SCrfsbJwYhJD4odaSRhHp3ZI7Xn+tj1a24VbrjrIw2Ba3vTK7M8mawfFdR1Hx8rbE5CXd6uPOMptOxFtgX\/d7diBwHP1jcU6pD97uxGlqxQ2Bv8ZL4em89HAv3Xzlq2gdDux8BebQSb2hs39BPTcVV+3KXc1ZRUTzUtTahsBveZAWwex8tRdG03ZFfkmiY3VQcuPJjJ5xuNTX8VVuCWxQ6VfNedbC4fMjL7Nc710aRn9\/Xgdhrbtez3vej61mjKfPoLGQ0eV06tLZnXufGyhOedxeY\/H5ERaaPDNCYvttdtRunXQNpLP81ZOq+kPN\/9bHYzdTHZpurxnv97cHpSAkhroYe1vwLFp0ay0ubpmBjDrsW\/8kejEnEvL19jWh3wujMQAYVtV2dVRYupSLb3Umy7wwRXxqmqTdfTsXrktxNg4cZoOSsM3zlrRDMNKy3tVwXiglvJ6qDTtAh33xowvWePXgZf6QsjfbC8GGR8tHZ\/NP59VYh\/juvQOmk3HkLgRzMVfEmlesyINjkR5hYQhx8fXKOS6ooHH8tjG6s2dcHV+JcH\/LmJcFSzSTxIhUy8vP9GFueno51m\/1OxhCbsXBYdkeoNwW1tsTxpF1IxSenwm7FtHXgK7tLVVeOB+Oj7aYev1fRUOfTGx2d0h6sSZU7d9CjB92XZ55SPEPCyy9dPquax+OBoI+Oz0V6sCBuSpN\/GwUrxj+rCEd644UnaW5nz1PQoX\/N5XZxEhoFejtuq\/IBJscGmBwbYOqgMMYgdFVUVS+UzvkzwggzvjH5NsDk27D0otiygBKy0SYKNNP4pk9UfEPWfJPYfhyyHnoL3oXaB8PPDeH+mU3R13giIFzn0la28By8fd06SzM8B7Sv7\/Tnj+\/E6se5tzjWpmPz4o0zEJwEzoo1HEsFydjDrnIp+kIZ6r+R8hHubwLeS08YDy61440HiqaPrxAwu0J96E790LyuPpJ8jVtTj4ihZyRHrLmGcAFTV+\/50fXOD08ibgrcsvi1\/tC8rl5ZS8NL9sTs+\/w0XzHTP4ABiUH15taIEth8\/O+LdmDzf3o85mUjZN71rFqCRXC+59vjGLNmqGxyeE21bIKHPEPGfaqFcPBqg58BVyBWn\/9U2Xi5By6oZV17HxyGQwN\/Q0RKA2f3neAyEyEq7Dvu9DTA9B1ohEqpva5tgR7dZ938r4hoZfJ3YePvNLSvq7EWqu6ErToB7\/Uq63GXVrfD6kOI1668ybQWo+Cl0cNsVkMkZHIvQezO7\/wZzSH8wuSRVjDPpalaEop+LwYxMqVd5zVvK4ww9aKHExfu7fgxOM8p3dRlFyfCUQe51RUL3nb2YXLy13i58WaIVx3semNQDI0rGiytnvRh4YsXFsXuzbD9s92mQx5VILw7aLxVrR9LNPiWvXzWCGx65Y1BvuXwU2Cc\/fmickgN0LZXrO\/AqxIep14XZcHmm\/KFgrnJsPp9kKzKlw6cvvXBg+9zDnA2v2Y8HPkM5gEhi0QUW5FrRceoSVUGVLWpdosfYEDkCYUEH\/nG+fxnv95gTft0LzjKMMrXfGjGcWa+FCxO5qxc1At36eJBI0rE+bxohaydDiGOBuYKg4VfYxrwRIsPIySQzHoffDD3PvCdqWudOHnu64sOBjLP\/ebjlXmKQcWSD724Jz\/499jHBkiTuPHszJYu1POTyVpfQ0X+7zI\/xmIYoLuk2HtdeD54FUv+4pjNc\/jneDuoM3d9Po\/Sm8ujkJVHRaiu1vyg2oixkYunldeTgav\/19vcfU2wYcfK9iGBVoz03B+t7EgCs75q2pJjjVBkIffD6UQ7el15VWhyhczSJ4Dkab1UP51m3BdQUlZ2ggT6nc\/tbdjpcCnrSc4bwVbc8Fby7TXbaJa+GqRNvCK+67UD7dGvIyZFObPxfuLmYmMyesZ2uV8Z7YLQQ4Z9dXIluD4p2tv+GgWrqiQ3fvPuhMTvZbJH6lPwd4hL7EctKh5fZ3XX6CEVq06E0PdtpkDG4i7TXSubMWON4aniYhJu6T+0\/UUiGdbxBFq+PNqEx3J3BSxIIyGHtMyrW5vJaDSnG4djx08sO+NfCIw1Fk96dpCBwvP+FZGjGUifCRq0okp4o5HN3jpbjzu+jdAxIDQA2Vw04Rm1DBYu4P18j0KC1UVnggRe1YFp9CGTdau6cHnHz5QB1WLcUBhR0JXOgJiLRz93NrbhOVl+tedOxdifrbbso0cf0HfLPPl\/XJ13OBX++\/9lNUgU2kpJkoySSnJLEqE0iJJUohAqbUnKKoQkISsrmxAZt5W957HPtkdSEfHz+TnH93r3V9f1unLheI17PR\/PdA8KVP74qXL1fi+Wzp+jf\/Oyhb\/X8Npocd9wMkxu86xYY0RHF\/OCyMcJhWj0aEWYqigJwi6+0lmv1YOEx8GBjrQSrKesIMRfI0H\/hcrFcQ49aLxtlo8lOg\/JAgVu91sdkCwaqJkyQQIDKp9a+psoPL59Y+js6ReosP29+pE0Iuziqy++Yu8NZv\/tKyGzr6Rq5d5Qm18Hx8ZnL8U+ozN9gjA45nzd1tG5z8Mn\/wcr0LB9Pk7DcPKSgxbb6yCl1VL5MTcN2wQOteqspiAj74B\/8g40WPfzyUvzKBAt9bUXE2kCtczR2d+ZA2ijFvVCn5wIbiYPClxUCSDIbxJfPdmP8jnvdxLW9uGOh\/H3P+RU4dgIgRIbUwG289w\/LJrn\/i1wnv\/xa16YS3z5zjuIcL8VK5MbLu6dy2cJS7n9rnm0IPVV2ra7YgOYG\/pjmFzWCNaMOeF\/+NLA1FH+8XlrFjk7gMtu0o\/simgEZn9h7IBvooxvP8ZsErst+bcW1EfipFiqG8H4d6pv3rc+5Dnrxdna3QBUhUqz19LNTF0\/\/KPrB275Dw8sbgwx\/YIhjzHns+qJ+rHmjiHwtOszSKI1MPMmoBWsvSgQMQC\/fh\/PHMEGWKK66P7TLQVgQC8wOPGJvMB1ZPo9ceZwlP2NoyxwIJn+UPZcNL72veQFbiTTB8ppq62F20MSxKfuWPfhRxeKD2cvPXuYDMQ2gZPftl7GlzIvQqZnCBCdICZsKELDUhkJX6\/9jrjFwtBkck0n\/AqR27AhlIr9r5MP9i2lAuljq7NNcBXyrryleuoLETZdnRmNlusCkR9HczVFe\/BWv4baXe4mFJpiC80pJ8LxpaK\/9o7Q0Sldt+1heTXG+EgeWDWXLxsu1l0r3kNDj\/iohz199dhmpjNuzUqEs5ZWskHaDQt83egBGb8CHhLUSosR3u5rAganGryNqL\/+HOiCG3c0\/Hi21UOBq+Yuvei594Ctz4PTnQ47Gf3W9LOR936uywT4uJN7KJQOqvPnAgIZ\/oMaNoeebTejgmee5f67ozRopJ6M6pIOhm9EfVWbABpUKr8M4iujAjenROfyODtgP7y6zN2JBklG0pWV8VTwfrpcZ3FNIvz9fTGp73gnpv8209W1bMfTNDMfPOcPKflHK+t4OnHYuXcwbaQDVTWLJjutMiCMJlzjbdazwCFk9D3R8NSm+\/v55+5pBmeD0T\/FjgFro1n2HpDI+Xg2p7aE2T\/F59za2ruNaSBR8Lz22Ng36OhuS5Wci7MVQ498CNQlwfVSwvKGJ7lQ7Xb9g955KpQ9OnB+a2Qlqun8EHKQ7US+M72sl0d7kZFn4T95Fq7U6WJ57VyLVzLUb5382YLGTz75f9zXj9vr3j8gxxXhOqHfrwJCSsCatbJeYzEVJqzsSvRz6HjlnDlvwoG5+6KfZh1+qgKHS2R8FvPQME0ibsdefhKueOnvTa4qwNWg\/7QqioZ\/Qra0XbtMwVmzn1p+\/d\/QRVW82d6Rinb6A+WRVnP5w5ewAIXsUowS4PAYt6KgwMcwH8N3JJTan\/JAWqcQU3JO5atuomFB1eXHLdlktPX7qztGqMD2+bkC\/GeuAB4m5Y0tXpmGzD4jkzOjn8temdcXhsZ+eRHPo+vwiunvsMEXg1DPlseVWJqBIQd3tUgV1mPrsLmziuogMHiAGMGo472Y5wFCpd0KW+uUEdRa2fOQoyMTiesjYuwOzOWXy7n3LNlDB5FwjZ6q5QXQy34jflVlA65xlrcmTlDAQmWJw6t9hWD2p3FrjVkdTigeLPsbQoWo0aJHT4tT4KPloShFaj32Z+RwFDyey+MyI1\/bH+tZqA+8kCsVNl\/ZASHkiWM8v9ogwcFSu8m0HfpTjhiesmwDNd+aP0u+E+DPcsNmveRumOGw9PmkTsWQLp57d7AOf\/0NspIKLkMGxxX\/4bgiS8zmw5sq6EyeGDDrgZFlfYrndtKRXDB075BaF\/ROv3pJJRKQ5bAYDhBqYWWMkFDPYB\/KGGarHYmYO+fZhi3JB+thyQcHl1WU3gXfgT+s380N5Ksh16WxIO1HD1JnL57p4e+C+mnJE+NPayH18f5d5D46RpLrD\/MpEv+do1vQPb156R94\/0EPNm8eu269lcbUlcAMt4p1njYN9Xv2qRzdSIH43l18O0LLAR0sB2X3RQGzDs88X+st3O22L0sHZt2ewTXC3aLHidUDkbBc8fWJW1upoE5yUhc8R0MlI8tX+\/TVgHv1AyfrniZgXX9aomEzCQ0L\/qZpFfrh5s7r3ILBTXCi\/daflYu60Zq1ue23vRdmR25bm6feCgW\/UiwVK4go3uyrdOdEL+x78zKp4EA5fp6qXTuzrguMLkpeZeOoA5fBT7U17wnQJVEWe7KoC\/v5Jq9O3iuEx015oze9msDPgqvIwaoLa20vLpraU48zN0aV8jeRoO1ESuGvylZ4JHD1rkBjDQoO3Vbq5SHCoUqluzSpZoh08xLXodQh7zbX576pnVBL9Og8FtsOYnsrSsp216DiTg8Hqnc77Dbc+FqOhwD+JeNej3ueMLkcyJx7Od\/I4\/ftbzzTFx4Z9WqQv1NK8N3nj9Iadm\/o+YNY+uhe+s78b7BFbI\/Y2z3x8En3So14ERXkhrJ6MgrqcDfL6v6wl+4YtONHDVcwFRQSYlMP+tSg22aU2bW8E3JPt6g8PUuC07Y7zQQms5B9Muh9qU8XKOpt+CCd1wkuSYbCHPKfmfVJ6J2vTyLTH\/Yfzs8CD+H4TrsPPi\/7IJTGs3jrntIFHqbmbPBL1vY+kA8QD4fd1ZDD0IMz5mHg+fw8zEL\/jv\/CA2f+o73wIthLPP7rNxDvYTUZ5SDi4PPXr4+Z9ICJmq+XekgFvIy6eso8kYhd64RutmjXwYZIWvrZ+1SgxCjHlnFnYtHps3xBr5rhqbNK9Z0+GiyZTLMxvpqL49uNXUYN6uHBCd6jq5\/TIenI\/RDZCznI4A3iP7xBdP45Nevs3oIsy4+MhG9vAmbf4doWWXXv\/EZk\/zYVdC21Hqa5jrTsUuhHiRdW7LHkOljEufORZGwPNEtf1f+RUIeN2Q+m77UQkaFnh4JQlu\/rRinwTzzP1IHCdUbeemE+b4VwRt7qorGlb2SyBZ+V7yzws6Xg+ObngcsSS7B2a\/sg\/\/94bVdpDsPLq8BW6eSZaz7FINhQkUi\/1o4zQ1yW59fXwR\/j1kXG4aXg23Dl6a3fhZA6UmJdb9KPt50SnijufwflbOo0W8tMuLipar3Q\/hwsPfAxztGFBhuuTORcNv8CbavDAgNzYjAh8vuDZ9ZUkO91M1X0iUDxOFWZ3ReCwf7X97LUvhG0clthJSwwCLKNZQJBN8pxmh6\/NWwmFczm52SA6bvH5FZpJHcloFkvjj6M5LpmVgctN95d6jv5DeIfvOuxaqbj93HZYfXKaji+jN7Z0lkLnG\/4lhi+70HFMj87kVMNUOG+gzK7pwa0BmZ+KQ4NQMbe3o5Zoxd4jKMmXf1LI6akcTmf\/9YHS9p1Q863+qPfycGojfYNyNAHwaZ5fRCundcH4QHWwudNGSGYlL3I+uCpMjA+\/dN2ky0Jn\/43bgRm3MionwOzfv5svn4OuUe3n+bBbsiWn75AjiZCxQ0L7b2LyLBBxjKpdzUFzr2\/Qoxb3YhpcaFr87\/G4q\/ABIfCufXSAb3Fvi8aMLP624g8Vzj8ajO9hTMZIHSw\/ULsu0GIy3gmy\/W2GqvrqIOfd+ZADsOnntkn\/eoosTuSmA2z0XVeZRl9oDDgnEVsq0a13EbdKqc8CJrScBaYGoDxVxlfC4WqkTXMX7jlZB74b3N4fP\/6IHTZRH4IEStBq22kQpEdg6iyTD3RITgfHN77OGWllSJDP4v\/6GfRYpMG+5bd\/fhg1bm7ebbZUOnlRFz2tRgHTsSNPFs6hB4nR3zyvPKg5Mbin+4e33D04y7Xieov8KDM0aQnoA73vaoV\/fqgF+jh3Vt3zH4Dfe343PbY\/+knf7zx29cDh5R5Dj0PT4GfGqSW5u4mfEdt1qi71Au1u52+DDj1oDpj3oOhD2XOk+A\/ej10Y\/gHUec580wdGfK7fLy8SbkHHR++exXwkgjp2sMEyTt1WPtaI7YtiY6bNeAirzARIl\/Zd17Y2IQGDu99dz5vQcPZKlbTkbn48e2GMZ1WAszsXXv0QVkm7J4QLnnOVgS+1VarvANKQSiw8BadPx8Im3MvjaYlwtNm19mAufjUBB493fZl7vNasWlr+YMikAmWogtdygP5xb+2LjlRDFE6eSH1sQj7it2N\/Ofe3+FXovldRSVgqXwxTkojD+p9tfZsv1YAzsEs\/jMzNBgr6k21XV2H2oX1enaR9dDkZHy5au6+WxY\/MxOdVI9vJcX2\/ZZsBBNLJUclXTKcvMw6QtxAx+myE73ChHIcFDa9npRLhUe\/LbrE5uKl4fk6GD76XF8wEEgBbpG8YW49GgrxZmHtl3JUFx4vvtTSBLonNYUUNzTi6UVbzD10OsFH\/nfkuzfFYFFFFupiH8AYJ61KH1IB5qkK36k6kwe8ttGf5LYPIMvlkskbHMVYZSIp7ThJgr1bT3\/2fN0I7fuoRAHeTFSRiKGdEaTCrpmcItFDtVAy0VHjrl+Mqfk65YWulWgWIH5Vor4RAtNVwO0oCezuVpa9rWpA7zOpdvtIzWBWFsIe4UuEe\/zUB6cC+pm6MxC34b0rcjULVxwzWWLJ0QFUs41Km+fiyK\/mhXc\/NDZC2auKNY9zm5DpQ8rsFzSLbrqYPtoNCfGOIrW5rQu6daOhTu+rnSRMbDGJWPaDjrFpszcdsxKR73v+ejczEi6XlRsvl6DjkmMhlmuUCpHJKxsPa1gjSvJGJq+MyUMTZtxLzHz2QXb\/AdYQOiZOPxL9K\/0FEzeShWtLyXB5TOJl9vkePJTdQPzgEYmxV\/cs6+Eiw4tdW19JFc+dX25R3a2Gn5hzhmjRuKWucnRg4d5m8mYF+J18m1cPogSDh8DkzU7kyuTej+9DYfKV\/k\/ckXN5orhR5UAbukb4lAnN9uL6Dc+fCXemwJ8szmLbw50YOuPz\/FljH+6+rxJikvYFAs9xdH0faMUZm9Sa3fx9eKJ1xFKKOw+uqLteM1XowMjhnbExc3Hphvtplx0Hs+FDj3neb9VObD1XEn5eMx7kTD8nhosOgneCkO6zmU74HXB3e7tpDgRqGfiy3ugHmyd9pr2ybfCPTnYhDv9HV7vQf18WNNt1s2UQ3smbpKvRg9DFKX5ruZEbkFNVlrNcI4PITRW57v46\/JlavidZKPtfPxRg+qGEuZkqBDTEA\/P7MvtucvM8YWDG\/wyeMASJ3Hx5kZwM\/uEWQ3o6HVC7edMWLrV+SI6R4Fo1HgM3uDj8nl3qBvbtdq3H7\/fB84MyqaXsOSBmfYXwRmkurtU8+kPmTR+EWb0weP+4ABjzZtDH8GH3tXmtrHK2CFySdzVll\/ZCXKxO34vVdaDW01TYdKgIjgsJ33E3GwAx4+p9LLGNzDow\/lMHRkVRAdeSCRoyuTTMvvD0sgtNWYXvUWd9ceqwXgIYf7xkWjTdB09czxHVLvXALWG3kbffc+HR5lLub7UE3LJ+4345TRpwin117Kj\/Ar4x13U8nrfjeitryf\/NY23cI2mRORIHf9ilL2j0ETA6YtP5SO7+hTkKBlcKN7+08rd+1w\/DjDmKCs9XJQbhJCTvVO\/zMO9bWGdyd81aRtb27OwDC1Hl8eH7jqBsbSBvcICIux6WXedg6V1YT\/B+kiNFJGEMaaNPbXceat26pXx5gAgpO9PMo3c3Atmqk7XYOhvj9u7QXR1HhgdF7cSd+1tAfuszxZTMYphdcfJavBIRjfQsa3VEqrDKyNjbsCAbNk8F59FCuzGpUWBQeW8pRqJ5is22NuDSetHQNFmIlZKUnqGmLpgS43nSsKgDXu4JvqNCaV7gcheF7Nt6dW83eGSZSIbGNSOTg+G0X+dl9YE2iF3HW78rsgGXEDMstHx6cUVsy3SuZQts4DmfH8BVhJ+O9PQUdlCxMYWyyOxpAfj473uuO\/gJbR6IWByq+l9\/6fmfcOu5\/WLQ+EPFio7cJXc3nivLwhPiOeMl\/pmwwatm0D2FAmE6FnmcWZ0Y896JuvlLBHgsvv1FupsM5zTav0\/JtaHdpq1r89jdQPb+\/ovRzyhg8+GM7oHgbiT68d6YPmKMPCEBDcu7qLD53HWLwOx2NE6+oiglHwcfdkwuMU+mgcXlSfkopW78a1hACp6L86P6jeXSqQVo5zLB2cZbCLZlXo8cOPsg6ebkoz0zKfjUUjtMbH8hKJ\/sfkyTTsJHpxTXHy4goaMkmzHPmlq0+OQo19Doh6Gad2OJJkSMSL0RLSpThYETPKm\/o9pQ5LiJ80BTLxyfEuTh1K\/B6SJ1fV7dDhy7Olyl6j0APxj6vj1uk97Rfp0Ynuys9X1uH231o1y9XFeGF8w\/nb+pT0DnBzuU\/P8MIJOzMb6dPEs4OHe\/h8bYPMwhgeQqFs9dilXgOaMuc5Kdhp4FUYXK+kRQONnf5zD3rvM\/WM7hcjAeHghoe3WL9oHp6YPCHDplqEyS0w+4nwmyp1K3Jyj1Q0jDwZmHtfl4yfrKygGWXNAxpySOafUC50uBRfcD8rH1SrDp918pwLtjkygXRx\/YWKin\/fzzBYOW8jsmzlTih7W\/lUk1fWh8+pdp3mQEhGS2\/shsLJ87H34sq3b1o17T3mBj6U8oIcPf7ekZC7K2u4KOd3RCX0jyxnotOuoOLHOTMpu718Lt2viTSyF8P\/+1fQW16MDVp\/Qkqgvk38oLxVvlAb\/pIdnfE1UoOzKof6KsDJfeu5EnFpIJ+jsULtFPIZaaKfPJGtdhgY3f+itrw4EgfP2prFQGUvdTjuVK1eCGBOWP5K0FELS2fcg3PhkVei+cFrSuwzNm34SSfDIgyOf8DcLqAiSy8Y5S2DKBOU\/CP99nB1rVhdN+FvlMTgWcYPCaCNsUxvs\/fwXO\/a3N9ZoDcGbNvSDJpGYY5SEMhbYRgXdLvF36\/ULIK78sREya+zymCxuWpXSBQoHW9rqgQmDMV2CUe8LD17p1cOGOkedpDRLq2RScjTtAB5PNv2WcGmthekJol7oaBR0IatRGLypklPyQo4WQ8WddhFit+ydk1mlJxbPqAbkE7F9na9uUQ8RUzsTPyz9mw+Tnu13yhp2o9EBBe4UFERUuV3p0\/SyC6Lwpl8Wf6vCJeI4R5656uP6EPMEf3Yg2MSp\/xNSrsSjiA2551Ag9nQd4E5dVo528TlFCDhkbBcs3PGYrg82plM\/e6c1Qo8kRv\/gTEd2Kxy13biyD8qBMvqc9rXB93XmYpGfj3ha17ZeHm3BtzqLLpf4DkLpa8lyvZwOovThOJfiWga3y+syHpA6och9s6GSvBusXYvlbtfLhSsjLyYbUufe2ST6YfGbuPq6VYR351AQSBod8jrzpxgdm2XIHk8go8XDT78GEVsg6EefXGtuJsMlrQ09PMlwM7k60uFwPPG81TZUcGmGLonB\/UfAADv00z02SL4Xxhjdnv7JU4cMKnjDzpAH8NH1DWNI5Hwx\/vBxpiK\/BPJGbU7f+5qJ++w1inUI37j+qe6WloQfsN6fqrj9ZjFf\/fo5XFCehEa5+s\/NSPzisNvfYtiQHtV81Za7XbseYbywjj3np4BHZvobIScZe87Vik8dd8cGPsWd1l8go+uE257VIChZVFn4s+xiBTeVpH17kU5FzyVWCylYSekqM+Zu7ReDpFoeDfrJUFCRPaexrKYWgp4JSNpspsL9+10HJzYn4JJT1dO3WCnis9dzioCgdfH\/k62fFZmGqql71ieoCKJAzG2Tl6gVerdbM65apWNSwgj9MoAj69E0lXXbRoPgp7bxydS7Ku7NKclX34qBpV6jZdCrcVnattS0qA7VHV6qW+HdhrdaVjDO5nfD18tOhxyyVsL6BuGFTABGvFApO1S8hAmvtjS+EY4UQxE7KyB0lodB4f5dRcieUcXXWRvKXg68\/r1WrIgVdBC946LMSge9RiT+bQT5U6\/m8cINKHHyWMyCXQoektT8OL1frxg3X2Kq6A2owfNPIGfFwGoqJqb55ZVqFJ0lRGgX9iHJ3svgjzOloc7su5ao1Qq0yobV7qG2Bw+\/FmGOJyM5\/Orm7HbhEzxdIxQwwffRweEmRxV2pbny8nPp0y10iDj+6aCjNR0EqPx8Lb24HxlFqF30Mb0OfOlXJs+IU3KBK3\/qSpQu\/nkjccy2lC89qVni4VVKxUImXZBhVjkW8av2dDd2ocV5KJWp7A+gNGT9MWF6K2\/9E7jkq24YvTlwjap1oADprpbiRbAXqZSbHyhwn4sgTY+G1xBZ4Sz7se\/B3IXKNtL37nNeFrPIP+KRXNELjU\/t3RT0eSBx4qBlxuxw4fxd8cEigYZVXgRG3WTWGbbvnwJZPhsrmKY5Rt3zMvzZwsam\/Av+s3uHsE0iEmc+xqq1Tedhoovslor0PTFal1XxzrYHdnoSHqs55oGzbVGr6dgCmAu8dkb1SC6H92lqhpyuBVcho+fHpAXD56JJMvF0LEm5FXFNi3yDkr\/YhFno1VrtGrYKnNOh3\/fwyQa8adkjd5XolUoZKObkTpw3p0Fw8eGqFeQnYKUU1ndvxDRUdmvl2WNLBXUB7Fk6TYVLq+saOT2XI9L9m9tF2R\/hn\/XUswWXkQPGI3T1Q+DDul84WEtxmN20PsirAU6cjnxpK9oLg27u7BLSI4PQk\/EznNA1PKvvUfv1WiI2Sl3TYojrB8HvOyxdhjdi8zCFoxrwLw2aHx337unHJm6eFS\/e24PHovpMCW0io63mH7HuMiCf9uKMsyP1YUeJwgV8nFzwfKc0In03DY+XBlE03+tGD\/fMJgkMUJI\/mr9rxOht7n9VO15LaYPWZxzuz5vazsYptnY1JK+4X39wyId0Bkt9UpzNXkqFs\/3a3g7dbUEFBS+gbBwm\/TDp92vG6C6SDNnWrhTUhT8LeLiv7PCgu5DWU4B9CvcNRl8TqfJFwTIvyOqccFD7ate\/bP4JZ8xxs4E52+1gw0gba29+O9z6lAPHzrwYdrkZk1XPYrhQUAbpBTu71bM1Y78HZte1GAbwUDE4byWpGhr4J7w3Imm29lYNPJL0fTVk2I3n5uatcpgOoKx\/JVVybiX3WqW6nkA7+BcosX1UoyGkl0J22NhpHUy\/\/dFPMB5UfuSJnbvSA8foXyumLK2Cqp4Xthx0RWBz84k2IJcz3Dvb\/10cYmf1l4vx7ikzuE7O\/nIFee+SGk6H0TOj2XepEXHRvOKGYIwSrB375znp\/BS9tnn13586hy35jmbG7SVhAi0+LFEwCpcEw+DpNRqVN4ZISufaQ+3GHqNGXYLDPFNtwaAkVxyL0kpIFojDPWO\/gzi4T\/JKdxf1TlIQusX++n8x1QZNrz434VVtwzVS9QxG9BmWO98UsayjDkFX3lzvYtaFFW8D4aGEDukquXh89movSx0anH2W2o6WhBs19USPGtLAt5ZutQno88vJ0ElCPyr2e+3wz+seXJ397V4zvkin6pNmrEN2+1G4bbQQuz\/vCo8I9h1fXXb6BUubAowDzFtjNN2SR15uFzjm3GxIlK0EwVfnGrex6SApsvbZWJAWHK9Xct2rXQadu6cqSXgL4BPlNXL+ViqxWJx8K6FQAt\/JidS7DFhgX9h\/iVozEjcsl7tFU8lBXS+V3wNNWWGw9rJxrXorF0u0UgeWdKHHZiVC1KBVGLzyc3UUiw+q3OYYbvL\/ijjipcN3zOaBEe3PmxEwjnCpn99tVnow+ArIiHcOf4Tb3vdQ9BnUwruWdl\/GHjHx158pvnynAu3ICIqw2JFSRlz1APvUVElyEnJ5aFi5wOwk7fkWfOPgVJlLGVT1WfoNajieH21cMYeqK0e3v1AjAw63zNNWJgOxrZCYjW0j45rva5STFMmC7JrceC6i4eqj93lQaGWXn52Dh9vwc7MJ8RdwNv5d6B8qgqFeM1D9OR9FLkl07T5Fwifeg0O6vI\/h9Pl6CHfP1GVC9VUVeYv9\/610M7rqNnGWrQAoVpn+FXv\/UUwcdJ3UNVr1uROsqbzbHGzQ4SxBMjZWpgOQzEdH7MutQdfBt7\/kBOvRSN73Z+6YeqA9zFOWJTXjk+deV5WE9IJm6cmmRSyVkPOF+ZbisAe9Z9bizNfYBfyDly5OHYbCbk3DeLq8WBWcr5Gtl+uDBta4MQw83sLgTL7YqpQQj1SJFuM\/O5QOHhB7fL2nGx97JYYqq6fCePGO77tYQHGPUYZh8SMHMzszYE12Q1r\/jkklII3reXHv5SFc0cN2ixGvEEOFD\/knV9j0NKDe4vSdkIgHW2975eGXu\/ErYbrSUcG1f8GvYO+m7yD2jCypldz8PorQi01fX1i0wzbiVCCZPrBS+PiYs+D70K7RkJL7ogjd+7juLOdvQ5fxO+\/sPaBB3cUfnZ\/luqHrfPXlmshl3+R72zuCiw7kEBb57SIRdpHIqKYiA6269i7RoocIkdLp1lQyBfNh63q+\/m1HI48fdT7MhwJsafq+hoghPbggJUNNqh92XYrfRBVsw5vrSaZNdqbhM9E7F5cw2CLoVcfl+fisWLPrBHiSajSI1X9+reRLg6dUNh+ZyUnT4U\/myW6QIVmnvb2mNrcUVueeqc\/7kwOIdzy+sX18ASUmsF5fM5WO5nwPY7btC4aWijvux0WIwrPukvf8KCR4599RZsXQgy53Bl1zmFEhdpV\/ZN9MB24Ssq+wo3cDkV4vO86uBya++6S6+aK8rDV6yOevUm7RDtfdPB\/Wb3Uz9Lxz+r\/4X9f\/rJ87UFeKxZ96ysd5psPFleFCqJAXY29hCBgToOPO3uSpxOR0YvFBmnxfPG3Y\/Pr6YDm1yDp5K+0gLPlAMXTAwdMEL6ylV51R4Ymkg75FkZSDegTNwfNloVwcy\/M7Qh+F3dn3e7wyDnridZjsSDvbLZfR3X+nBhB9p9qNGIdDI0blaatID6Czjg0mUPtzQN+Bw2TME2khJSX2ebRjpKrPZtJMGmhrU09xFHTB42\/K69loCvsObBn9m6fBgm1EUyrVDv3GfrP3ieiRQN3RGvGiF8GfrOAZ+d0KalmLzKusuVLD2bHg1VotwzdZgrKYOGfOKGDU\/r7jQN2TWo27P16MWfPRaXM+y\/w6lo8gtWk3l0TrIUCl15Z\/Ln2J5fEhBizvQas8s91gEEVSPWVQq3SJAsFeLfnpCGTL8l9Flvn8HJj94dfn1+iG6L0VljWzBAp8zeoNszsh6IrB5j5B6rJvQ5rdb7rMVDSAhuafZ5nEnnDY2e6eQ2IyGMsQfqs4E6OZPKVVraQHNg683X+5oWOBzFnOOi97PJiycC6aP2CbVtT\/if6Th8GXr9Il1ZIzXrdm0nzUHHeFh45ob2ciimhknTqfgi97ie5whwRg4+JW+5nk4Li01MNWxpOL5NLmOVyXJC\/Vbyfn67cJ++PvVseOO8gDTvzKbua8EH+kT8mt6kfeQXheKmeCb6ftppSrdTK47MrjuCzp0xj5Exj5c0KFnr88\/N7KWijuXpjeI7idBVnWOAd\/2NlhU+trm07om8DiY1hPI1YWDge6cLMolIHQ6i2LS1AiVl7YIZZgQ8XiGjKGuRy2Y7Nhyer9aHQRUxBebqXThxTe5j08bFsBYnuPQav16yLKM+9rY0YYTQ7ZJO+fyJekmfi05xRZUU1Fkbb\/TAu7BizylYsggYKA5meHbgKdGDc6F9rSD0kVj43XTJDBeucJ+MqMBg7xeHcwRb4WlbHyvVxdSIPhuaou18FdkvYkWn\/xHUIGh00\/i1ZanPNdD9fPT+icEaLiyeWLYpL0GRRsbr6lPucOfwFUxO8LpWPlDk+uHTh22\/zJfHBRKwm1pP6+2TXeByuci+w0sRGTwS+EffilK8QoIWVwqXeDYT837F+MLl7ucrKMVEC3RZC4R2YeiGnU6HJUETDFYs9SUtwp2RFYE0Kz6kVfMtJBVaC7+9L3BfXdjK3KHfLVa3PoFNEuybO4JUpHBCUcmL4LJAWZwxZn1W2BwxZHBIUezeQ45MHnCH91KQ9aqVqFTnO7uDXN\/B8qMfME+swEM698Z761cj1bdf3dupdaCWTid9x7vANauGfPVzyLBB97uN\/Zb6tAZsm5HG5Bh3dMTlp2nqcDpGsR6faQW1WazNk42UkAh5WJa5OUySCkSWXxfowy9pyW6VpeSYZsJ6fhwLRUD\/95B8W3dGMl2fNuRx9UoQs9t1aqqhJjKvKs7RcnIY75XgRhHYt6fC7xl5pyM2i6zydtiVDST33qMNaQd2hUEnstzdYPTKCnZYxEFx6d6kosruhbWyWFKp9Y+KQOugSXjuexEtCxNX3aYi4zjhwW\/9IQWgIuAiJ\/j3H1ab\/bzML\/6XP6RaVm6+Uw+nI1KdFV91YnLXm93aRsgoYIhD9uvkkow0\/6845weFYU6nT\/yqhFxvHbo47W59zX9w98BqsJ7aBV4cltmvS\/EDiT7dWi2YnZ0aRmfTApsXO2oqG6QDHYMv5Lseb8Spr4M\/M5Obd\/5vh+X7tV8lmKQBYbKbDMurQ1gZNN50mljO57Il4i5UU6HZL4LgV2irdDrvKHee3sbMnWRxweC2O93tcORA4qfNh4hYI2KTF6NcS8MuiYrHh5thllPB8rEsS4QCRn6ftKyDn6y7z5qmNiJjviZq9bTd6FPyvDLRml+\/jerX3kvcFCZdTNWw3rOJ\/tDcEPFzm9GBdV4UFnyRYAwCTT3H+\/8ce4t6nEvrhgKr0ClS1MV8aEU0JZ14lNubMQtfMHd436hICe1tZf19xeYbLFb2lFVh3clD8\/alH6FFWIG0fscC6H+kXPNt43N2PdFIJ7U\/xUEhlWOnfQpBMUij2iZDgr+OlK567d9CJRfvrV41nbu6x\/wq21Vp2NWk2f+7T9xMF24e4XcwwacfrPuQutbAmp34BbpRA\/YnrzoWrdRLC75+fRCw\/MObHq2NbXfOALtCx02WMreBxOnnqc\/akn4gu19WCmJhrxbXe+0Rdcjr5FS4yTnIL6snLLDuTj9j6lo38\/cQpRL27Dj+qoBJJuB1IOGbiZHAhMeGupcz+7DhNeSKqm9Heh80SXkHHcexleUD6T+jkFp6+stVawUvP2ut2Z9zVx+TyWoNa5BnPvB1A3eUDBvy31PtcIa8NLQ1O4T\/4LlvB4c8oebobq88qah1QAcn+eBI4MHDky\/gOgx9wvhjp+Qn8ImXXWuFbhl+IVYh\/pBaWWFuWZDA9hudqB\/9KUu+MV7FlRFXlxPBkWhRbcvRedA+tWJ8BauQhgNC\/jCe3xooS\/Duz7Tq\/h1Kwgtsgi+HZADhh6c8ucFatFf9mieUTIJOSqpsofel4G\/IA9LxHgpiiUklV7ZTcHeiCdUb5siKG1M5dV6XYCn+x5SJ3xJ2CA4c+j5rhKABEGuMYtq5FXTqJaXIKEY69JRzYBkcJGQeGeqSQUeIbd+qbJ8FF6rtHuFUArEvG5Pk5KiQf9fp60pE6nodP92cEJGG2y+I5X39VAjjC+yv3dsvBYivZ0VDNK6wH+o5oTr6TpIeF7meMS2BFzeFEpUHyVBtZ7Hn3PGTSA78CD+yZUs+HOt2m2orgjeVfa1Xagahup53yismeeEAIMTAg8Yf997Sjw\/44OKgH9p8VeWbSPA3A8tb611Ql8Xw8972aNCqoPg4i9hXcFehC9Ykj5+fj8M++c5bMjQRcLxTduajq76v\/VbDA7zbQWb3Du2\/cy+LXMOEN2mjn3NX9qL1FYXwW28ofiX2D22qJmIle5swt\/eUrGf5frJvRmpuOn62J2Dy6jA9Odi9pcZ8+1QcqCvxDlvAA6NHZO73Z6Ga5Y+4WQ72QQibTsfaPk8gdPNAq3bfVvA2F1HPK+vF7bcPO10u24IXOf7VrB43o8J\/8kLQISRFygXcgYcWzIIzVTpQD6NRlDtU\/54McYb+Q7JmGx8RkDrD7w7y+qrgWWG+7CXT8pc3PD\/daPMOj8ydFXQfJQa\/kZuBCzWTLe0kgsWzp3q98+W65VHgMGpWDh3DP8v+Mf\/C\/16nHsSAgZhXUxQik\/tF\/TRtKG86SjG7QoZG7d7DsK2MLLgydACXL0kXK9SsBAnmsvIB0wqUYzhd8OM62Zo16+r9Ncic86cyWN5dN7hm8XKEQhNeKWQYRHD9CuB62z2Omu5qjHhsr3WPVcaSlxydYj50AR1BKWDz\/W\/IeeNjfYyK2iobynvEu5AgDDvXxkeZcXodTxzh+wTKmo1bddzT2mAPFOenUJrSyHj01\/649C5\/X5SJSRoohdTG\/c+t5dqg5bETRU6KzoX9PUdO7P9ChxbwWbwpeYK\/raFn\/NI8jVeZ1cCRPk6+Ry61IKZglfLjm7rQfq+b+G9Q03wtfRd4qRlG86sURdrn8t3TPR31orZ5cDuJbJe4uY9ILSjq1WrtxRHhwKON+4qhqOs3tnHD\/SAOvfyaF2PfHTW3rIsYy0R\/8SV5WlGdMFxRt5k3tFHIPpUIHd35pHFy4pQYH6uGF183j9xvEgDsfI+Mc\/uBLjv\/EIsZHU6LHE992jtgX4Uzaz+vu1WwwJnIAz3SFn+7EMGjwiE+LYmFZp3opryfvbjf\/tx7HvY5r8fGoHhG4VfeM4mOsU3I1ftr+SrVgVoN\/vWp7qvH5wtosQFBIvx3v1ZBe5WAgaHFwUfj6XA4r6ZwBixEjRi83o\/\/K4D95zapGTwjAb77xT2iWIvSjN85BmcbWSuizP84pnrX1\/ICRuvoqM\/wxe+cJ1jWFQvGQ0dqruNlCjA9LcSmteXIYs0zk4El6K\/teXnwIgeFLkQG9m3koRFfM+3Xassw2PscWVbPYrRetv+VUtukKH60AoRxR4SrryS4jelTsDkmEuXaRZF4JxgsDf2DRVtWxMM1d63o2oRLUv4dSlUHr4euTZ4Lt6hU5+ck2vDlcF3ydJV1dCs0nLU8GMeZpi\/CjzU3g1o8u1i+WE6ljrdrSc19QF7s0h60uZcIPz8XBgm8Rpdr6gNyKX3w4TWwKjepzyggFTXIeJnVDErOrKZvR62WTwz5j9IxYeBS3WFn2di\/NM3jnqBDfApmiLx+gQZf0jPancEZCPPseprZ3Wb0H5U9vsOvmD8esZMi0+gCVQ6140P2HehbIbszX45KoRcNpLYx5WJSSZaZvnqHjCtpzCuL9W5wA1mORH+\/RHlKtIZPHamPnqw63JESIUDpPj4fBG70Aluzo5PVi7vBwZnDBicMTg7r3NBBmcMGP5iwNQd254JeKQpSIKDftvTRq\/PvZc9ir353nWY1sdyfqt+IVpfrZUI4BxZmIurU91ypK0qY2GdOU+luM\/D88xEGpylkq66UVxQT+\/p8m6zIajgzqEL3siBXK6lQ6dkfFF0VVxOscIAnD6hyx\/j2Q0Ssqf5TZ9Ho1KFV2XDmmI8kWP+XeNOL8R+Wd1s7FYDLy\/WbNOM7cSZIMOtJ5R6QK7twINF3fUw7VEWdHesG1\/86D687GkiSPeyVCVZzcW3p\/vHxnT6sMtz+YnMJhKs5TCK9q+qA88IgRSduCuw9GzavggOGpheOHwQwsNAxfaLmiqZOBeXE1f0ZdIXfOE\/6e9ZcyOMDNn\/5TAw83ogfD8kLPO6c2HOnMnBuxlW5Jqp27Uwl87wjYIuLwWZrqst6G1i89ikmQpiHBzNAh0k8LTXifa0akOTCZkQzTgqxPrVT4e3EsHwU0+9+5pqEK\/87iV1nIpKLi\/rSiqy0Pd3bn+OXAL4xLnKOc6dK8KutfePmZdC6TWZ3osB9vjua4B+499a9FUrld7shODepm2geTUO4rCiOWruXrM72pchM5IPWZyunrfOWgPPwzJ9jbFKDOM7tU\/gaz2eXuW7zqozGnlgOiSvKh+Lqj\/\/2vSzFt04ORPZOVOReptT4fLcu5FLuFiuptOAIjFhBlpP8vDPm7fVyxJ7gdT7NnpbPwI5UvVx+lycJC2sfvuwDB0OqiqXDmRmgvnuukHh+DxcJs2ls6GjF8T8BJUlnpfDzxzymbBCChJzbxA2cZZjtKHiUjXLJpCO\/rxZ\/z0Zya7GrMdl89FE2ue3OWs7nJk6ff\/6dhKev4jOhS5FqFFkE30ksAXyLvazbcnowWvx44qNpHzo2G1dV05qxg2nnha6SfbiljfP9mlqxIJGzn6TBNlmLDqnw9dygIajMj0qz9jLgfVNyx\/DoHpg+IDDPz7gWDo\/RweMOTp4OD9Hh\/3J6e\/X+tbB46s\/p77J9oOqlpo2X3M1rhEbXzQp7Lmgc9\/CmDP\/aUZNThhPwXdPK60DHtOQ6Ser81v\/9di4N\/rZk\/YFc9PwuvlY3lMPKrATnGtZUuMxuvKXM3k1FUWMrVbraNFg8AHSJI\/2g97egwfNdVNhpbQuX8OjErxz65uiRBgRVEOGXgjqtOENyWxDtjIi2E1w6Eu1dUET4ZvTspAONHpmNjxL6YCiz05s9JwOCNxVoR6yqR2z2DomzsWRwaBsUXf2mTYQN\/mo4WPWiayCOl5ndeby059Rg6ZTXXCi9onEQb0u\/BqhZ5ZZQQS97YfSYj+SYNhN+NW0ex7sbLnEdc6EiC2HcOdkeidObI6TvnigAO5rBT0Z\/VGMH760wq9DRHRq5Vr1hjUfRA++uccmU4ERf1VNPY52IFmOQ\/rPgUFm\/AnvJA5I6ek1Is81M7nOufiLO9a4\/MTxdDDS1nzhatSIu0Wb4x4IDILfNQGFSa8Q6HJxrpJ17MECK+XQvd+6sHf5jjGp1Eb095RaPfqDjr9WeqtsGuvENrWsXwaGhH\/nbJncNhQUWbIqwakailITzrCxEFHDPWbyAGsqjIs+o7wbpiI9gLO0tqEOwoTPiEWMkfGTseJQ\/uVevHkneTdrY+2CLkDRU\/1z\/fk+ZPCXFnQEGZHnD9SV5OO2V\/c34XAfnD0xuchO8z30sk743rFNQYtkaTE5bgqm8JekOC1uxHN\/Nq6diKKASPeKLQYBVFyavlto9k0GNOpdkBCTyQGVLc3r5VqbFziEUo1hbcmfM4BzdPnDGZ65OHBvgxV\/TQW++szuI7o9FRadUjU+k1mOAYLbNcg2VXg5hzsq8aw\/9H+5XmsR\/xWDDikM28xW4\/VDoc23K5txunqdUEj5EDgxdE+Zd91OPo1oXuBRMPsdIotPF7DktDL9boCph2LNnQlttWpBn9OHqEL2A+AUMTZ76nDcvzplZv0HeK+qS10x7cDweb0Vs84DzxWnsnjm9nMjSx29ddknHGYvnM1mrwKrQdm7tgIUpB6+ILXRNAl28+W4+5HpKP68IeoV59zvffiGQo0GogTLmEGmbifWy1z0vMRSjQNR3BF7ipOwuKkwXmcPFQimA1\/ObCpHYyWzLYJv3gPJvvBYWQoFRC2iXw\/wtkC46MmResc3MK3ZteLXwxZUEt724Kf5aZjo55R8\/60XfQpWJDizfMIHrUfDk+1ysf2SwNqbdCIydBnw5\/WNoKtKVMwJlhn0ryOiWHmkU4p0G8SO\/fows5WMt1ufnEp81I2rzmx\/47a+GcZE3n4CYSoq3+go\/NDYgXa54nebApvA10zzfMGaFvRdzWZYotMJinqhpbTqehDgL0v6XtqGDF9jGGT4X6TNx9VImI+rF\/wy7H\/SrZY2NaOR4BdXu5ZO0P6TT\/wp0gMdls7tUdatqEmNsCwoaQPuifZnRvo9kPDYKnm1RReevfX7u4ZnAzDm\/YDr3VqZXXpEtDkT6vlTrpbJdQRCTVWb64ZOXCl80GClTzVweEeEaWb2gjRuEeBO\/IS\/DL1f3p4hgSJ597uPtV1Y3rtdKPi6Pe6W27D+5Rsi3Hh0UyA7vQOr3lmKGkoEYVD4lNeeuXz3c+87oZsmpH\/nPMGeMefJ4NDiPxxaTNfRqbPc3wZNonI6kXeJ+OmgaG2fKQnjHh\/gDv3YArJ\/e7s9znfitrHLYZ5GJEy\/OX3YvZ8GBz4JwiPBYggySfm8+1AlyunT1Po2D6NRmmvw3sxC7GVw8j3c89043IeQ0Zdc6EcfXrrho8uqAXwbWdLd8aUI+8kRv+VC6\/H9oQl6+NN+pDw0KBa9WYSlomU7x6ab8L3v0gtSIgMYcf6VY+qSbAy6Lfyt8Pdc\/DZj22GeTgPv1Y6\/Hq4mMPU1WEQ0PbvqLg0kKeuv1Mg2LfiyyVoYLQ88Q4a6C\/K5QWNNQHqinvXlBRUZfGxg8LGZ\/ThkWfr\/\/WWgat5fBpn5jqFtoI3Xu3rYf\/4B\/29fMip0NRMKxWl4+6h0TaREOeombDUpNXVDG1nTbJNFA8DUpzN1uMz+qbbmufdtt+uh1jXRxy6ACs1SRsJ1ZyjIyMeROUe6lOGPrBb7QyzlwjCemd9veG2+rw3mhYsCBXOHkDlfyuSQeN\/M2aPROYDVmgq7S+MacK1C\/O\/DZ15hmmNFZCIM4NJ3sZYby5px2df8qMFnL6Cy01VOIpEM5zwcTZ+29qEJo2+eusLny4a1VKDU2z93qe9FDkZ9oL4yPNIsggRhKWYTG1\/34OqIV1fY25+BsnYm4Y4jCU5r6hVtm3t\/Nrw3otgVR6PBp7rHz5+VwcEsbZr+3QbYuVqzdmxpAd5wfdX19lcJqAyfPBJQQYBSyqki+qUKTHIcLVj3owZYDZs9EkNbQcgv9r2\/dCGu2zBYfmdHK1wxmNqeu4KCr0CmnvVEKxreceRv+d4Bj7PdirdsI2PkFVDMCmzDl5ejKcc+3MXNHTzuPTf70a6ca\/fOyEbM2Ni8I1ijAV9G2e66lNUCe5+udDZi+QTilyIeUria0DDjvvq6vDpIykqMmRZPg\/rqKx46R+fu\/x8lh\/uHCTDhE05+VZQDO1J7rl60acEruuii59UKn7+9MF9lFgN+x7WkBnY3gLqG9oU+rjbUzHq6\/uDOAog+dS7ddrwJNqzRd0mW70T7xs0UIZ9sOJQcucTpdz6U7zGiXcijg51u1yZ2vyaILyukxVn4L\/hmTjL8OC6WN1VKNUXi1DwXiOnvg5LzcRcw4q4FXw\/9Z3HcA+\/9wY2d6\/AlEhkOzmQnvr1Px0GWyGOLPxUCgweywPtl+JSB6n99yuDEYIfErXfFSIgq0vYq64LnL5ebBiuk4Jroq8EsE3T4vNSPYqJBApuiruy2yAqm7zwyfecNGb7ALhoqxmrcc\/fDvP5iQUdG3tX3s0ZhEMcCEwi7Uzrw1by\/OTxdxuFQWdaPtrPfpq3WtaGg0cHvLiqxcDysK+mxZDOyXB\/7RPpJRqE7zQ637Ml4vjkuKf9pC9Kdaz3\/ls+dq2n1itNidOSc8Hv0PbQMlVlDI912t4PPJv7Sm48bIEr1PZubTBnO0F\/E9h5ohyHSIulxrko42PIooEqoBDXfeG\/XsumEzUsS9UV314L7p6nPEvJEqNd+Nz00REPu\/ebP2a2aMZo71mZg7vPluhZ1riKBiuJTxan3NBvx\/p6uVY\/qO4DrxfpKX9nBhd+rl61gSnUzFRhzWajiMpVhI\/QFvNQKIkibqKC\/J\/f4keLehb58qsDd8y41ZAj5WBI8nd+Hpox7QNwlfLpm7jz6X\/afDrvZg4S9Z16ytCXBMs6HXpHTBcjwlUPmPZlSm5kbklqO6ePPvJpaF\/zFsN9HxOQyb+kC\/4rhR4asBgOsr+IL0eqAk5WScA9y\/9rl+3APGZvXdyylCeWB0V56IVdAEz74dj\/lWB8Nj1X1b9M1yYI9z8zUd58j4KVLKzM2USgoxyG3LyekD\/3mOdKgPt\/XwKMUv\/KbMn34l1EH+MPor1FWjN5x0+7BnZpPfKlHOha4ZDGNw\/yGOl14dXrxyY4jZKyKf7tRXKuZ2X+Bf\/ovuEHj5on0q4Mw2hHA47euANQY31fK9PZOqaZ2+FZol67t0wArNqs0H3lJAomQ4bNB5gSYFXPN\/pDeAIPn0veU3O0G9Q6\/iW7HBnRd\/W77RTsyBtX\/pvEuSsb9nrGvUlrKMc9alZ7xgYyBm4PVPnWlYrzVe\/7QX7Vov04zq+A1EaMv\/dbdf9cB7\/iveph5pxal\/+49\/Oc4BX9K\/NITKQ\/FEG2Y9HpRB6dPGsbHPSRjxxQnX5x+Fyi3\/tRVCq8A6VVnKk9GErFkc\/sz8z8d4F2yKd7AowjyDuu9F3dox+nsBnvNCCqmf\/a69iajAQQfq76LeNOIXsczygLm4uzrWqzSkvVNQD5wJCDgSD0qzj6Jy\/1WjmSShPeGdAIkjCWF1QfX4LCSGOch0294ahmrwoq7vQv1PYbuFXmNmwteDNFxNU\/Nhxx6Ef4S4Aws7yOh2efCiBu5hfhLNdntYHwD9gR8P6A7MwRiarIxD+7nYEzm+8x1c+8Uk1c5vPPpnc3Pw9DiUeb5H5VlqCfA9+m4EwFOZQ5dVJAiw6TMKYO3A964Zl2vMU90BP7D\/0HGffivTzoyOfwS8kZtqEcCe9cvndnLakCTvE\/uUkIpbK6YPHdRjgQegoGPVJ9XQ4hJaQ7n1Ny7rh+7uj61C1SPHyS+tq4HZZkvJ3Tc60CDEKTIWkph1p8XeI\/W96ItiNzNYCg16kRaW40dvI+0N9J7YLT+xv7y661gnz0toEipwfSQSBlaMh0CtlS3Sxh0of6h5uXvHVLBvLHL03iwDAt+yan+5OkHnrB3HMNc9fAydWqKuI6IlvV+i\/n29sOWJ49iA0iN4Dmvn8J6trVnT23pW1hvV9t5oDqLiAE3u5qXn+ldqBc1x3o5nH\/YgbGP8qg3THrgeNoGocTUJnjQODotm9WJQWuTIXesHclboU2I\/AVynTcJl07FoDWfbGBWKAFtd54SoF1MgYnuKo7BpEwcNaC8cdxCw0PUg2M\/2Enw8NcA4fHfaDB7Zp8dGVoGRwM\/Dayv6QD+XRkrNl6n4GiFz7PWoVK43L3X9S0tHe6JmyxxUs3FC5\/DjrKtacLK6ESR7pZq0F5qo\/vCm4xnust1m6u6cG3POa8V7LWwxO5c8eHKK7htibxx\/PkuVLshwXL7eTFsjm6r07RPQekqjfZXL0rh6\/uJ7e2yGXDS7Lq9OW84evtfi0mcyQdvgl3Lda08aN7myF2h7gOiPx9NXh8tBbv9bOmCf0LBTXOQ3UDSGyOJwUZPMmvgOvcZp30sBeBqmLDEiC8Ulr07rKrEQ4ZDXzSULK1CFuJ8wXMtzispc++J9lC451wcyJwHc1F9u4pj+jbenucZLvg7xNVTUnLJYcDgHwLTVyKBlrRSr8UfCoTN1iVw0+G26\/UMVn0yAGdB2Dn9ZBj\/EFfUbFsIS2SeHyH4fcE1dxf70X6+wJbgP39diPmweUvGs0urk3D\/ny0rjooHQpgsq2mWVi5cKxdU6enJx2XuZ5rNXSPBS2fs5DvVaMiw41e9kZaJZX2rbGNekvCHfD73Dc883CFzY8OPa2n44QZP1jJLMqaX8fVcLi7DsZEHG7aWJuFxYas\/tw9RMMgnS+b3XJyfRDo2NvPGHSvsL4SQ71Mwo+Dyoh6xIhTIG9yU5J+DVpEbS1aN1C7wfxh+AVisXK72jpWGHIMdfLP1ldCSKWtq8oyCi9P1y5yNisFtmZdTGHsj6J0yEiY40CFbx3+IbWs+iFdqsddot\/zv37tv9Xpg\/9R9nYtPEZTNv7AkJdWAfwC1n+7WC9\/2NWYbayWjSFTA3XPCA9jBOBdLj66ikso+o73jjMkazn7k\/TBI6DUkY\/T672fHrDvB5IaDY9LWVgyv3+TwRCURNqRdgj\/iA2BveigkmcMPLAzDf11oLsSKyMzE38OeTJ0RvmKcU+n5+RBkzodMz79fsG7XMeeUo1XgvY62538+7WeL3YuWrqbjC\/e+Iqu39RBCNP9dFDmXl31\/dUXNiYaS++R9frXVguDglq30pmrwudcbv\/5hLz7OLqx5FtGB5T\/5H7l9H1ioS8fYXuKrsenGjL1\/AQb7F+rSMi4H7cQT+4H3g4n5ZqiFZT9XP1TzrgFrOY7PYlVD4LNVoGfcuRY2MTh4DN4OSs7zdpDpV8Lg8yCDz7Nwr7Ksmu5exFeK3IviYzJ97XDNG704NdVOTHy1uCJqXT6GnZg821IUAmyLUjkGpFtRS26FfEZozcJ8MpMfu1L30IW41Gr0+m36421PPxrZaNS+4GjEfbcsXrmf8obtnatL1In1aHMhSUTzZzla5Mt87zD7v34cg2cIvDweF5LFGlA+kdVbaKgN85fKJLxM60CaSkVfWXAVMv9\/YCMHm97SETAaffFIdm0XGKrG+97OrkIc29dyZSMJthx+1Bc\/RIT3x6xtT3p\/Q26nxz8+tBEhZMf2+m1NdBCRyFIYaW+DsKgr5MddxfDb2YvDO3kEmHUbxrw33FN8HtaypnCBJ8zkDEifTlLYUpj1\/8g682go+\/ePy9IioVK0SyWVNpWQXESSpF1EkiRJUkmSJBWSslS2ImTf9z2XPfu+jsGMGYxdJSTx8z3umXOefv\/OeXTOM\/c9n8+1vN+vN4snTOjioDb2Up\/GBirQBY+LPc5pwZq7GwXfSjVi6JP2pu6sRjj5uNZ4u2oG6K+18rfT7wYhbeUPzb9yYHeMmsvLp4gyEUoHHW8UIaf+01MZ0V64XmaXyJ2T5TiVJ1S+akEfSgytyHq7oQVsAn\/q7fFIBFLRqzNTzym4\/UL\/9IgzCVKdrrpaP0sALfETnTW3aDilpR5TNVuvvk5LH\/yRngLz+as+rL8yW6fkbPq+V74dCvy3roPgZLB\/4Co6qtyNq\/7LLcelBLf8n70MM98E1\/53L8PiwcaP\/xKMnwlE\/Yk\/kx\/qy6B2ZoFau9gwnt7Ns79rwgNk7Z4uPniwEvzmniMObQkNoynXQv3VBPPHdzqw+7yL3vcgMoyY+K\/49q0Ylvju1uTY0YayKdcWfNnQDjtfnubb9CwSkkSXFkt0zD63uboalXOGNm\/MjQId9jXKmgXDcGSuDkdz8U5d\/fEkEN+1SHCl9iDQiwrczyYk4YeAFWerFw4Cs84xmOPWwqH3dd66EQPg1FlONmluRIJvD6KPzGi2bg0QHiGzVa6Pjk3ZP947mBTB5kkenuw+EqiKLun5mN+FO0wU946a5wHDaEK\/ir0CTYovia+16WXpBHJNEsJiBorh8YfLI2YzOZARPWG+d3U8qCYIKz91r8MRWfvK1H43PLTJ0dGolYE\/S14FOh5qhIGTjEbq41yc+rHlXNUdBoowsmN72Btg+uPjIYug2fpvw7p9ytV92DKX94TMvCcmD3CVcpzx6FIqK7eOODfQ93hGt\/cJCmL8MYHW2ff87\/H9QoXtRegxvf7Kg8BAzOWZ2Lt4Swd29i851OQQDzFcxwrHe1\/DoVtnZY7btmEGzd\/N2PArRKska6p4xqLuXf7mjnkknDhVIXWUkgL87xNirYZMwUnxxfz05a24uGxe5ouiWJiwDNBSaaBiTPb3O5skC1i6JikXisqDDVngxt5k3GE3DFcW+dR81kc0O6Tc\/OJUAQycW0qx1xuGpDlOGj6VvOeV9CEZztO+fnfZMAjLAg48DHLKRQE+Ptsg7lyI2z9hePDvAFi+efjOryILddgFyinmxWBlb6PWfqETHJMV3\/35UvXvfcfMx8E9zq8ZsiXlTG4eMvV7kvYRp4cCamZ\/3+plZbP92mqS57fB3R0gspc247CgDMcXrzywYDkdb2+4zP54BRkqvUa9JbjqUCNFxjfPvBuvKd1U7aojgYfdAc4LhtU4LetM+XaQjj6LS1YH2VNg14enJ71LajDqgWVCthwNnzy7lgbxZKi3k\/LL72lAnZ44lefe3bhd1u9JQlkHTL7jNg1Y0Qr90hI7G7NI+KwnBtaQSyGG7GwTYt4Mk+uiJa6eacOxa6LSEl7FsPBcoWydTxOYKCxyVxNpx7NlS28sLa4Gh4PqxoamNDzR1H9p6nATmv3IuLwLPEDuxMELKpwM6OQT6GBb3ISlTg+jtxxrxkKJ89b35s9+rr+5I8GiHt2t\/+z\/6ElCboE3Ko\/OJ4Cww95AG92nEBzO+WtGoxaGL+Qsb62qRkpQ2eLb8ykQU9e07ltqJRafdaz6Sy1l6XaIeTsuo4lmrXSvZul8mLwI7SBPH6vLpaB\/RHHnbo4BEDBd4LVUIR3T0j0n17eUwQj61V+LyoND4mk9nsEM8JCyETcqqIMR\/1UiW7YVgFPfsvlf9Hog70M6B8\/DOkjPt73uNFUEApFlenmX+qBiYv\/1H2zdIDc6tJTzTRswf7\/cWVHreEl0oJO05Ax0KKzPkxLJvZ+Hy1Cc0BvUEOeezSWNIYuWMpx\/9e1xukga+hLn3g+Fa2np7cWooXTpwocrIVh1c3K+wrcBlDjwyjPKoQ4oG9sZfPcy4I7AkwvTskP4ZvHzPNrRWua9CSlE3lwt6dnkhbIqmH8hn\/asPQnMlatHk7360XyOT47\/8Mlxs+ZYxi7fRvTUcjpXcqsZVXbczAtV7sfq+UdjXjs3oJPATvqauFZk6gnzDkyX+C2vR1+jh0mPDRtx7O05aklPL+4rbcgwd07GxhUZOff5GrD02Lm9FzMz0CGa12WLtSsyfRYEjwgGRRbLX4yKYOWDMz8naflsGGjuhpXKKtdeSdOB6eNeleOmuoGLAaSrPqZ3ZWksTjjBmYF\/ODOQUCbQFjbQBRMN8gHsZzuBVzLp13NyJdyUW6T6wLQLjE6HKkZzdkJowd6u+jV1cCA2eunuTwUYGk1eqa5aB8vkDtp1FXTDRPLGo99V03F\/5bdkhlkDKHH\/vp\/ytxvEE1ONA72H4Hee0U6nmnxWLioxP4cr\/52fQ+O+nbxHRUOx1m5c+IINA9WbFcFkJgedJ7+steMNh4kN65MLoxj4pji2UWn2vJWPEnj94E4tRkjwSNvqDrBy7bVefYt2cujCB96jKl4XmzBJvlDMe20aWoofXz0s1YMBrWcMHzU04CO+V+W\/+nLxwo43ZxNm78nHi\/psf6hQMMJA8\/N12ZcovFrMopA9EGeWk9xVzjZiATdXXN9svSWpKVKTtTQBbYIMHgRo1CKbTf16UYcqDPf6zKvAFY3rCz1dCr824u6UzvpjCwsxjXN+4aqSD\/h5\/5Jok3QSpp0UWjleW4bp4k1SWw904Rn5hA7x\/Bps+nDqg6REG5Q52fG1H6QCRfFQln9uHygS97LyMj5bXu0O+HFt6tB+l364Spzz84\/bOdW6dEDCRq1HF+f1QoJ5p8PGy0ko8jrIOiC2CO\/lOAnYrqGA0LI1B77HN8G6mZ63o0u\/4ZG2d7s5rtJAp5kqJNzTCOnjgiWbt9NAqMeqhle3BX5blvBEVjQgVwmXUkAVDSRlDsZff9IMFkOf450vkZChRWPntOvDyKCVu5YnZOJmn7TbknubkODwowKRe0Vw+PFaVMURPjIDeZ0ZaXrfwrB2pv\/Xj0d1qDnlwbjT248y30ZS88uDsHrvsoCMmDpMOX9FT12yA01eb9FW42jAjG2rzh2UpuAf9cD01k2duMxz1\/Uj72tx+0WF43YBVLxGuu68Nb8XmPMQz3ye14n5STiW6me+NpIBe9ZpifmP01j+RPZ5V9XOljBg2tVtw7sldAz0EHNaJR+DHjun92u97QHn5+3G9dupKLfOIkVXMgP3n\/89+vx9N1z5lW6fbduJE0FPRlLdk1DJQ\/JE4q0GXMhxX62msBOY+33D0iizXXt8wH1c0We1Ujeypx2Nm9gdjlL69xLq\/c0gId\/mq\/ckHe6u87q\/6w4dzdnvWP6Ue8TkPbK4oJShmGe7tB1hcxR90iGSBmxmcU6PD3Xiafr3q+cuaYNfAE+F6UQXMAqVQxfE0LBEdSCGOvUFFbdOHfKs6gZ+ds2aDUWdeEjNk9TRkAeGv+vFp40aoF9MOWhRaiNMXRH5+vdjOvgcYOtaGzhbHzncfvu1pQHG6BeuqkxkQqvqj6\/yuTVAKdPJXXm\/GVyNL3Z6DGfC23zOLM7dzXDvMPWPaH4LEHxXPDfHd2VyA1DYL+rd8L42JPiuTD87krVMNeRL23DdXD4Ic0+KbZ\/YDecNkPFjtw2bilYNsq1U+WWyk4FhJqsmOyxzgOkfYeYjc+fJy7s45UDc8iyz9mcNIMChrD+S34Cb53IN4Agx12XyFgzYez7c3tgOqcQcmMnn0V1yqt3hLhko7Ueqlzl3IXuSz4RpHgmEldrvzXyugE8Cds0C8f2wgeDzHElYVayQUAl\/1acFAw16wbpHt2IndxPyiCXetP\/4DSjTt9ISrs\/2v2Pey9jsEXM+up5ey1EDEkHCZoOMaojltjORmSlAm4M71JPTKODM7nWP80IFiP0tsVGtLMW9nbmbuXwqsPOqWtr05xbgvG\/73X0VDd4Gmu8Mp1aip1iyV+HHRihXtHS7MK8LLKOWV1p1dqKZ4nLxoDc2ENXmbi1q2Mzk1zFzHpGZ82i5JjBf+tgwJhH5Wa\/m5vPot9qFT8SyA1WOaGWVypHA1UsBfQaagRGd\/2afABU9\/E9JvatoB8sUyaQHh0kw0PZs1\/rKF3hCmtdJ8REDnu5avaPmeAuKJeS+NeMMx78hNp8rzHoh7pWdc3pKGx7fXur0bn0EMnSU3N\/1dcMeqda+1LtkJM497Jg791h7gYUdjSvirlMQ2gd+hUz1YFLy0IJidl8YLNhO++TVCsfo+WpbRsrBIrl74UgCAwyLVizJk2yHESKPhrivIYvucI+jhQyWW5b+davLA347nzPnzvdCR4Wzbsgg4pll1rQPCeUQkrMwd1yoF81bfILXnIwHWlhd4w\/zRpBryv4z\/wMFjVudHGJeJoDDWVq2g38tPBn8VvC2lIrXy85PK2okwaa1\/mV7TzSC15hCiuIKGvIYmPhopOfBZPSfNUnNjVCfEPPy4atO1Flg2lZ\/kYp7Ik6OeJX1IVNv3JDqe0E+nwZTMa98Ny0uh7ETV1vey36FszGkYytEk+FShr6BsGMtuH53a32mSsez0soye9bmgOWSKx6CRVVADeXdIH66E1WPpD7Y+SQbrIU0v4maVYLuJb3rdoe7cIFaF8dr90JQCxTxH87qwIbmM6uC3Btxe0ncNfMdqZDwEGT4+drQouyhemROA1Lnux\/zKM6Glaeu3p68RcFd9oyTJNsmHNwtVCxm+hnWbHkx5O1UiKNjcm6SXS1osOdQW4HQK\/w0fCY\/SwexXPTP8gPn63GpVcvvE\/MeorZJ086p8G844Dd+f6N9IwYYuG17GhYCcQ9WCYRT89HnBp9dSnwd\/t6xPNZTvQYNynJnfvk047qyo5m7ZCgYupUteFV9PXr9Nfu1U68B97N12JTN3tv2VTH23eN1mOrxUcZ3VSuuDTThsimkou\/1c+JHeguRh3fKwTK0DxfN5ZWAMee+R10fctBRZZn4pHU\/ds\/x\/6EYQ12Xf72LuRUXX98QqsW1bPmWVocZsFtj3bLFD7+AeahBp\/Jsv\/Pae2tQe0o3qK1pWTO89S6YTphQ7kY0oTFjoPA1dy\/kr1i46I\/WZxw8N9JHjW1AXd\/D672v9sDeq0k7guobUdjV\/v2hpkEIuhP3lF\/3Gs5\/kChkf7MBR9L9cjyu94PMzaXOGcafsMS8wGHeBjowcxw45\/wOeC5CSmgohIoqW1\/1PtPPAKEgi5+L05oxeSrrmOduGrqXkwY6FsVC8O2butSQVjT6seYHPwcZBb0fct\/fVACfD46nfHjZCcYrr6GuYwcKcLk1Pm74BtM7XmQ8PTFb\/x10dMurrkV6oyDpyjYSS49qd1R53\/v+GmTyz5n5Pk6vhT6J0mrwV+8JI\/mTzSB8JeeAvG4vBHk3Hp74W40LnqNlz94GGNC8asO2uw\/yyr77DdnM3u9JE4svujTgpp0LVHg7s8FlTkfB9Hdj8ZyOAl4dWCSdsWgAbslGBiifykceh18L5x2tA4Hv8g25Lc2YkKqYJayTijKGU8MNMX2w68ofjplNBXiu5SF30oYk8E8Uvr1nHR27Y4PvbOEdBrszGkfC3pUgs46KOLHgyYMxEp7QLTS74kgHYzURpYuJRXDfyaXDoJqMQ0YjCoM0GrQf+my85GA6jKSuGVkS3AiRg0G+Sp59sD+L20PdphysN9PSFmrR8Vt\/R4E2tIGBV2XUTglvvLCfKzOvtQPtzyQLtyc1QzZ\/wkW1uBdoeXuywpCjEzUG10sp\/iLD9Yi7ToNWMZjtc0JQqoiC\/pt2pHbJtsEwl3fIjr0f4azoyT2KTxNh3dIHSzW0BiDPafwjv1IpOls+zThJaYSlZcqOJL9qKIz6bSQTOIDuN5b\/dVYgwYpHPX5Gr6qZ\/Df8xwfK+pz0+smd\/Oo6iLXqqQjsqwLDMxr+Lmz9eLImaudCjTp4G1mrnp2RiadXb78XpW0Bus+DuuXtmuH0eOiZXWEJaN52sfLUIjcc+nmlmudhMGSl3DriK0bGPtOUt8ZSiWj769H9fI9TsHro\/bmtFa0odipl+JLGdab\/FP\/xn4Id3VnLtrsbk1RjctY5dqJj2ce0BUYFaDcvxapsDR1Wdr8Idk5oQqM3en8fXI\/ACM7rhrkvu8BqSmGVfkEjWkm2uT0azcSMmDvCGpE9KDjyd3LNjwzoora4r+UPhwQK++VFEj0oeiH8TU+WP6j0R1et3f8BvF+Q\/nxnp+NeXNG7QDUJvGwWZZmLfIGgruKPmhwkfOf+zP1bXD0sERNXPbOFDGNH8ipUAlqxNvxS2ou6Wrj45NBiFQEKqM0na5+TbMf9Fvrk57vbwKvakzd\/oAA\/vfqpMdVARfZwwz0nFDrgczjZpaAwF1fqZtzhIFGwziPhHnssFWR1LhjKBWegzNFzHbc6qHh2QWVIJHsHpC3fojvzNR2VrgjEn6cGYFH1dhmdFwycanhsZ7isGvM3rXpk9LMOln7euuJcZhOE5vHfMTXuAqIvxn\/6YhhYudMuaLZuYs51mXtMo4o7L27xNsBKms8xP+N0fHdY4\/x88RpwqluiNq+uDpSb214ITOajlJ1g7GrrOmjbtIREzqqGbh1LDe3QdAy0+GwoPVv3rB28qGRkXw\/PJHfuFPqZgipvy+47zP79ZHe6dW1uAwjVCjWurvPHL8e5V91\/XgOqYTfP7PMg4Rut+8YWY9lwuOBm36OBXnw7z4tz72x9ydTnlM7x9ODImvX3rSwb0d3E9JRrMQOJXCoQvpmw2wprMfpkvvXjL93Y9C1FIayOAhufhFBen+jD\/QOLfhn\/amf20bN\/t+Mq37FePPE274maPQWYfF2x3RNXP6b2MnV9zP4aeRvPUPgae9BxAy\/p2+F2sPvezH5ZtA7F16+nflSerVvzEvkXTbdDgQv73vffK1FmKm65i3I17LssA+3XhljzfJlDK6Kdd2aAwRfJbN64GgyUTfrV+KgLMtlC1T0UyUjwEJi5Ceiqakg23N6Em3sK2GJnv\/du7n3lkSQGkuf6CGBy45n7i6Q5\/jkzh5S17whNky\/Sy24A4\/n2+vULe8CnhcP5tgkZ9X8NS4z5tMBKIu+GuB9xa6NC8mLbFLTb8EPQ80khxtqdm5eQRoOz457BNWzJeOCFhNvVnemQERC92k5uEIuN5nXvvBcIY9nLlrxYUAdGcp1UN4ly0D1uKDJwl4EvCvibcs3LIXtEyXxelis+rg56GpDbg5f6JmmejmVwsKttw6h6FlKmX60uus5AVaXu0sMra4HHZzLCwz4Y7765udbVoA2YehtmXpvAnB4S3szpIZHQQ+KBp0O1Lotagbesk19QphVtGfTdn+y6sZlL\/cb327Pf79+fO+qOt2NRX+nbverd+CH7Gdu8L61wNmNx4aOd7fhJI+6aqnkX2sSITFqsD8VPb+bbZ92qBP\/3TZlNmjRYVC\/yKfroIOwJDpz2kKxl5bsdmctjYt7jSOQxofrKdXf+x+sifGGs3GfZ06twICMSGQmJ148\/q0a64dVeXhoFZMyvvhZ7lYNZAfVbzN9V48V5iYsKLDqAQpbxMJ1oR8UNV55cb+sEdf4VoHSvAC0KNvwqX0zBltLFbQHzqVA132zBHkopOsl96lQaIyPbmBB5hywNBLGZ31u5HDO+CYntuktBjx+hO648oYG9UfmRfbRqJPKs8Z88ayB4j0w9HhC8RyiQzVF5spOKD\/vbAptuNTJ5syD9lrPxgHEHrKzYcKVhRTsuvbNuSGwVGZHIAVSdy6dg8UgtV674NX\/xN9jce0s7o4rM4peOz\/naYCvBwWDeF6nTtWM\/h4qBbdeFc9prSfCdb8BiJ70Xho8v+GsUWwRtSr3j\/mpt8OzQMpXzu3tB03lq2vLXAL6YOW13iCuNqcOBYM\/7utdz+tBpqGNjW1c4FE2XaemNNMGPZ27iJ9R6MK1etG7RjCEEng+deZAShQ8TswY70nsw6ERZ5j3HAEh6ZqpWVjxbX+Z6Lno83IPbcvSDvC5HY531K0\/jglyMOTrZfk++D3EyacR4zztUWdZqdDcpB3l+5pXyXWagf\/67xTudfFB3G6+B15Uypu8SD\/3Xd8n062HQf\/16+EI+WOR4xBCavasQ5pPNwBgiF7KjSnne1x8DaNwwrtMhEYQytXpFKx9WICP5pq630wDWhnDEi2xIxVLbI5oreqvxqf1VgVGVDuC6o6of+qYGSHn7Dd7+zpitp6LCJt3zUHPP3hiZhd3Iz3mTK7qdDLX+F049vJyJBhfe72sUpuNCwWUmwXxtcI\/If7w0N19l1ZPMvEiNubxIVj1pfO22\/YGDCH53ZX8+dugA7shdnQ2rymAZn3QStpeAfpZU1eb4DlA2vPR0nmwJENx7+Id7DyJz81vwmJvfsvpBAf31QuekKeC39bPB4ZZOtMX9dS6DvqhidSUrvq4dLxE59cycFNHbFVde51Lwa8pj8ejtccz3DYWUFwjtHmvHQ4RegllHRTyJDK1\/2oZZJ3aR79X5AP+rbXre93oxZJ1Z0J1qEq5q04\/Z2hINtpc5XO5t7WNyjGHXfznG0LtFysvJog+4X6pmW65vAemCPaZhy9OR0BOyeM6EnhC5rQeirkQz4KIkufuofSMUf17O4ZOfimEBE5brFPthUlfwpK9oE1Qu0HLdpZGOZi9fOl7g6QAngRXuXFzhuP26Un6mTiRmBqg31f2mgluSpFrAldn\/7hMX3xmJ++hV8\/dR1lAHFF0PaFvjHYOch5XfOUd4gXZ24fOLlCKM0AFO\/GILbl3vNX2lyUxeJRK8SuacHFIzIw+mXKfiC6IOJ\/ZZcJI4D+8QPlnmeehK7tx3+A0FTWqP8fElFuCyz\/xmtV97wJmuZ3hw9v07Uu6iYWaRytQtwzJ1XT+7fk9YpsbtcYA9DE81+ex6OtKJh9kf+umeikdbUZqlVpsjdB\/YmrXjOxUJPwL8k5uGhB+BlePM5E5QckMP7A8OZOYSMnOm8IiZw87ieDMg8geZuVTM\/Aj8Jz8C3rTWcZ9VbEdlUqb2pgwqdLWQffsianBp1\/p3B4zbUXXF8S0rGTSA22d+5U40oLjbHo6\/G1vRlKvkUvTw7H0j6SayQbcWhTK16nP+dkIokQM4FjR4Xs+kG30WK29d1UIHE4KbQeSbAKGfh3\/083C1w1SXa0E8Cht98VDq74aNhI50\/5mtZaOSAzBSZ2qcz0ZCgtsPQmYezuGx\/cDk1RB+cyg\/wRZwJ\/V\/vow6y907cjDviR5XfwAdquVTPE+GUXH52\/BL8i9y0WOg8Bvq0kBz5PK0dFsypK17c1fXpwcsUnSkdLZXY4ntgQGXiUiwGJ+pKlnaA0qVrprsWfVYUlx0f71oBXRF+fvHejZg3zmymmVBPty4zRuzTbsSQntNm4Uq6nC5\/u231zhSQfzY1C5HRiIEkt22fD1DgynfS5MaU8nAu3CiSTvnFahB3q7HRl3gfzn7Iq96Muglw\/sY\/kFUuH3d98e5PBDz\/vH0eVo8dH2YVtd0bwNSVpxa+4tO6PM58+mzwkdgXyRycutFCqyufKRy\/SENRtglFTIV3VAj+PTzWDsqvAyF1iPFdHCXHFkTa\/IBbD9ReB7y98L7D9\/jGg50IuE7g+0PMnvGhKqgUvz4fp78NmiPnSyo\/foNBzVkXBTp\/aycI+Z7tV54\/v40gQEkdAJI5KNh+U5n12NbZs8nSY1rWep5eNPpua+JYjVo7l+dzv2jCtZ2JCpPUj9jt3eU5U1q97+5n0z\/\/r85oThM3DvKujpjrUVdUPZG4sOnTZ24JzD60U+2GpzeGi8dcrmLlSPM7K8J3S+Lx0jM99C18ObakwlUFBr+IPUgmg6Efgl8b9j\/3KlGRU0TkWwnbxoQ+iWYVHCQUdfvwF9vJDpsJzshJ9Yym4tCgYWJGVwPRBhQa9343vXz7PkGbI4qirO\/6yZNJa2pHmDmxzF1UJLqbA135buhu+XD1bFPDWCWLb0+2ZbCzNfAf\/I1wNFB4KXSukJs3rjiLzWtE79PUo02hXRAXdzfDe9KqWi947aumB4Zid8dZPHK6fg8aoPz45uebxDsAwqRb6tHCo\/9c54MXemf9NoVGGA\/LfJyY3Qd\/rXqG2KYtaDK1yVmjr9mfw\/tgq\/zHpfCarN2tiXnimCX5fT3B2zlEHh09N0zxQF8V6hZrPvgG8xfoBQwzVEGNN0PP8mSvWji5cMn0ZMJl5xDFlbblIKqzKKqttN9uNTILzPx6ACWnu5\/Q+dpY+kBVm9d8Xft635cyS1vv4KTwtojT\/UOHBMyHECH9Z9ulG2a7Vvn8tRwMHH+V52iXgyjDQeJvSNDqUsOCitEIpMXR3D7WfpAgufP+pzJawrNEtXM06bCXRuBl85xFLwXKdGsJV+GZI7Nx\/0tKCBdH\/zHZbYOjzvNNzpTUo2f5rntc\/xIA3a51P2xL6ko+oo7Vm\/2fd+6PHGFbx0JqkKCdY88SIdPIXbKt\/cUYbTytpB5BT1IKSQLjqmWIPvgXxltnno0f65vqHC5EbM5X1K+L6ezzkMRq1aS99Na2B3YtJY+PVv\/qKcKBij1YMqrB\/NXLqKDvvZf+RerQpn5dPhiR9no4GzdHDXHbWDlmxP8ZCD4yax+bd5a\/7ZMdhoEeUi3if2Ig75nMebDP7qR49J63tc+VBiqWVKjLp4AOa1h68pnevB1Ja19cWUNllMNnX6ytcDpgqtujk+6gcjlASKXh6VP\/u10KOLBbD3EEbvypH0FDQm9JcoKdZ67N0EGE8kFoBPeibuoePDHmk6cOdzsrujbBv6jUaPnfhciu8mOy58Pk1G19O0qTxEqkEv3NH0tc0DrCj7Kl5Qi0OSoKdntSwbHB6M2vQHmYDz6rOvUmxZ0\/PFVwe9nHW68o7nPhdSOMQ7e0vcs04BdbafxpaROENIy+mWrSAOVqoAJxW3NsO5EwbXa8C7QPLbjnP59GhBcKUgS+tHdI9UFZxmcvyl0CgxcfD1O1WmEHMEdd+T0qmD1Z9W\/Fee6sVTvbhaXaBHKaX8WOWrYi4d6fSSmL2TCxoV5pw4If8WFXKSf49YtrHqM8Hfg8u4ygVJlMmufzpyPkaR49FzPt6C8ad+bQhE15P\/q2Px0pg9lko551ZpTsfl7x9\/TL1swMb7nWOrrOti49MVEnkcRSsGzmJgQOnAe8la9c7EVEl+2rfXvyAUOLm4eHsMBlt5+ZkuXypLwBPR4\/vn1tvA20OxqvTSzohYrV40\/jboSjE9IF78eqe0Ai58GTylWTTjy+MFBvU3NaPZ+x7He2\/Xwu8mx8WxrDiac\/BXxLL8RfU6Twq84NIO2ccstTbciVJHnyi5QaYHHTgMhStpfsfYbLYM3oQqC0xWz2DJ7gJmPWUW8D7fbx2\/fT6oF8aTsvrXK7WDlFrEnZZQKsWWBBjnx1dCpbBkVv7gF7qdoXBlspMKG7qODoZdrgVzsSOWcfU4jKicb1+d1wDGlRLeVs3XTXnaOk7o8FLAeGkp+Y0WFhLnvATnnvgdkcpyaH4XV34BGOOd9\/O1e0WKW39Opgk3eagkd887IFa2obMaeHXeTxlVC0eaL6OJGoR58X5Xp5EIm462PD33lWvIxon3cRsWdjmtdRWw4zpPwEq9F1NTNHIzrueJb6NeFnQ5cC5eca8eVzvoDV2QyMYrrgeTb3VR83LaseXxVFZZrjshRLbOhay5XlHkvsO5NIj8UFs7lhyKTq3BowMyn8TcDrB18RSZ16\/GOoOMt6rImJMUHHvgR14\/MHDGC4wGq6sFHO490oe1JfdWS3kY0y1uc7LTJB0pOnljlyN+Lj8xnJJKqasGhKeJFtX0qGEtwlwxp9mKtrGhDoXstcB89blt+xRVUZo6GPO3LA4PEKvXCHV2QxDky\/OJOD5zVWneS43wOZHdYXQ543A1MDlJxj6Si\/sFiSJjn88R+uItZB4L+WjGhh2sQeJ5fVpHy7wIV342h3pfpsDVJtuvg5jxI0EiQ1jlNh8k0vGD2qAvkw72kykO+wD3r62VfZ\/\/+zsnQqOT3zahzvmXMdXcXtIRdenzctBOkFFSfJm+tQKcz0u9ztjNAi7ivOYk+dNN\/fcFII3zB3jH7v\/McTgH9Q\/vqpSjx+G65x4uD4xR0vd1peNomH8qznDmNSqJw4dZP7kvvUfDSlaUzK4vC0HqOl4KmzXto88oHcdcpipeBuBmTl4JmhP5HPPPNyNp97ZB3inG+\/1EdxgV\/F5bn7QFHhXO+J063AqZ9tgg\/1IDuTVxvjYEOF407rChH80F\/RopD0ZYGBI8U15xLvHgsuwQSfzxOTKikAcEjxbeW39k8rzfBlMqH+O8TjfBSr5Y2+S0HX+5NHo0UqAbzAlmn6pezdUfKYqv+Lw14yodzx1GJOmBUzAu\/UdoF37746R2Orcf3x6bFdH1rQP5V1G+bp11Q77bsWcn5CiRy2\/Gf3HYg6jFk5rYT9Rh4SWg7\/xToAyY3PkHr1s84qTI4M5Bj6\/CxHbM\/hO3Gjk649\/HHBRGNIqgeTQy2qaTidZqDxq3Z++fBgq+2JS3JUP1wx\/u1QjT0u6AevsK0FEr4Dz\/r5qLDRy5pSb+tnXj2xMOXxhHV4O6tmWWjNnsvdj2OEM2m473OYWlP00pWPvX2wQ0dB2brQgHqm7rbnKWwy6Ht2jGpbqYfGf7xI\/87xwPmHI\/wNcM\/vmZ0WVk3YD\/VAgHxKt\/Nl5Dhk8F9F2pxN9Zd\/nzu4bdGuDu6R7NyGxmKJt5kFAf2IOErhH98hWD+33kpU3fB7IPgnz4IDrunpfWPxoDpYvtnrXzdYBi3aq+cBB1qg5IvyRlXg4XcI7n2yzRIkTP7tfwo7d9cZmDmMgc\/NKrKesnA9f6KCuMNX+AOn8DLzB\/FyAhh83VBBlrdil63rj8RJlvz2t9P5OKQ0Dfeb2v6gMiFZ\/2+RDrtf\/9NoCGXcmV\/VnENky+BUvdVOwvVwmDeHDcSNIm88gKjjQ9MknpgqM6BcUIqF0SjL0U7koNRao7\/Bkz+G8EHg8KhuojSZAZ2EVwaJh9SuLRl8d\/IRljl8Pps7udwlAhK7012iYPmybJXhxaagVKyzIYrm2thckXgmaUas\/XGAt9S3y1hoMrBx\/NhuhJOlK\/\/kKlNwSGBGx55DAqqH2t4\/PpPIRg0XZImideDqhqH1lHzGkj9nnWhfqAci9Ymqef3JUHn\/fhbN\/bUAv3AhqfHl+Wi2OovXvu+JTPz7uGfvHucCBUuOaw7W5cQ3H5m30pw+\/Efbj+0HxsTOy5cAMxcy\/0vIrZCpxMMavXZcJ8rANc5nS0S+cLonDBImrSZ7VdFBX7mQgicupIpelr4K6zq+j3vbRYNLppFrPxbQ8b7S\/ppVrIhoCHMQXqzrhuOT3BUn2xqRQp3kEtIWCzwJMnb7Deg4T2D6BMHh7qQXhZ524IrC29IOZFmEltR8sbZJz\/Xd0Lado+6+z0ZuPDs983cO1rw4hVpTtEfNHhhtt6u8FUxUpQe3nHRb5ytT+9vNB2ggtXpirOJwSVIzFvgn3kLGvnpJui0UUHV182Kt6WKxd06z+mzXMixAzclkyKPBKWA5tGS5DsDOXj6lOQC7lOtaC\/6xKLvYwxotE6szbpXwOwjgOgjkEqc8z9tODUWNTEgorjw+Gv\/VrS5dkzhCTkFKnk3JriPRSP\/swgZizd04L+aLO5mGA88h3UjU+xjUXVu\/8LUWwJlQm9y351w1Ey9IDvp3oFs8dJGzcd6wae+6qDEnWY8UnHj6JF3bThvY\/KGy+ohkMa7SW7\/slKQS5URdVpNAaevQkf4j9KhaSzdknt5AShbWHuHKVBBfmLLh5fSNIhZco\/vB0cBOPuu3q12tQ14y\/4Ie4bSoP1GS+WF5jCMu5w9OWRkhvwDH1bYktLBaK3fSdNdoVgZ7Fc5yBmFTW9\/UaIcg0FC8K7qChc78N+jc6SizA6LtE63+2\/MB56juqcSJV+BfHcb5EfEYO\/bl4JCO1OhZi5Xgvl+IpErAWlbqm+wx5Jwd5QzlUedgaH8Z5TuOdfDzStH62cMKmD\/vvdH6L7dcPTVqZBXp7sgdwbcjQ9\/A\/XPv+sDX3ZBMdsJRqQRDSY7zm93f9PK4m9bz\/UpwN+Wk7u5kgTZ537M\/NzSzLoff+Qsz+y\/FcryQTP5Yy2ZN8XnHQ2EMsKPc4HgmMl8kv01ZZICPHM+X9hAcMx8Kh01SAkeID\/2JC3Lpw\/oS1w8Wopb\/9XrIlOvOzi3f2TN34j9IwYa5+TvjYxi5Qv4bX5E2e3fBPIvUm7tszoMSiRDBdmkfpyqvL3xJkcjaLyJ1SucvZfCzCfTzygWM\/Ne0fZpO2fz8CBOX9mzID8tl\/U9V9EHzy1QrEfSLfOfj69ScWQ6JUZssgAWpszXNVvRjBPPOB66m1KZvnLwja4QqLBoxRfrbqabNeaz+F3vb90xOMgxwJwDwFMipzgqyqJOILIfnTnU1iaOtgJTB2vodlh9+CEFN+REPiki54Ck18d9Ig2NuO2E+1KuQ0VwlWzMaBnLxadmW\/Tvf6Vh89NIJ7MyOjQOTx6tudwG8+5mlwb450B972uxyAO9yGN+ZcRQrBVyDx80F\/ubA1lXF+x+WNGOQeVdx0PHc6Gc02n3Ip8WFIuMopkGM5j6ahZHQv+\/cz9kzv38kjYfXPUrCQ1mSo+m2PbD5osWn28UVcF86Y+mD+SrgcmBYe5Du7nHbqxzpsEHyo8dRpEUlp9aiN+rmuRFA6KewdW\/5aTqCv+fPpzl+4g6tCq8dQcVgg6JS5xJmf3\/aLmjfLeaitUDVbrljzrhyJ5JjeNC7ZglN6hBjaWgX8\/OMd7bnZAT1xP1xbsVzTYuHbahUZF+NNfCU7wF9llQdY4I9uINeuyw6HANBq475aGmUwlS8ou7Ap8M4DgxrxCx2SzGt7oWeAPFLFe09iOTF3pp3civRbmtcGl5e02\/JAMTKqrTzjvUYc6FAZlwiwoIEn8sdX4vDXkk5m\/qkOlAb0Zrrte7FIgRUXMlj+bC67Z+j3m6xRA2UX2lNyoQ9B9O0nUKi0DustepDcI58M5GQ70kJR7KeV1vRegmg3qpwcOzEdkw3GSpXvuYBt5m89RWneoEZZOszlvhdZBlcizOdYYOUwQPgcndvTAixKBV1oLIsMfZcyfbUOJGWOnOvxTsrpXmuPfHCdng0etTX5pxz4lFh3sOdYGpS2xYkkkETtW+7\/vO3oYhQu\/9GUe6obyAf6O2DwPWVrilTEslQPEBUZlGnWC8f1rlYy1fKGZomm7lUx3GUsIvQ+Qmo+xcbjIyeWiab4sUpzg7wdVDP\/FOUjvUqAUKn82nQEzq8ya1eVSghyRIxOxoA7t+h3nWFzphcw+b8rEWEgrYlF37PfvcvCsO3ZWt68b9nbf3dt6oBbvuwxdHTtAx5eJRy5PkeqTyKlzzr67CnCktmXi6AxxaZSoxJUsG4bnniMRzBOI5ov0+ZduFrypYn+cQ+ZKdej8OVLzzh9N29U+ElT+hu2eb7WVLBlacHFtleyUcJA59MUOLFEyx\/fw0NKQXE5xP7zpG8oAdg\/pjw9qZ+EWj85VBQD9qV76NOa6Uh1bCZ6lJtjVAiePYs3YRDcJ9DkU5ri1jcQwI3QLK2ljr7FrdDX0T5qVrXArhJO9d57opNxhw81wkFtQFskeT5c58LIXCQPVxhx0JzFwb+CfXBgn\/Hfzjv8OPdItA564CmFmnWvFtdz1y\/rpwfmrBbB+\/VGBsYgkNmP6FRote6Xr3LggU8Gb81qAx92Uszqrqfp7dQzVU+LHHNyB5JwlF3d1sF12ngcFNul36hRgo\/\/v+165wOpoFPlXX2p2Joz3DUWYb6zEuzUixeW0Vjmz3XDzz8R68lvTecm93KiQtVdmexzcEAnO+OTg8l+cCtnN+SWDqvpzPHoux+lYHTJ+InFjtfQOdISgWyWo6VtuF8zIk\/yYIVUH+AjlRl8ZkyDIIvfdyGwNr9uW7+w2Vw\/b3vHwZT2MArjcLce\/Lx23dpNVB7E34Z+lQSAWVBlzKqtY8haWoXsvp9\/51PY6MxF\/8ZD1bN\/llRgdxdqBQ+MEgkK\/D7Vkn1VyFe9Dqx5htqyAZ6Y5p683aybBJvcc5fYYE7w8Iri9Xr8a4Zwy\/0coiFLJ8EKT+iYxibtt20oVK0OmDdv2G9lxc+KRFP28FFXdpTe1vfziExD0F14m6tMKGz9osYRhVl\/U84iKnQydRR6mZ7WsMq+gFmPPXsHT1qhq9Nwbc6pHpFyDyQ0GC8OfOm\/PnsuZsBzz5ckznF6D2T\/Lud7Z9kLLmVdOuMy0wNhFew3eZhpJSw1ncMRSQd7C7O1nxAkbshGve72lBZp4pc4+8QTFrWedMK9N3DD0EB2n9OH9HmkwsM1cI9mt+Fzg0XYLac3nxzLoacuby4pF\/r+QWIalWMFG6lvTsf\/fbtyPj8gvzofR+XrynYiXSdbme\/k8vuDavTmPTwFe077txXd2qGTnn+h2Qf+giVr15AGn\/zdHDk0SOnnzg8k+Wp4thunByUnLNIPN7gwGdvKHpmhwwXKW5k8uvD6Mk9xoIpzaAey\/tSvTNOiBJibMXBFUz+TB4ur5I4U5hFYhs33ohwKuaNX84K\/c+ppuvGpnvM3P\/rv5f\/y8w9\/UDB0bfV90uQWb+KfP7XP3p7lKjmDB0\/E67xUtpAJ\/N8y6UtwTDOoVAD\/XnsfjcLGjF2HYSvBoQ+fzyTRYsk+JY4PeaAUlzcwlk5stYkxdOqAqFoFMvJV57SSs6L7xwIksnH4NPrNAzPecDamMJD4qlZus+cf7qQxV98OSdpcDWpX4YE2FnXbKsFe7M+fVAj184Xno6Dq2edd3daUWG1tevyprFZ5\/DM97nnNfaIXdAo\/yeKpXFmSE4FcDkVBBzACQ4FfAPpwIp995Jcy4kQ8HHKBE2UwpOLQo5W3qUjl5v0j+Gu7ZCc7eIpahQNS68fyfPNo0O+24rDdV050OEhMpBgSf1uEhy+PngzX405tjx4ODdHIg\/ISvs1F2PXfnk5N07GWjyTPbesUvDrHnvnspdyyI8ill6iUBC\/zaPeF6W5we4jGffj4VaO+p1qr1BNc2wR5q7DA3hShp\/YBTs\/sB3NjytgVWXDi6Xkfk0248laWda8h3tRlNhr2TSUCU65Y+aP9RnsOZIzDlMPu+9N8bTXbBSs2m9dBENogtW476KEtjen3Mqb1EPVL\/eddUXO0Hg3FF7J88iaGNUK7M7DcMhIs+R2W+GSNw3XnZzmJX\/mEjscYhzA9SIc4PovzBop2S3gekgtLdphSzUzoXtx5WWLDidgO\/zzdfUeQyC+\/GZh+bnk+Er3\/iSc7cymPw6+IdfhxeSOCWP\/sxh7SuZew1d8tZdu\/MTIT5zI7fwsQ4kc7z5cMaMgT83Bq+59D0H8sZ09+VXdmBkV9h08lgPiky2tS+ObYDTvw6sj1o1gPcITrik62o2ackGaOR+dq7Erp+1PzLn43q4UqoOQp4MCIob9+GL8Ph1Pw\/VwvyDN\/V4FqYj5xKp+k\/qJSz\/YI5IX99wXRbOnMY9R17mITMfqtz0fdkYFOGUcbEJlufCNaUDd6T9G4HOvmCevFw1KvzRuGXqWQClu7U3nvnYCOYfOS9YbSrD+vPTI6QtRVDMod2vOFILUqfHe7c3VaB2sebA\/IlUGNryibT+SwMQe09WbpT+3N4TvGzYVj+brYNMdLOqJGf7e99rTsNOpxJAPuqdzG5aJ2T4ipE2SHbjWMr3wB3r0+ETu\/BmdoVG+PZ57xfc04UEzw1e8ahvfnCvCSRLRvemO9Zioylj9e+GBkw683LNIakGkFWSYGzpa0Chr7S9bx6RUDx8hlvrRDWeSteL6vuThTHWbOZnOXtgq0rH5u\/DFJjgLLuQ2NEJLxZfbvtAy0P1L6a7anloIMGz317elQ4p4eNV6osRswxjh172VYBum1AEG7bj9Dpt4VeqFDxuVZi\/vq0QGXUuYTHDmTjeO3VbZm8+knIviHntbYX9vKXLuy41owjvozrvhhLoe90ftNi+l8X7NbDyXLRXgoQS9x\/M1Mf3I8G1Y\/roQWXp7TUH8\/tm+zLLC38pJCZPD4789zyHTcR5LtX6VNzJiw5i4yn6m44nwZq4XTWBXyioH+bw+VnHbH152ME2yyUPcvJUFMibOjFn5snPyIuP0GpcwfJwWw9Yb9WJFHv5Fa4bHXtXVZyIctLbX0ix98DA9nO2kb7psJMmO9qgQIfT93nEHLkSsCNgqNjdLRFNfr14qi3aDRNwqC7O7CVKFx3uWZAUh\/ZT+90is+hgK3pymuuxDjgJN+obKCZjEe+TtXsDuqHxqeyJLPdYoCttedZyPYGpO4J\/dEdA6I7gH90RdC5ct+W7UifmlmUqbV4VjKLvrtqVFseDuudGnbb0IVw2pwPH0Tk+Hi4Mi6xMef4NJd2MHszcqcYbK4IFBXh6MHdHWzOHZiWKH2WI\/+qpRdGdt7hnTvUg45xILsoy4MoMPZLdqR7U\/KcSyr0q4ey85WbV73shauKWdWBMEzhLx353X1kHrpv1ci\/6VQFzzk\/4TJHf3uGUoxsZFFNnjq2idAKj4I+nt2UaZCnQyHt8k9E+pN3JqK8Xcp7JNkm0FoLfXD44835k8RVfzNWNzHsWlxG8BaFhob\/lT7LQaupkxam9A6iv0JahnFGLHZF+glyZVcg5cmbruG8TbFDTHjJ8UwYC57nOv4kkA9M3yjw\/Dfdn3D07e899Gb16e11ULygd+uB42zILCW4\/mv6X2w8Etx8jCG6\/BTEvtT2vdlF6uAPWN72+Yzu\/lzmvwH\/0ANhB6AFGTGasX66nwFRg9iaZ9F78c77tYPhAHYoQuV3yc7ldLB6j82plff0EErJFJn7VaCsBO\/P+d7nTRRBS+f1v1M4vKHbdlKcjOA8M+P7Uq7R3Y2mC2D1uWhMqh5a6G+ytgbLt1Hda1S2gSK19dcKoF1M+tBpOhqZB0RLhMxIJlUzuPfzDvYebej\/lGj2o8O7XfCujw23MOTbEqVUrv1nfASqJ4z9UTUjwduONT2NKXWD\/UaG7LzkH3wQ+HnV7+z99kad9cjUDBJXIa1MT0qCEJ+1yx9UONBC0jJ18Hwy\/HGs+ZrTEgDB\/5rbs0VacifkxI5f\/Ecb2j+RZbczFZf0\/Vh9U7YTIrY\/MbLpm61FDjcZE+yJsXH7TaUMyDWxd5H5cn61HZYe1a7e9\/waPPzrzSWsVYHa2lar76TJcHeOw\/Z5XKfwR09D4bZiBK1XW8F\/ky8Ek34NF91dVM7lzzDw13FzVL\/2kYAgeEFxTpl6FZCm7uaVpCO6WtTR43a5m8TQIXiUw+agErxI\/1ijLWDgOgFyZ174GixJoedGuTHFJwJxo9W2RGwbA5rnInxyBanB9XCIoKByEizin5U7xDACnYP2tQ1lVMGXT\/SoyJg0Pr7W6f8m4FWzvWx8+st0DLRMktmne7sX+XdWvRI41gaX4tLG+\/WcQOyOtw+BhoKPbWp7UBySoSTXRa4Y4KOJzMDk42ot6sjNJ9kuoqD0wkyEgnoWno0kSHQpdUOw71Lg9rAe81lmYPaWTWD6psYuXhPhOdaP2SlGpIvgG7o801i4sT8D1c3s3+GfvBoyMkS0ct\/wx9XpzpyRPHTZe2phzb2kfdNMiOpc+i8SMhGwcnqyfPe81ljmN9sN3qqbrjvVNs\/21t1ZkYSYI9e7TE8hs+5dTysqnI\/PJV\/UrVMLquvzvjR87WXu6IcWlXEHvy+Fjd0DZqt8UyNu1oILnQQ8+\/i83FQOJeZffSq6sBj86TFOj7382a2XxAK+OTx6lfKLBTw5nWe4PDRi+TI\/LqJGGXR9dpBN\/V8PeSI9fp3TqcPLvKX2NdRGou1U578miKnCVzWBMZTegIX3+59DCVPwYEFCLC8rB9fOVfXbXqtHZKTIw7Fs65kRY2y290Y2bCD0zcw6w\/nC5iuFiKqjXvryQuo6MyvUpL19w0bB2Tl8E\/+iLkDOjNHkmuh3IKqWqd1pnv6+x6OItd+lonmCide5jIxbf\/bHdVDsOmH2K7Ttdqy3XW9DwpNCJLe\/SWHyq+tu8Yesam3CDx723b0hdYO0aYvrnpi9ExFqfndRsw8s8Q\/x8YXSoPRJ+eo9mIAzM6dCA0KEx9Y1gf9Iq0C26B3kFVc5HPyqCx3IyGhu9KRAS+OR80VADpFh2+51urwHNg0kVL43yUXhOJ4n\/6CSBPqerhH90leBz67ycFT0U\/M\/sGTHnHgRiXw\/VXL9PNCq+gqxCPht7136YPlVRn3K1BdIbBcSeJfqDQrrs\/Z9b26HAqVhp3YZePPdiJuMofwfGSXIIX74y+7weHN1m\/LAaeY78uSIaNgiSo1a\/dyxpYvlPqcVq9nrD\/XDpsWX4Dus6VB+9Z33aIgGK6+d\/lbJoBtnbOlPagu34Y1H0L6nZOpDwp0DnnD+F9XwJfwoQ\/hQgfl\/40y\/joqBHLWSYeHmUL+uBdTvr3BartKPG\/qlAObsYaLxVoP1hYwuYbdZRFL3VhxoVIsszIlJgexUPXWY+mZWDFnRgxvkAOQMCBoQZ3oKNUKn7SV1Srx8HOLVuPvBuByY3hqm7HvOuiv+yZxiZuiZmn0JybjQ68nWI9TnBvYeDc5wZdCf2X4SuD16FDelzBTfDW6+UpeqzvzNCjwTlBkoB2z1JsHmv0Y3RZ90s\/Z53t6+Y7dYmMJbx1eqZR4ec7MGNaq5UIAf+NAxe1QJsdeqxbyrosN48cfn+6Q7mv4P\/\/DtM\/zIQ\/mUg\/MvAdbVJM3W2P2LyQJwJjmu2r5QWpWMAjD\/tsejxyIMXD7YtcmLksfbX5nP7axZfUXjNV\/ZjOjSMSfZZs3R7FRK8WThSvWDMqWX2eaSlLkWjHojjDtt0KiEFgoIktHr2kUDy72howLs+GF1ivkHcLwXMtKRTDz6rB\/\/nxemrgnuh86RnwVRCLIuvWErk+zD5ii8JXRkzD4jY1zB9ImD6X100HhUJ6wqwyYW7ZtU3GHWNMG2kfSNwZR\/MX7xPr+ZRLnjMnedMPyA4naWfG87NATWtyn3q\/K1QLbxBZLFKH\/itOHw16nAH3rw0pnV9ew32cQ9ERz7wweRsV3xbUcjiOzF10aQpqqdL0TeWHpj5HooeDFo9ypYEC63C3ilo1QCDevhI\/Hcylg8peTM+1IG8zyq7lAul+GX9900xNytgbKa7yYu\/GprCbTO9a7\/ib1UGW3Z2CVjSjVwW+9ZB0nMN5Yq+fLR8z06trS6Er3F3nQbDKiGbXzepKb8UVcpHWl+eLmFyX4HgvjL3GkBwX5l+f7gzd85Dvl3\/w7JLFPiz9OFB9sxW3KEm7\/VjIx2InEH4J2cQvPTSnOnaDTDfw40UO1gDtziVDN28euHOHF8OCb4cy9dzb39C5gNXGuY99bMy0CqB97tream+s\/f3ApfBK0soIK6jY\/UwoQZcGkjpck1JUC7s6se2sgT5Bc1rnX7QcZdQu\/B7g0qQOf5M8dOxAlyw7W91kWAPPvdXznj8vRgIvhMSfCck9JzQLGOy+5J7InBbkJ6azm+H5nchqxWWPoTRG2E\/\/oS7Qx33sSC37jYIS1+R5lzgj\/O+13zYnBWAvWFbC\/k3tcHwwPGieYc84VnlyfhTTyLAuroqfiJ79n2fp+jc\/vcFFJ93kVO+k4oT9qQD5Y\/bEBK27fTGXhZPT3yOpwf\/8vQuzfH0WPoKE675evNyCjFkLkeVNU9r3nu5JmRlG\/bVJiU8\/N3B5Gmg+aTOwrfHOlBM9FRHSyOFqdvEv29jNLefJ6PCmH5A6FAbeD6XeWjRS8c7jYpfnsjWwOSQw0ZlBg2SCd0UkR+N\/+RHA9PfJD\/nbwKmv6l9\/cDXd2cbcH5G\/S6zsiYIhS\/GapZUfFRryv7gcR3qMQ5Mm0TUQZOmjqOyOxWnukQl+Wca8WrjtbKlWAtrBShCpCIa7ml2GefeP8ScH0LJ3N4EvjtO3HItykNiHgK3u36rdA+Tcaet9XDX6W5k5vYy87\/einDVK5r0wfb+x7GbpamsXGnlTyL78oPJLM4JweFEIr8GiPwaZOZTqJ0a3YqHyOBTvK6ub1E7ttR8e73zcRfEMR6Pvf3eBOqm6ozDOm34bvn2A9JidGi8Wx6pmdYCyi38pdcUyahn\/ChLc7Qb1Bt1HZ7KkEBZLlt+lVYLHvn0ZtvzLXTYcfzJ55sZ3eh4Ml\/0j2szkubx7r7N1gRC9s9t4gq6sWJYmLxCpAVVXXcFqNSSYdGJv9uPxSSh6JPx4CXSXXDhutq3ss+JuNdXb+lDnwx8qrxU0HYfDZq\/xUZF2uXi8V+8gl1eiFvP6y4bvtgFIX0zt\/KW5+GNavr8tpZe1OdSIhkm5eOkQnjabZoXOL3VZjMLaQcmD3M5MWdgcG3+9oW3CHp0ZwaDlXthKP+57T7uHAzLfOvILlsBTb+iJ\/\/uZcA15zF10UnE5U+OH2skDyKT8xksGOi4hVyIjnP+I5w35z9i5vYi\/YVx1uhCEu6xXJ6\/qa2RNU9zlHLlOx7biE+dYvZ3VdbjmEHwWd7lvXi9UM\/Aga0DrcZN2sWO9TD37JD77FG6ZiAFv9779u3LdBcQHE4Y36CIyxvIyOB0XtT5ng685cHb2AXbIb7z\/jvri\/7w8iYf3N\/aAB7hPdmX3zbBtjUrf3mU10OMiV\/3IUofKz\/3n70nc18G2wsuv7rGGGb5X17M8QrAOqqy3Nk8e\/ac415RKNDO8j0VmloMvQmIQPk9lXvjDWb7x+sVCg+yelFyTieAhE4AhQmdJP2\/OkxmXYejXp77ag71sfT8y+b4LZjy5+jw184auLzQerruERknKHsHBA8mAaHbxH90myAuqFYffqYbTC\/7VetdagL\/vTdd\/o+uM4+G8n\/\/f6m0SYWKEiVRaJMkqUuSREklISRUFCqVNmlHUiElQrJXsmUnl31fxti3MZt9zVJa\/XzP3Pd8zts5v3\/nvM95N+O+X69reT4fT31eCsg3uk5TymQi38+aQ2m6bDi73Nlyu08N2BTiysJCFp67FpL5dIIJoh+ny+f110KApSK9+2Y7ysR8ts+Jbyf3HfDn1MOTYpvfoGZshA+1sBt\/3W+rCA+g4rt++lWLPn\/oqLPwTlPrQqrQvEOnPKhY1NFfUfIIcejYkR9Gn+vQqEeq78TLWKxb8W7x6hE2zlkaUyTr0ghnbX+INjUU4ailgIpOcjtWje901j7QABnp1dJ+lyl4ZJZPzOsjnTj0qni+hnkjMF07KZslSrj51JHEuUrmU0\/JoyH3s2iie6b0\/eT7eCBj07sA1SoMNaWcrk2h4yffHXufZeZCamXBQvGv9SAXdHy20V82SC4z3xN1sQ\/rCP0eqY9iHd2028e9DyM5\/iMc4nBZYazrtsn0\/i58fiqzSDi6DYcEi3Z77UtDqQ2Jg0P2nTgwf+YabS86nqY60Lv9PuEdgmf+lcMzR5JnvuCH1wMXl0ZkmXsxvfVb4WKmazdvZClGPucLczzXiLvd9jAj0lugIGjakoQDWfjNePejQ\/bN2GPxMURnsgPm\/UlZvT4K8dWDjCfXpMrReOC+ZA1fMRaYtGceEGfjt4o3SSO8TPy1sd54rlw8dE2fu3o9XwakMdTFGs\/WAvvqWocuKwYqP1vzd\/u\/IrIPxSl9KBB6UZyiF4Uoe0cP9WnFeMJqeE3HXwYo3jAeqG3pgL7EQeEgxzwccvnYnr2ZBUXPi4RKd3bAlBwKmEHkUBA56fCKk5MOtzg56bDMeajNSoQFtPuaTz4s6ATT9FTJ4Ctnse676XK5dy1YPjKmbnG9C0l9MuHvRsLfje0E\/8RP0Din0rMJbW6eNkj4XoVvXM98rdTzx6atvQvHk5qQPzEgtI9ajnIJM05SVyVh6\/cFPrNvpwHho0fCd4nzOToumKLjQnGFz6XzdAvwV+rC2Z1nqnGiJ0xb\/kQLnDXzTrsqwyT1jVxuvwHfh9mRF1hAPQG3FTNp3D6dV0aH\/5IQG1u8DrTf0ipBXkWj08kT+ejtHBUoN7cB9WoH3IUM61CL7+GyDQNMdF1EH1wY38nNByfPt5z\/8pNJ\/xFm\/Zd7zOWTx1rz92e9DED7HbJm5et7wEVxYFHCvFZMveGYz69NQXq2hb+ASgsuNZ3xJWMXHUcvrVaW2l6BMkfn2mmrtOKcBzvdrxyk43OxEyMyGzPwxvPuxblKnSCmur4i5nIBslLtVdeaZeEflsrl0MnnY5qduojTkxIk5zM+RD1P8g2IeQJMmSfAsOdudmZQB6ae01FcnlKNWoH7zkxE0SHQNiisqWDy\/lXb0lL4rA4XP4hflynRBmdf3kxY\/K4DLTUVGyt58yHsQsb0yvh4WHJxW4K9LAX5n+1sPjueisnSmi394slwWONEgJ1RPfKpKkrJ7GFh7DkpKbHOVnBNtVl0bVoG7hukeqcfYGFB8z2+xHE2rOLMM8l6huvTrFb9bDUnPxcNP0ccm2ZExzQeRft3vyf7n6cdxZ8e1+I+HucGnthqcJq2y9hIi4rDprqPvdMn++wcvkfD7nT4\/rDwyCYvJjzVHhxTTeuBOYeln02\/WgtFH3Lq9EWKMChNes9FQ4TNT\/bOmzmrE4+03p7xra0elqXCTlZmLaoVJDb8DkyB\/RYpizPK2+H1jcvGqbFVuGxjBdv87mcwe3tLZY1XB6nDxyk6fBRSkTmfuiAdKzZFnVMyZHN1y3L+Qa\/Kr0TjI4\/zYWbhxehiBPMTb1Fgc\/Z+7dyRmxiaWnyuW70K9cVZ0m1RteCsk30o5HoG6iR8fcioqET3+YJXeOIqJ88trYvfUj+jm\/ZI3XrDGvTW2qD\/aV4t5OfKu\/RfS4alLnPVD05+L+Wzaz+w9Zkoz+EtwwkObxkpHN4yyqic2JWkw0R3Q6nDIil1aL7ggt64IR26aj2Md06eM48iG\/bON2Byn6s4k7g3CWp9EL2p66poejBIXJBu0cqiYgUz0Eutrg9GD+UeUJ8eDLMevmNdXFsxWa\/WPJVS6wUyx5mYb4PLs6Xqb4J6yf0pkPq9KP7j69RGukHYRFfu8sMa0NaXuf\/lbQ3M+XU0QJOvG+RrGEJb0utg81xtP5GSOuC7945Xd8Hk8\/Fl8TQz1WaUTKXpPDfJA9Hzb1f0ebLhgyBzj5l6I+xMv\/5je3QjbKL9ucD7gIqvp4VOuGSzcJoZbbzsExMVU0cf7F6VgJGse+qxr9k47VNyj0ILAydU12FvAwUFPoqJdfZ1I5HPjgGgMrTwfCzXr0TmZxF5NDAljwaynvELhcnRscfxwK+ZdnlgCS8Yygu6oCeGqfCCXYEC067LfDD8DHP+qGc0NpSA2qwGodVuFZh3\/rnSLosAjDIRPuIyiwJ9Trtszph0kz4vkCf216R\/vMst1DN8ww0k\/eNELjYSudhcTlTaGku9P8eb8K+zUjilKAu3Ln24082ajnnzjol5TdYfBVER8me3JuJyg2RTpystaFiXNmt0ey0u11Gv+ZQag3FX8vqkKAzU+d0cZmbfgO9mLzj+mx6CaiJ6li5720jeI+z+L+8RZlZ0H1jnSUPXtOXs26wmkFwTk3PlaSKmTSSfP+Hcgi30OIna3W3w4UJbSbx9Eg7vye6wnc3AvynPHf650iH\/xrFNsca++H7ZlbS1K5vw8T2pfeIbafjaj34tbGUumasL0pxcXdQn6mQiP5c7lyb0q2DckWOs84EJJ\/Y1KqqU0chcKuD9Oqv4bxQLiBxkUk\/F5Vfc4PArkORXqF94WaLYWIB05aVjdyRZ6D47XN569mPMdPtsLetaA5GW2jzR30Lxd\/mmsAPsBlDVO9d7\/3YlBA0EUmdavITMyy6WjlerQc92NOCRbi0kvO45\/XO6Fyw9Xmn+4XUNHDY\/biT0iorB7NhtmqdqMJOh7KQwTkUtxWeaVPU67Dt0KEHnex3W3kvrujBZf+jP+FC67woF8zJn7jq9thHlT4Z61Dwow4RpX5XuRFWh9NOYk3onGUDqfsMbK42XLi9Hsn8k9vgQXg4x49WFYEfkGBK6XHh+9oPgYHQxCLyV7zxdXcLlBTmGjpyc\/y8X2JqVhb22JbBy5xJZgY19YPIy7+rTxjJ0C+h57b23CHtUKlsMJ+t\/Od8jeU1tmfDt\/qo1PBIlXJ556jmjoyKXA1A3duag03c6imqvuU17kAObLTYkp8hbQ8966h\/vx0y88XRi7h7hIgjU0Bmt0\/4I7JH0I6fXVsHWa6dCPObWwZrbu79LsbrBUEXeljE9H9ubbhoxVHOR0MngFJ0Mnt047Z7ak0j8kbdE7WIgCwZ4XwgElDGB4nLr9qlLjXCB4JDbcfpx4L893\/D3rjogzweSz+Ce3ly560ENfHWtyUkc6USXt8YXjLEJvl5lPpmhxoSotpe3HXILIJXnm8AmWgEkHP+17cxnBuxPLzvz70w+VKUfY7d7V0GKDH6xHqPD\/Ffje1t\/0xEjjJyNzBmgJ2pkfmMFg5xjkPU8tBha7nOdaIXESOZR7Wg6bhWyyKhWocHSXX7BYdo0COWx35zgx8J11vfedTa0gWHtn2WrJn+X8UzJyzq1bHKfAn84+aRA5JNy5y0d\/+Wxc7nNnRLKdmIiFYA\/RuS\/na7Aq\/4ZrOZ+N1Sq91jw8GIR8NK2L9WuoeDsz9U7yrxDYSP8rs\/urAP6tK2Nh6LYoK9a452gU43Un2v1AyYQL5mMv563tAiYW\/QWzleNhh3HizZepGbgGw0N9szZ2ZC1+1jsaXYm3IzNGp4tkAhGlnLJ+xUpKETkbh9Z6eG\/+2M0yK2OHQ6YrLubBqUW2QX24uoxi4GDC9hkHgGSejNvPytee2s2EhwSJPPp7HVNdgkcYU7exwZXpW\/Vo6xnBnPeOAslvktYXM+nA+XAyDS3cz1I6tmIz7GS8zls43wOJT8C5CsOM\/Hrevn73327IYIzH4Bf\/Qveybv1gatUQv7VyfdpjWNz2+vjHjh5WGmtvtQP0juuKUV6ZUPF8vZhi6jn3D0Rwb3h6kWj38suWiDYjgT3Bsl9peABgwsrC9go6TLrWsWXZpSL+KxlUkfDQHP5ck\/vNljkH37EQaEd+1JsedKcMsDEpoy61L0AdxA8GXIOVt19p9tLohCd2sXe\/FFIxKR1+qNb7fvgdum3tYoaEaAU8\/2j8mE6KsVH1fto5sE6\/bgfAWpJ8K5M5H3pJzr+S0pWXq2XBlmzk+ph11Ncf37xg7LJ33Vw67k8KZl4aN9YsdxmRx5ukT8gaSPaCXlm5vLHt3iAe1pBx6KhbJQRFvlr2d0Jj8\/pj6SXfULJGUrwZ7Iv7wi4UPxiQxPe2I4Rc9azIOnIDJfbumy83vCT7+5PFvc9tUrwcF6qwMQra12Kd7Yz0cju1vGspgbIEzGftUq3Hp4JK1t7eNfAurj7dXFOVfhlNmOu8vZqsFpHVZB8ToWaix8G6\/dQcNr3fw21Hn14aecvH0p0KfZt6Klys0oDYi+MxF6Yuyci6nOcsj9FYs4JxJyT3McB5V\/o4JUVWXCdyIclda1qLal8Qj3Z8On2FXOXdxQQnShKWfK1F5oMNMunx5dCjdYlj40jBZizNftAvn8n8vUbO31aUQ1B1NsxG\/oiQctdq1TySBUUKMiH60rloQTBmfQi\/A4Mw3vis6bl4iOnaSr5m\/q5unGtT0tC7m2iY8rpf+r\/vjajenzI28MDVRi\/Y+Nqlyt0fLUxQElIio660+wozq5UFD5eKqju6wx3eHdoNs3Kw3kV7A2v7LtxUcPpzrANFFBWsSnbcbUXNCxvaDvqZeHrjQEGy5IbufNbIh+ZvBdwyr0Am2denHvegw35p4MYIWw2HuToOfFSCiunnDcT9WNpC9pMq7C3ZcP0oMQvXJ4MwXWE1QRPRmHaL+OEkx0g73L9U+hkfXxp2v26i27ZePtXf4uDXTvYHw054GPExvCAt\/t2BGZjq\/Rwwor3HVCmM29u4UYWRp745P3NJI30KeAUjj1oFm5UkqNVY77j2+iFfK1Y3ZvtU9CVhfI7ah\/c1a9Fh4sXmk8INKF\/kO1MVfdCDBg\/vmO5ai3wsenvaXfoaPdr2fsVjh0QzslBBhYnB5nUmaBRT+1ITx0TR+bO8EsVaMDFalIGHd0UFO7c6BJ4m4Frx79+Sl\/djDqeJ6b9lC\/DijtxjCjDFmRKZm45ZdeA4z9eBU\/TKeXyoGw5PCiu7vSB8kILjS99aOrltb3k5hcI73SrOnSmEk1utoyf3lsP9NU6D+82N6Fi3pUz26Z3kboXLveA8AkisU+EKftE1Lhczpxzb5DLQyDvX\/U+hx7b\/f2gyS\/7SGd5AnwJ3wca4nlT82uAzK\/R6HV0+ajDBrLPIn3lT9tyzvx+wIKcI6UuK8tZQM4xZKZrxKc2MOEs0a+Rc4+sQ7+Gr7Y2gU9ph87H9yVI36my+9SiMvzS4l7Bd6oGlrxacGmDfTG+fhP4MPNyMTrbdVzZ2DlA7umgkpjDE7ogch9H5lZjjWrEqo6d\/aBSEzkhW5AFiubXEpwMs1Ao9bev2eTvZpMkcVvSrATtOHObyb+PyYCaRjcqzTp0xEe7iXuOrVpg++re7i7u5x2hd96kSNBB9a3X2oGMdu78XO+XT163IB1sP6xdsnlrL9CevTCd2FiD8ct7Vml8y8cE\/SPdJTtKwC770UhO0+S5TeR5jRP8tHXEPULqyuxOytCfv62EvR7iK3fOouFzuavUd\/xdINMc1yF+sRwcY2t8Q5\/RcRfvj1X\/9ndC02cb1b+bmlBfkiK75WgXSo7Bgt9XGpHIg8ApeRDQXS6+O6e\/h+sTIefbBw2trh18wsaaLdX+CpWNOLs13dhlPwMWpZo7Vk2+n89a23bFzarHlhenR9ytmTCFl8Wtx4h7AYh7AYjfE\/XKBQeXnmBBTYJESsrBdu48eU6xp9paMSbQUmid15VYIHm69cDvTc3oWHVFMfJEIy7LmR23YnkG5PEd2+Dt1QyfXDY\/PXSyF+t6xAL1vNuQzAk1kt1w4phFD\/IqKL6wXc3AeILrOCX3k+R0cXNCZxN+ZzIndEoeKJC5mSrnt9uYPJz83WJ4G54YNoLyS72H0uHJ8Lry0pqPaRQouGV7vmayztXa5HjH7lA5d+5Xxpn7cZ\/\/3hPPZkg+a0OJTVZWsgpdkEb0R4WVAykSX6vBL\/hLx89TA7D5WLJIrXIg2lvQ6G2iWeD+vOP3v2WxeMP2U1+7YjcELRMOfs2XB4P4yZ0q1st9PkdbDiqfeJYNEsuFPr637kKdp1Re124aSP7UK+LVaocM5dhMl3QGJhWrS5xVrsFVnme\/nRQwxE+Reu311A40KoqOCdtWCH9Lz\/tE22ai1o87yfvSmBhw6k7pkjUsdCt91vxPqgAv1kf9XB\/FwMfBhiIHN7PRLco09g+1AO61vthemaoONzI3+uudqobK\/9bz8P+p57m8NSfB6MRQ22r4IPoz3VSjC+zuno429GmGHGPD7JmT\/YafmMCcxXtL0S7DxrHxMRuantXd4jHIAxn\/3rdWpsUomm4joNzQDoEmiR7\/x2cQuD0+N+h3NSTYr3i559EL9J7TLJLK+gzOavOppitrQSx6kYPxK0+8pV9uMb2hHTOI\/c4I4RNMUJ9534PRweUjEec21K1cKbew4X\/6djLvQOXH4OG\/EX24JFa5+Ni2V3Bb9Kj13Mhk5Cvl\/+pwPRurcj6s9fsSDS9X0AZYPMl4Li78sYdDCWaJb2Afrj2IkuuExCyzYnCR+LnxuNEmqK5aIFjIyoOk2E1yP1rqcfBsImUglILLvwUYv9rSgENWN\/cvEelCmu5bhaaePozbYNm0cW8u976edz3t2I67tXCpYUVX7uwsdH7zNMh+cQn4e8w8GCRfB1G2Rzv7RaMxPHZk\/cGsEjjJeY9gynuEx75aLL3p2o4FL9d9lXSNhXsWOdGlEfcwSW3J2q1WCAlpidYP+MswVreMOWeybuuXHsHwxnoUeTlMqxRqBT2PrUHfZJgYaacoIRtfBGf86723STcB24ehLtlMh0uMQwJDCztQhpZ\/IHEiC30WHWpuFWNN9Uty59ItsZEzrgl04hNbHmPH+Fisefn4yexxBjpu3ZIwd6gTzcuFZj67l4Lyvru1RnPouDskd\/+dJww4\/fOYgNXedvj9XTSjevUHdN1wRPyPbhtQPP0cKqvb4ZHmiuqFyj746LqmzXZggIxNiKSiSBfsOVnl65sWgSJzZ2kYylZitLVa5F+rRhj4KbhgWxQdgjqOOJ3tawGCu8I9T8rooaPHmI1A1nvp+toFWR7BYPPWoCVpRz3YPm1d+eh6L6SYF1bZ7AiHqxWvd3eM93K5MSRn7PLRHkqpezc4N5\/Tk35EhY5dD9OODNZPzbElcwBxCjcASW5AXd22g2snnxfwX21Z0N+MidGCoqbn6hCborqePikH94j7x4w\/NCG\/3cvUrJAOyL972fbioUJQbzEQGxWZ\/Hu2vnku\/KATRL\/whw4KUsBflEaJuNyIVmHve\/l3VYEXJ\/8diPx3Lud2Cu8OHxC8O7v+cP+HN9mw9NGxfxOrSrFHSCYm0oYNgnMc\/m3xbYe9YrPmD8+rQFqKod\/EGBOW9nrs7+KtRocj5vK67+qhT7VOxeN4NT70On\/byjoWl5gciHgzeS\/Zrf0Q\/GqkEI0jTO4EnUB4E9Y31DOjFowzkto77ZswbKfp+9z0FlDRWyUzotAO0e43\/NMtaWhz6rRuvE49sNM2yfhtrcI380N5a\/+mYscGxcdJz1lA7HGA9F2aPqhoM1NlAXmek\/qT3tXnrGIz2UDukYl9HCI1\/HbtZQZ49bkL1RV0gL13gdcL1bKpOSYkRwKIXHickgsPUzhaSHK03K30nRNPVmGeqc0RKX0W0uW\/R24IYANl7EKe\/atqnOirvUBZyMQHmpbKrZPfe55CweoANeT2oaTuQmi\/b7uEcxYO0A4duCzkiU5qY0OyuX1QKm91K8+FgiXLDg0uEB3gck78\/tmurT1bDQL37Cs2PGfCxS6Ws14bHZTPZ7iGrK6Ao2VPRnckseFk7S7VrLAyqDY0SF28tww2VJ5QevaCDTaLomRers2DT3+UrO8fq8ccnnWzuo9NPi\/Ec2J+f+jys9hkLLnv\/FCC3sD1hW1aJa+1uK8dVf68GDrflYr\/BKJOzLhTPTXfCkh\/SqH659LOwUJ0dH40\/OBpJEjz5iXMZPVh0ptM1YCxWpCL39rzS+gjCr1pFn2qUooCJ8w7jh8eQILTTuZfo1DGue5lA30oeloiQ3gdBZeFf7IeDbAH0VOnA9RG6ahTFfzgqjcVvQ+GrddPY0KwOUukXTofRR0jDHDbM\/Bd0tLtlJOHxfZLnN+\/yMClXZcvLVueBRWHzVctfpGAoYY8vJUHv+DBl2LLHK+FQsQRmve6nEz8pdsmDuPZqEFbkypyPwGSNgU+eOWai5EcfysS\/lbuHorQV+MUfTWskMs88k+6HueU0C7yHaJD2YuFHjutczHUbXeA8okmjG+V4xu6wYDa9z8LZteVo8fKHuE1S6ko9fvvfaUdddBZ9zBnkFkFTU8eTFs2g4nKrckXKw9VQ5lFwepO7zKUaZMTSVvTjgSHGQifGqgnFFhTnQeQ8PeBPoeLQupzcIo+B6M5ObZI5NhyuWpUJalObYMkHD9qKjpU0cXlsAkMjOrfWRyLQwfqone6d+Knsu73f3MZ+C6lw9QqsAFpdPnXXQZMrj9uSl+MZF\/cUfePnsVqQj3lcgHNGXT8cXrHKhXLdiz8b+4bEv5QLIGOKxnmXZi6ZP1bYQcaBu5V9VF58RqVO\/IdLhb0kBwDJPIm4JQ\/b8n7WT3osaV+mZxMK8rwtdbxrPWGtfcT112zCoOWLRE02skW9Ljn2KK9rhEcr2645Wv2HhdLy1GFgxvwee85MXjdAGY3zMsM9Jmgteb4UMyRGAhe1PMzSbwIEhvvfhoIYcAgJ4eFy3H93Vk\/Y8SJDv\/uv\/l8ll7I5cHqr9OM2zZSiYlgpa2zvg9XaS9hO6zPm+qv5PKN38cs7hRMoqOgZKqmnkE+8Bp\/sZBLRSjZPzrwq4oBXZmaRxOLa3DUdCxLayYDxEMm3se35cM0aZomv+8NcI0IFUu+NXnftukNvuJLBfpafjc\/cQ\/wKVqkmyfUDqbbfzRuHy6EYeqauCDbIDjbtjv4rmEnmesNU3K9MeHisbcvbXohojteXVghB9gEL33FVsN8wX10IOt5QoeG3k2UTfHNbcAbb+UTv6sJzn+v+vM8bvJ53bNi8OnhVjh9eXk97XIrOCgrdre8aUfKdNfs5UktIPbgm4SjUxOcLDufuDGiAxU4\/GQ04PCTkeBRYHal6mz306Vo3yEXOKRax81njL7k71U+kQnCreIsh+RqCPacpR+6nIHy7XdEkjSZ+F763s3pJ0OhlCU6Q6OpErYZ9FU0\/+lEJ8Wu4mVv63H055nlCncYOKZ9\/LN7SxeWEechyYd3\/V6Y3HmyA+\/U3GfJ3q1Dp5vmQ\/Ndacjm6ENgij4ECT4GEHwM\/M6pe1HVp3DdJnyD80\/d9RwcZMAShQey4jUNeFjz39CuX7FY6TI2rcGIBT1v93\/mHWhCQh8FU\/RRyFefPFdhNhNkCd0OkfeEiSoZmXMkKTihwKuRY9OHBsrh8wsoqZgjWfzzzyUKOh1t2HE0YgBvEHlhi\/N2XLt9uBzL+byqT2b1If33RZl\/Bln4cbD5ce+7EmSpN7zf9T0UA\/WOHbp3PRPET3vx+nyswnxfNbv47yHIL7dlfmhaAvC9smIEx7NxvONdsM6feFwTs2zwcxgLzVb2x+36y0L9Y1ImPwy\/YHzqIarsIToOuH3zXKzTCEkFPLGjbxrhiP5x\/9557cj3UVk6N6gRHkpmC3Qn1cKH+U\/eCnxkYcWVjaUn3FlIcLDxAOEb+ja4fJWlbxUI94uwtptVIm\/fzhyHpBaMCkx2WiRPhcjRUtGTT8owWC9K\/j1\/A5b9N8+Ry+X4SI967CrcCdT1Bd60rU1cjsfB9edzleQLgc+43OX4ggpYwEPxPvUiHC8VnFpeNxAPiut+NjgblcGn8p3Lmm5\/xlW9WY8UxfLAHR0kRjUr4OxlwWlR0p3owjrvylBKBLp645P83HIoO+jSHLWnC1dV9y9+Pl6DlJc5b4aedXDzhf0bG48+XdeAi1ZV1nu6dACx74YcLbtBh4werOHoRiCW6JsWWRksKXsfChVbHJZ3U0vwk\/UbPRmROlx3IvJxvv1XyJ47IvnNtwj1WU1qziJUrJ09skaWmg+0LqWKF4e7wGnbGJ+GdiWq1hs2GOpehO+ntF8ct22BgZXNj9WnN5OcLiR1LDM45xUcC3Sa+SSpG18TXJQhgts2tDOpIUCxC9sutG39YUHDJdKVYeujKuB4tm3FqapOPKa15ymrrRVvZJnPXk2lkrwgmMILQrvgvCep+jSw2n48tHlPB1fflTiPGbPtZDn4yo3++Hy5Ci9ub7xz178dVumvD\/spWg23rqcc7HtAwSadjIs+iR0w49JXz0\/PK2CMVzhaZPL7e5088uk2vRM+xh6aXV+eAte3b1OVFO0i62cudyKV2LOQ3Ikj83hUFl7rAr621L2z5+VxfQG37rkczZ78nNwnElxKkGC8jlPxagcahX5+wDcPAsWrlAR9WZB36\/AqVlAHaPJf2ptxpBD6ln9dxZh8n\/1mlszdMvm52tEf7067ZgFtsdfFky+YIPdf3SzJo8aokwnqGvc68Sdn\/0XyzfCY9KFhOVobEDlQoErOZ\/6bG8XVRQyGGgqs\/1qN5uryh9KfF2LdsmyDE\/MLYWvfPCf+W3Suv4\/IQSbzhvAhwd0yI3wTekzjq\/88B1CT4G7lcPZTkBT3ZkVhDwX5t1eUxG7Kwuv3dj3l8c1Buq7J6l+ixTiwoSHjl2EiUj8lObUfLEabS0ZVF2hV2LPiweDPHSm4gup8ca5TCZ58anjmVlsRpJXKXKu7F4fP\/gT+3L+3BFxFtlAmcingd4r9dXHIBxSx0HXzsS2BVfftDde1W6Pi7ImRy7KpcPbvGQnali6QSeyXG6j8gkOPHA9tjMqGq8UnXd4d7II3m0SKzM9NPu\/JHgrr5\/ZM9qGfZak3vSDs5sG76jaFyJYMqHobVQ\/LIwLeKwszIc3cYtia6oVqOjNEvdSqwUx307S7Zyf7qaLF8QvDXgFb3bn8IrsEZnpuaxyWZoGm0sIJxTk1MDZXYWzpyWqw+Woh6hPcCmMV0Wtuj1SAoJBG4Q2bCoh8Zh09rkyHow0mHirbqSATUS8pFkLBVysXuk9f3A2W77W6V\/fSwW6JWFsMDwNr1lu7+lzzBalMRYpWJhNUxLsjskKZmCHp6XedJwBG3fbMb7paDKJWyRlORztRoP7avORdFfjvb115zIIOpKdOo9XMopP6EDAybbutNbuD1JWh2HF\/2bpRGuhPy1CXKijFb1ZHsqiONWBZqxiXdp2JnY8z42t58jHI9\/K6n1WNKLxwIH5Z5jucL\/dxfo1lOGj9LZl5dUU\/hig\/tur4mA+ELwm3\/9eXhB4qikEWPj0410\/rnd7MJnQcNVG1+JuMH4+l\/2wS652sOzJjfnfVYcDAmYcbRTPR3UD\/8wrFXkybtW7+y9Y6lGqljdysicApc2ZoJ+Z4xDmPxDkPxDkPphJ6i9xG2rHPbEPn2ax6SOftXOLp1wbUIY0lGT4U+LJ7Fr\/\/MB3e6P84uSspHoWvXrQOCyyCw4HDqxYx6cCD81U\/aEUgNXWa5JXbFChMy5m4aNUKv3zLMsZef8Z2AR3XaPMe7GeoXfGeQ0HyHifOTyDOTyDOT3Rr+jU3VrYKzY6IyM6qzUeV80Fp0s10DDU\/+Zd2goKvO\/sKtGkFuLH\/zDMRGgP\/Jl7YelE0G4WNH4g6RDKxQ\/C7VrdUB+p22eSUvq+Fr\/OPP7hyk4KHPRx3Xgtjgfl+\/e0z+mogKNdSxGprCdaVvbY\/4NUJfAID4+vPliLJSyR03TDHq09MPu1\/+451RP5ycpnlmzrsBOVg7a5Nk\/f5wrRLWtP2ReCc0sdOK4514qUP1e6KQxVA6vYtY5NEbbd24N6FEvfUecu4eaCbpRWiRV88gO8ZK7brGCFa1tcXykzW9S\/d\/Pyv3+hEUuf\/gphL\/+rvaFpd2I7D5eIrix+y8MFlz6Qmr2xwW\/oucTC9DswIrhpR54Daneph\/1+NkNAywPtuBwv\/ygamFiTGgX6it\/TS8U5o+MLb5v7lOp7WUY\/siWzGoOuCpx2jqrGY4IqT9XxvytdZObdZXK4m4WsGNS2ZaK\/HDMjTdtKduNwB8qySyxIZFGiasWiINSMVq71bfR779iE5nyf5hPs55ySXFxr06lxEVdxlUNha1LsltQJeWR469mRVM0zhwQLJg20RSX2P80K5vsVkIg\/a6r98DzL3CoO6AyrsIwOA8vnN2YyqybpprpeHkVYf1itr+T9uQjB9+ONDcuNkHZT+L+ypQj2Zu41k7rYs5+8OBZx+DcmcbpJ\/6xFl0GvZUILRV4wOj7T3QorScgfXwkRY97uVspCHCfwsj3MyS1uB+f1Ir1TEF7hhzeb3s2ZAj8O9WTpSDZBlrjp0hHIblgoKbhd7QofF0SnsYJdmuBu5pO1rTxDWhSsk7588L41UnGoqp7UAMjoN1C9EgK6VkPrMLxkgLHVioeSFyfdeo+yCYlMp6m5Sv3ONag9fS0+Vqdt3Id8hQabvilL8mJmWlHWICjebVQpvh5TjsfyLc93294DVrvd19mV1+LtiuVhQST+6dqfo5pZ9hNuJHgqOMxDqDtt1vMusQeOy3A79yiL4pTBv2WykoXTjqqiTqz+hkdfXjgkXJpoJtanjMAMkLmjMWPqchutmmb7WLW5Bg1eK5btr+oGcbxP5zthgsHZ5QR0VCc4PycXFcQ7\/HAn+ORB9OtxblaC\/4nABWHK4uEDmz1J3WYYp32nDUI6vAQi\/Bszx6K2+Z8hC813Lls079xniF3wKu7mwA268DjGaZ50DSzuP6WreYQC5R3N8+knTsL6Qq58k84++\/Hfvxv3v919LTW\/c1gFvjgiXV6yvg80mVAGdOw3Ac+kKY2Z6O8ia9lm4BTVA15v34i7fa0Dy+g09E5UqbPtJ2X9CqRNI\/fOoSviYT7g3UKv3NHxxrYdILfe7s5e1AptzfkIf5\/wkdctA6P+B0P\/DV4LPhn8DFH58LYCTocHXzS5UQePw\/ArDyhJQyUp2Fu0rBKUr69\/PWVIKh3eNifBOp0CLVbutZHoHl49Nzj30hjesv2vDhK907WeqryphhUnuj+aqfIzd2bNw78os7DldISXlmI2rN59KeUNrQ\/tju1nedpGYrtXIXLI5Bxdeqrw1e2UbaszSPmy+OQHFdrX6LHJ4i1Z+WQvaJut8lU8jQmVsHxR6uylp\/s1XKPD2ylPazXbQ\/O9eGA8Qe2F7m\/f0d2mfgVJhoflPoRMPD8hkzH\/HALsitWrm6mzcaLnvrkxDOC7qg+P\/diZCw7JLxUGrm1BKJPaVxQgVdIR6d6y\/0oB50u78x8KKuP4+0ueu5hA5oKqdjXc2S1hQd1ai+bkfwX2P+mDOH4N6\/gkq7P5xs6Rusq6kCBXT5Y2y8CL1zezF23pA8s6tT28ZNfiS6ENzvitqjPH3wKJgn1kD86nc+07cJoR\/wy4WPCW4kQTnc6pvnfs8yGVPsEMXs2A8PMHj598GCG662mRcycQpnEYk\/LzYtOW5iqV5CZDvL5l\/t+njgOSv4XIISRnvDxnvwUtOCxsvXqpCT82cMIY4m5zjIck9GJbwcal8Ug3xUvecOgVa4MzGymO\/D3VhluFkabmhBGN5Yv\/+ag0HWkN3wZy7bBgkeGJKHJ4YN5dKfa+LsPa+TkgukF9vsGXyvTsoVyscwEThU7SjlnH3cWil\/tX8f224fP704lNGLehZkbz478VUlAncQ2d9q0G9+Y9dDQJa4HnBm+DVEpN91WKP++qn2Zg5\/NmiJ6IQhmL3d1FO5uDVglbpi4\/YoOE68e6y7ReYqa\/wXupUB3iH+dwdu9CBrkQOsjfnPuX65ggfMc7g2Tb3hFQHnCP6rDsczidKcPKmcQ8nb5q7Xx4yfagtJ\/AZQgXTaR+jGLCix\/rQpxsM1OTx3O0xEQRzDn9wa9Cmwc2k+n0yGf+nnzoWm76ahkcftSy45tUFStdfHyh3LoNnyhunR4x1APtzJNPjMZPkMIP7TVH5jcW5EHum3au2vxaeDVZYjS1lgN6C8uzvURSQMotdINtWC5c2a5ivOk4HZfUMyR+KxXBAzGOL0I8qCNisZujkw4B55gnSF8LLoFZn3jDv0yxcqXvXy9Z08vuEabpSdlVBOX\/MlkO2eSinKslLP9CG7kfO8zx6Wg6v1NcbXssrxfNhy96reLThpf\/6LpHk1Z\/h5DIjOQ8k\/SC9HH86RnH86Uj405GYE+KUOSGOVv+V2bwrDcWe3tnF2sOEbY1M1xl9ZfAjUdihMCcep\/tZb8nwoUHdy6wP1cll4BVZts6tsx5Ote\/\/96CpGBOy\/s2YFd+ItBljspJirRgv0DA2ay8bTg0uq3ZTpMPGJJlhPdkSrJGN2p0tVwZ\/D37+GL00GV93gP9MpXyUC2mx1K6gAltw5VoXvSikNYYKBoiVY0e+YowpoxgoZ9+26lM9UWNe2teDskWoMLR6pV9kFRiHtT043uYJ2\/1PznzyhoJMsU5H1fgqGBCxrBx0+IySL09PP1vSjfy0q3zi82Lw+o6w\/S8NEzDp3s8VRhea0UajxcDKrRlx2YHMmjd5WDZ\/eouYUxuuG\/niIRFMw4ob9mFjOfl4L2rjp53n87l6GFK37ON72fWXewdOM+Pwb8l9jUnDGt2mgRaouDi7kDGDAqc26VVvOMpA55D2o+jMgCu19hoX+9PgXUO00dUTlRBwcfCNU34O\/HF+9dp\/MBtu++zJ2ivCwKFkU6vpW\/Ogtrd17G5lMPzJfLr8txILL9U\/EmnvzIYJz+eFn3yzYPzAS14\/XjbpU4MIQhdH6lo\/WO7uzz7dBbaEDpnMySobcgweKe+A2rC5+ZGJFKCGLTq+v54OUuPPCx+EN+LMf86PUx\/eAtXN6WnL7Atgep3cnZLWBjTgmeU5758dekn5UnPNk+AHq1Im3LQed1sFj\/8djcWdErEhC4pSQENtPa48Xo1WNJmqgzn+2CajnHrQOA3UXFy1jihkQr5rrqaDXw9UcnKFYN4+QTaj+AvpJ+XyDYo4fiKY4ieCjRfGXMQelaHG74lz3xbFw5tDNjJuu9uhnHW+0ecMAwRPlT0cKerB2RyfF2yrMhIb2dCMd34uvpwxMxj\/TQtU0BXrRPUDd\/4lnmBD9ea79ifsGmA6fcPbA34MnH2pQdxEjc3l2xN5Q0CrFP\/zKKAdeH\/JC2psbAeSe6zcPDczcLL\/Xf7xsaGsJwuGPz3O5vWuAoJXjwSvnsv\/PL9f8SddtBxlBMKfnT3bweWFquVusJg5Wo6uLbq9T+6wseXGfk91Ogu8Cn\/OlP\/KxKULzPdK\/fWGmWOjEyGRLHB+ssZdYj8Tbyrp7e8M6OByPIg5LU6Z08KR5bppE1eK8Gmi3pwnZ1tw\/uE1Mt\/KGPDivnqI\/5t2LCE4J0mkH8ekZo\/tAxYGv39Uc7uvCd+81JH4ubUeP7+om1nsEAHz6XcLtlhVwZngx4L7QmhAfb4spfJMM3bz31MqS60k60BMULTOWp3ew+UZhr9e5yaiGo3nX3YJBkSWQsmRTMlXGj0Q7yYsvdI6HEo\/82wuL8wFhuDP6r\/LOrHoc988511VeP7Qbp67J8tA9WbWYrX5zdhPf6R97gqN1OfAFF8eymfZ9d9m1MC0UblSnqPV8Ohv3P7+M9240Hid0J57mbj02QLNGQ49MMKZw4Oqq\/bJ6c4tMKep3E42JxkGFpuPzlVtQpm4lNYyg0aYcBSLcz7zAfj6XxskPWxBtT3XjwytrwTTU7zpPWwWmC1qXgI34yDNOvZ2Yk8YyOk9P\/A8sR7qX9o5TZu8Rxz6G9VEXOLgrFnZdr5XVZAEFzTFWxhQNBHQo3v5GjYFvjsSaF0DR3kX7HJfSYdY436dmtkpYPrKLnN1Qg0km0qWLtWafP45vFMIJ7jcBIcfu04ZpEV19gORH8Gdm8m8ebCAVtILTfxai9ghJSgv57ptxowK7OPwyZHgk2MqoV+awpMh89Eg7sfYsriJYDAf\/\/3rVU0pUDl7WLDXemQVjp2Yd260tqymFpfHxgfeFypDG9bem3HynShnmRSzN7cRd6TP9dj8uxyTsl8bupp0IP3sraw3KbUYquPTq61AwZ\/Q6k4r7OfmVksSddE2Ds8Q6\/\/LM8QpXGKSL409HF0WuccnfSvoujhCV2sdA8qaeOZq1HVyc9\/0\/+RWz4unIcGHJO9NGPANCvnKHwH+ahksEa9GuL5o5Z+WnDbcdGRl\/usXjMm+xCzd7WA0\/jwKt3P2MHAKLw6GCV7clL0znCb2zke\/9abXtfZhg7m23IJbk\/VFkfQiUVY4\/rJacr9qdTVo7SlQ27qvB8g52N9P6ar9+lk4q+v5rI\/b6pG9JXn9UstKuKq2JX30Xgp2t+RYC+c046VHA\/v67SlA5G2hGaEjJX21r1\/jOmXbelAtUCyPmHyeVY5NT\/12swoCG17U3bragSmdJaL3d+ZxeaQm8pYmQ31szFtKd9gunI\/6lw478EiwsU9PLebRtEFcSnGfyxrORSeiftMzCQne96wPN908p202c7I\/kHd+cP5oHgae\/P6znp81+f+hP49JbAE5+W+9hosoUFlsv+ma9gCXD0Pq\/y\/kTvdfmtnPzcP9zvk9geBR4BQeBfbv47Hnu0LFjH2vWrdeYXL9g50cjjp6E\/MugqMOzLrdtzQcajD+9M5\/h+N60X+WmfG3Al\/YfDpBNrSmDldx9N5oxtnzIjP6fZz26Wp0Em9Nv8\/fh9cFnOT018QhocOEKTpMMs8Igjl5RtxzSdSgd0JNph+v9rkdXCjUxNWvErkY6Elwgfw4nFJYp7k4RrLfF1O2\/QXo6+HywLOOGug8GbuEm1\/KgE1pFzoetbn8tYgGy4sO0W08e+DnNj7pf8sqMOl6XCb\/s3oYynOnbLlNRT0DzxcNGRWwVSPcTcktG4LCxeVOGdRgJjy9WidVCtlN1RXJbXFgVvY4dWLyvVS8EaPmcYIKP5YtOGq0IhFCOTkC3HlXAMHl89QbOzD3UDpIHvWdKZ7fz+XyUb8f3eXckwRSUk6mdg69+M3u+m8Lt1oUUBtyepRKAfGY2MF\/EllcP5STkf6AQ2MpzCK4+qRuWdjmmZP0vCTYfLcduykdZN2FTj95q7cG9SKRa4OkLov019dz\/PUoT\/jrN3xJPh\/sO4C\/cqw2uFXlwjCxJw2yfVAreX0AM9NjhBc\/L4FBYq869l9+AgoS\/Qh11VJhZl0JSky8q+QRoYPmZ4vZqcuqwdJRrEn8VgNYM6StVkg044Er1J81xQz44+mb+H1hHYyLTDu\/0LYVV833kQxpp4Hd5y07vO5UQ8FhC+ducRpEFsV2ryllY2Dr7ony77UQJLskPmw5HfLKUw\/76LJwXiR7cI1wDRgf8Uv8Y9sM03qlt\/jysVDRd9ayDbax4NP6\/MXX3XRc0TuiLzSjAX59sTveFZgIVh9aOtYtpyHP4xYz9zl1YPZaflbS5L3MO+xSVHh2sk4l5k4b3AMCd2bVg+3BZQZdajV41jzCu2J2Fz5pztk8x5IJ0SKbitVUKFBzaixB3pqK1n3fGwUn+4B1qnV+26VT8LnZGieT75340W9PdJ1OAihnbY9I6qDhxjEjs7HS9qn5lahGzOHdTi5+KzGNhbEiztvC9zKx66m9DfVyKyb0n6kM4e0g\/SlA+iKPWjtshwXtSOqQSa5pgdqOw48n65okNbX6nZvywT110d9TMygoWHItW+QeA2gbpnv9HMwAq1FmVo8FBU0VzXM1ZRoxYvh4UvvXTm7e5byUFzOunqoH\/tlX+71\/F+F4uKT42sdVYKX5wGlGSAs4yVX8HlhSgc8fiRTt46uE0aqPTfmP6mD9jufb8+ZR8ZFJhqAxHxVqWFbNaxSaQUqEdqfcn4lb+Zz\/xDg0waX\/8o5AnNCbEVxNnMLVhMjeLW9y+BlI2byu4dX2Wm5+4s4u93O7vROJ+d6ljOn9rJfW1YPAd\/jmx15JJiCRa0bqk1dGQKQkk4XbjqvMb93Yin0jg4E3+tsgPI\/1zfQnA4ylfE7v4WVCyzGx+3\/Cy9Fj7l7N+Mm6e2lHgo68KAP2\/z602j2uEKsKDuX7vmNz53KkTulboc6qcOPOyTo2lFY3uwxs23bInmfVY4uhnb5qSSuIWQumz57s18g5f38M\/1P5b21ob3hz345HdPhxU++p9wEG8nH0bDBFz0bmYyKRgwlkPUD4Z8lcdfI5wUi85KG+vxf3fVUPyfePBn3DDwc2dNUh++CZJdZG3fDv9RHVh\/HJaFwc+6Av0wtpHA4DbuNwGLjzzFscnjMSPGfuv5\/\/vzk73FzsP8MnMlnTE\/G3Hm+M\/5E26FCRs9u+vxskbf37dtqkQONpP7vLKiwk8y5tcRor6mgC6P5qPV+ZzcCw8sZNHzM6UXe5i+ljfn9IP6jv\/DsiHZbTqoqvfKPi9mg9hd7LeRD99cqF8TkJ2LTzkIzQ+ib0HPk7T8orF0y01DK7DmSjr7FsjpJfCy79lamgdLIZL+j6dgf+jEO9BTkndh+Oh6YNW6jp5tkgLR5bVf6kAgoODieU\/6GDbqJh981XdPjJ0WVx+YEKu5c9MRWig1BNxHx+i0JQZv9a\/rG+FlKp52ivbHswe9Ys6ZreTDyrbp\/+OjcP5ytPXzX+jYKfNWNlBjbEwla\/w0pX9BtBZuYWhlwFAxZL3n8Z\/t4b9XdRys7wZqF9\/7o1x8ap4LbXmXeOUCXmK8WEHJlRA+OL+kXKZpWAxJwz3XFXq7DCOK9\/t2cVqO8+rLdksk4leFlII\/o1pT+xgi80KKhgogw0iwGMJfTPWQ+lBBoK60DErbZ9kUM2KpWMvesaLEANzj0LqZx7Fsi9v9GFD0a2hg3ofGO9qt+vXiDmezC6mGl\/+mYtMjk+IyA4vWBg2yBlkVyL6y22Do+c64bAWweTxY\/WguJ\/c8HgOsG5zUz+ltHvSYF7MU\/Lll2vhFUZhdUTx6mQZBEg2727DuT8JSJv04vgzCeXGj0NCkgkWzr0DEze84YpL2cq01Hlz9knApPP0UeLRy53tlXh0\/caSx+Y9YHs0c9lF1ZmAM6KZLk+KsBfYkJ4R5qOm6vnjZ98zMAxi3ctB+27yJxTIPXhY8mBV0U\/dZH8K7hN6HaIvRjUc+Z4QPg1MGaVtUftmw5gJ7fUKRQzYcNysbLxjen4NMQnQ9GMhTY00XuJ3omolBZoEslG5GseVp4QaMc8z8UlVZ3p6Dbv7+7z5lE4mhhwN\/pnDsqFbnPcGDyARL4PxsrMqD3msRu\/0YtWzd\/fDDOVD2XZzwvGlqCQU\/Zn3qPmClXBULs2mNmU+mzn7AR0d7MJDT3IBquhX7YJv1rhs0X\/N4sOKlhGRWZazO2Agl3vV80LpEOpaSNWC9TCA9kxL+nzTPztJm581iQHbYqv1IYPteIo9cdMijwds98eNHgSmjJZr1j6\/1lOx8QdMucfsOnw+0uhcdDzXBR9UqyzMrMTCd83TvF9I1+T+4nRmDwsqTbaKp1FBY1VvB0FOb24dOveYapnPdIWnhGQepABwdLSvdMn66GrJ5hnAgUaMPjYmbjN0wqgaI5gw4qScjj\/ZXaz7OxuLDEu+Bvfk40L1m1+NUIvQV4HVlH7jMk+wtLN6Pm7QgyyeaxrHVCE7GXRAn2hJVj+dd\/pIO1UcLNYkzLymgJO\/80pQDsip+BAUvGLoxfjkeBOkHxCANnQtPHAL9hn3Srp796E0VrlZxkve2DdfKf41UxPtN937KuMbyNKha0WDpmsg3XmUY\/NtWfDwI\/dl0x2M4FmrL005kcMCgwKLORvL4cK9T8vj35sgNjyWy9Ke1nQ8\/5eWJZpFVi2liRkWLYATcB1tXczC0YvSnateFiFf90UzG1LKfh2q9f082q12Gl\/KVMrKBv+2AaWeBd3g\/CMtvk\/NgSBanrl\/m6\/WNAyOzYzILcHglz\/rk9b7wVuWZmnjNg1oEh76uytxoZLpd+PrwEWmFNigk38q2FjfJDHxLsq7FOQ383v3YCywufeepxtR17dJV8ezWFC+7eRK4b5X+BOpg6fYwYdP5bXr2\/zoyPrt0m70p1iGPovd470nZH7UJySdwDJLd5xPBsb0IvDf+byJ2f\/udo1\/L4G9TlcBSR8lyi9mdFz6lkV1vH+s8+qbkFVPxd\/H71OdHT3T7RspOPZOxdV0m43IJmnucLxSoi5Ex3JnDKS9ytB9+jq8qVh9JjTHMtHdZhBTbV\/fLcDjTh5IkjmieQR+pmmOazXmkCDFkJnS+r\/HTj8QCB1tuT8c45Ke9+caDp0HNq1sjqagfcJvfeXSD7R1sPNML71Zte6J3QUa9TaZpDBhu5lo6bhNjTgUZvdJpXZho65LSGRkmxQ1spOHeTvhJ81CoFxtyjo+shHPWIoDQTD\/6UU97BRwcuOTZvfgmmLB5766dTghTMezwtsGrFGRzrH7Gc9Kg70xej9YWPC3lC+NTsmf+e\/9mfGzk\/W6x9790QPMfDrvwxR7fw4uJSnfjXmXw2eSPjR3jt5zpbXFJ4rbcxALbnR8OC3TLwd5Zy+IyAE1hu5LteYFo9v4oSPa56h4+jK\/qJjt+6D920Fnf5VEWi93cf0sAkLla76+q4W8wLf31GMspZutDFpW\/l2ogUj042v9q2Ix7JP+5cs+PgFLW1+Lzg0Xo1Pz4XFavwNh0Ualue+Xm3AoxeenStw7kZhMxm1624UvMXJhwIyH6qU4Bzeup++ZcIzDBx8qx2C2wdITiZozY3Mo0uHAU\/3TWws6cOlnmtHLnSVgWN4rkNBTizIm4Q8X6CTi8fWmBobS\/Wgsf+rH+ZiPbh+93GZxO1N8DqsWdAoMQc3NfZflfzWg8H3LdQyyxrhhxd1cI5AEvZz+n0Q+m+\/D+84fRNkcPomLq9Mw0+Q59LKbOCVVXeeeaMJGnxv7eE91U1yA+AkhxsAnQQ\/RCiax77mXyk8LdMYtD3QCzNLdT9sYVVw++gpucB4zVuvW\/hoNxTzC14sCi+GkpYFh\/UNWjBpgzhP68weEOYNctj1PBfGkp6EzC1tQjFiD0jqY9WJPaDl\/nV\/X06eU7eMRw+tojTgPoIXTeSDIJEPgmQd3tqUe9RMORgKkq427v9bAMU7Hbbu\/NSFmhPR4p3lXRgQljTRwN8CG7YEM34sqsKIkNQbDl\/bgdAVc\/WWDSrFM7ZdiyPrWCTrdurT4bJz82rxm8WfnQovern7qT\/pSYcb3tajsKbCl+UBPUD4gyD5Un72M74WFKsqsI5UySJz9LB3Wvj+2R9ywZGjNybzu0Gp60zspYL74Jc5\/XehAhMs86gnV\/2uwTpjnoVr06vBWOnYzOcWmfBs1iqBRwk9YLf6zf2C11kwWhp3pSrkBrq\/eCh88S0F7t\/Jlk05nQE30hnOsnyfweRf8Mmv8TUgc\/l39r\/D\/fDpuvmIgVAd11\/zJ3LnMjG+Zlhnxjw6c4SbXwNBHD0\/tBLnDMkNXnjayiJoRToY86zQMMgbBCtiTtJT4RyxSLwb\/6VeqdX3zkbHywkB7YbB+I9\/QtbuZifaeOwWzT6Xis\/5ecIe30wifVVA+KrgF\/G7DetfP3hYqwfIvB7Sv2\/kfHXFuZFOuPfgrXt2fQN8F9UN+9XYAAptSQ8UNxXhFSKXhOTedHb2W+9+VINZCe4tP2Um679f95RCy+ohzaZlxx\/lclgu90fmjcz\/9keLzFRrfvL2wZOy3064oJX0O5PzLpgy70J3kaTY3tFeaLIZ17cTqgHn29Sz2w98QS3xtbX7BAdwJ9EfXebkv+DnjhvasX7tKHfO7MO8wCRkBqW\/uliF+IJnrJiiFY9zxHlHDs5m4jT6ZfNTdDqYzz\/vp+GVgjcoyw1vG7FR5GuB7UINBginG9Zk\/WVydeYkL71n34U7+iUlUMBXsaFkHht4zX4rZj1JAs+0pBCtu+2whKPrQO+jV5Z8L24Dm1atoolfNHArFAmoU+lCpiZV58b1QtgVVf3xDaMSy2LePI+e\/xZGTGM7q18344yO9NNKoc1YdGpzWuz7dsg6yWc6JJOE79qbZ6SvaMH6AqMSWU02mC7orV\/Fk4u97UeOxoQxwd7K9sSGe0WgpKFSkJGRj6Xe3w3DG2hote778y9B5zHLYbh7\/EoaLB85PLCysgmz\/+HhEtp7sLzrOLF9TgY8iEnTWSlOw6WrQthhIuGgINnXniaZC5QFQizvJZN1j+qHpF1VCeC8Lu5S00Au1GTc+ONQT+dypUj9xgAnlwp+ELlUpF66TkrcJGmoDQj\/MslBmuprQHKe2TCm7Zfu342tWUHfRodiuPmPFldNUtLNe\/D2fIlZ+yuTubrx4ZfyUqaUBOB3\/7Lh9tN2sF3eJHGOkgZEjhJOyVGaquPl8gfkBld4fnLoQPnq9jiT+wyoFwozzjpYgLFNNY+q17WC+6UvbyVk24HvuVdUH6MY6dvnD2QdmawT1qYY+yUzQfaeT0TtBQreiGB8fKJOA8mYWcPe39iwwvPRNuVjVTjkY+qha8oAuyTb\/FkxnVBL7BdSkv13OorTQSExa0\/omiaslHGdWf97sk4czhEV\/sUAhUXKr58uZMHNRrZ248PPYHfYLEn1Rxuo8Zz+s\/UJDWadXZ8kmZAAQdc6nCRr6KA8k\/fbGWEmHEwyuKszPW3q\/ATJvIP1vY1ptM1MLleWrJfqOb4ksv8l9TmQVf9uOqW7GT12+rrZesaizcQebZlIOna5ltGu36TDqsXzzvD8bcAVdgkbBadXYSf1RKj\/OzYMGs252ZyaBbttmg\/8P67OO57K\/4\/7SBokyqqspJIW0qa3Fim0JEpGU4WUsqOsJCEkSbKSItmbt03msTdn2SslodLtd7vOue+vf3UeHrrOdV2f93i9Xk\/fEjqYxttwfdg7wNT\/M3y+NXN5iTAvLxGOTJRY5tUWgLHaZ1nd1S3g\/aDrWn4AFY5vtn\/r596PjPORsf+tV1tGqyxsgAOax7gntZvBj+PisqVRHbBQvxO3R4aDX+BuJ62hjzjRsLX9pfQIRk6NvUg424UXxTZ1PTD9gnW2GV0H6H2Y9S8hc31gMRg\/o7x5ujgJgpJtNQs76Mh3JON13OXa2ffQrWucL9txrTp7zOaACFji5JqXltOA3CWSnj\/etCFL\/I1z3o6KYMEXu+PukjiMEPSj1znEgbfcqQ9eTX0QmiO3JNTGFX9c+xhrqpoNvLf3\/nGNpQKezy3dqleNh6g3msQDw0F67fK8UQkyuH+fGew4XokR6JatIPEMYw1ED8j7UyBqOLJvMGiAyVNj+E386\/y+hzf2M\/2YDD8+Mf\/EefNPHO9T0PrnXYflc75IONX7J93lWh5MLRdobdShomlRym6Hpkq4e0x25aLACsZ7Eue9J0GcHvbPwZkMjHwDRo6ccs7mINZUMtOXTXCpUF2X+m3hu3gY26aQYmhfCo47zay\/HRpi8LmA4HMx\/I8gK8i1WVkhGS68U80RMSwCA64bOaHh\/TAw5hOo9j4LTB4ebdeWLYa4xhlvr6dDoC8Rnv2gNxpJvW0PHl3pQskhTNvysxB5P11ZZHKuCr7nTfoeWF+EgsP8NVnDJPwjeddrrwgJFj\/p2+XfXICuHJSn73xKsNX7wLcXR2qBigrFbUnZaMX6My9vfxWek1u+JCmrA51fsW\/ga6Ji56WUi\/7YjNdXGM4kD1GA\/WCnWb0VHQ23vwgbcs5kXGco++91xsXibrGSpiQ4prmpOsF8BMhEzsn+\/3LYkcFhL957sWiPUhsEmqbKsVRFYMOPchdv49nzX09+NES8mZlbaGKafwtGych94Hd6V0graqWukB2SoOKB+FAjZZ8OnMdfYD7vzc\/dLR87NMFZyepXdhlksFx4YbD6bjfKhOgt4AhoBec4\/5CnEWR4d\/A2f99TOkYaHBQXHSch2524H9+LKmHzRkP5308awdf34nTkdhKOhEhuzV1TB\/awmobT9SBA5JmYzuWZgD1R50ibLHW2O1uNdwk9M0NP65IzuXKndzWMrF3EZbR8ANxjKkpZDOrm6zmxgNBzis9x4pj9KaNOKNNvLRJna2TqhBlcxdiOL+JOF7PgvYd8w+PcLtSSEOQLP9yJZ+JVflWcyAVNFY+1It5U3HXP+E1EYhtKm39vXFDXiOuIvU8Ysd8vm\/PLM\/KRMGluL4MEFxXncVGxqmTx1tc\/yejqLnUscnsLrk5ZOeb8mY7TG4KX\/5Km4DdFCu3xYAO6vftQ5qXRjbQlP\/PruXMwNSdR6YTVVxTedvcPPbkbjhVF7S1QaweOA3KWAe9zwD+h84BaYScK6RY2mme2Qu0CpVcPz5WC3ukYi72G7Tgvj5Shs0KSesSYDe0KMHz3DD2VFB+fr+AzH4j8Oj1s5UZh6qliTRLMzdyL4Fbl2KcbDd1YU5Va2pfYBkEE59ppjnONjwnO9fUfPFp82gMYRfgcGToExWMcd1uk+vFb+xvugNX5TB9WiuzRV6o0OkSPxrS6J7VD2eTNgutD5YxzBOedIxCeuKSddycVQt\/0P898QsLzeZOCijfImKBY9j3MqQPMW30XNw5\/Bb5\/S75SpNqx9yzPpMSeQrh84cex+mudaMjP+sJWg8bgdwPD98rggIuJc8in8Q3hPkcHzt27q5h54x5vlEmp0\/1oVcFSvu9TJSwNWJhPD2\/Gn2+fNRRaJED4thvlzw9Xg4W19efTrkNI2aKRMbwsBAatk9pP91fCUNC4D1VmAPs3KNoZLihFn5ta1zWMilHr6Hueq\/tSYSSlJrm9uRgThb+rXurPwNP2N0ubSqPBXeV5zZR1Mo7uUl4u4NWCcXL16Yp\/esFojvOODM47o+8r6d11+PLuUkxgDXzoOtoNjPr2CCsryftcPh6v8N\/tsI4OA4urMk640VHeqUFz9f06PNYQGCzc1oF5u290u09FYvjOdSZuso2wYW\/p67C8Vlj9ya\/FQrobC9esbntUO9uXeVotrrIZAsY+d7DCrIK3thfruvjfpbl2wvWEfaX5rLVgHMm3zyywFR3HNr5bZNmCQ9kfb36reoHl+7\/0Rua3oLGjx0E9lQb0+64sKXLTA4RsYXXcAjpaEfofBu+PyFlFnf\/mrGKW2IbQxZRmHOP9sVm4IBOo9Vz3KGfp4Dy4crqoaBBubu\/gOrCsGr6\/9D3Z5leA5OmMjyWq\/QyeOBB8SWTwc5WIPCLGnoXwm8A8v8l8vTRzfx2tFzVwxaUCBFQWU3YM9UDkmaMnxd1a8bSOiPoCzVzMIfZWbMS5uerxcc2JFjomTIqHcnnkIxfnn0ufJYPg\/pxvjplPyOivI+d8dmj1X58d9FaVGUeYIcbuV8o3XdKL9VvWzrgtna0TT9Ud\/x8XyOWSfCppQxhws4nviLlZhQEOyz6fHG8C3fzxez3qZfC33YT0MakTiDocbObqcKav55OPuS63Dwm9Iu9V7mpLRSEn18C0oCYs57Ymyb6swPd\/4rTz5ArxnGzb\/gLHZiTytXBevhZyzu3vmNeB0OdgcxV9YequRyi7WvwXh2sNWKgvaHgdmwhEvwDkuX6BqXM4PjfXZeYJbyC4MxtTeD+lt6eB00W\/WyecaTjmxMa+mocKxVQJjsTb78Fje+eBK3F0lBlf9kdwtj84E\/ScbW3ccxQJsol22dkNx9XPew4o0eDV2pKrvu1dEMTn2MwXP4j3iPNrquDF3iYyHe\/zx3Kcbc0CEdK3Bz8EK4HUpKXGf4KGn05xvpVVyQSpUu6U0ytKYI\/Ftbp7aVRMaKtQt5itcyWv5NUf6a4EbnfpnjgJCqpZ\/w7oXlwAMhe7+MK7SsDieuyau7xDsHHnFV3Djki8rr7Cx3J9FtjGT+49vKcBKlY9Shc+NIhBWQ6DZpF50NqW+shMsA6SHoXJJ6+JhT7x6S86s+dbglS5yIvZOq7w4tePey5kw1J+xdUtF7qQXuDW7xJUA+13HfdKxWWC38S+H8Z7Zs+hOd43zuN941DmH4uX79swsImF5dTTBqx9u2Xodx4JpufmHjhv7oF3V\/rOpFzOBTuij5sJ6NPR9RiFMLGKJplzRWD2T0CN4pAD0rNnymLvXrx866+I1JseYPh2peb0DDjPD8vwc8H26Tzxp8fyMOURfXTAqAOyVMgKZpK5KKlWeN06OxW3uYUtz\/vYDiKJzedpugnz97mMnEz45h87BLF1+Ffhyxde1RFk5CMR3CIcm+MWwU+C75N4MI\/TrT4AHFzrRh55dkH3xiVK+Tci8LiW2uAuzTIw+0rheH24bbbOC27Oi++HA5Hv7NYfKgYPfTa13NMkkOvs26hv3wnTx\/U7tsikwCPjb4\/ie\/Vx9PS+t\/2vO+dzpRlzLVx9ME7uulMTyL3Luh7DSkfhW39Xd79ohmVv1\/juDo\/H0qsCXywWNOGRC9Vhq8gU5Hy1SnarNpmZP9nus2+D0L4BIHxSTD8pI6e6q+DQKbdoGvw5m72kKoSMV7mvrywIeQtc+95aGd8cxok7zwY4uJswj8hH\/S4hJPaTMoT0RsFW\/U2tDM4XOh5V3uE3WMP8PDGvA5KyxOHW2feV2RXSljcco0xfP1EfIlEfogXBKVAnOFYmRG4eY49A5DfCvPxGDBd\/0IkuXcCmnjp1zZkG7ALJw2IZ9bgkMWPhA4k+rCP0LYT+gelbrPuvPx2kDpJfUkO60ejGJ7HlFo2o8HJ1krU8Beb1U+BM9FMiJBu79pA+TDzB5n\/tWSeEDLHaOX+NY\/h5wZn4OwnOLxJ+XlAlfGoFxPUso6fe\/3VuCN7m9XpMUkqB+9Gh07etc1HAY1HCkvAaoOvn2hnbF4KUzq2dKdRykDx7KLFrdR2cWSvDE\/OyArY4TyxaRf4K\/JyKYvbtxeAocAgNnzzHZPLwqcoDg7Bvw3u6G38VcI3IOWpL3kOyDqvJqNIAtEtusLDNKYQomRVqVp5G4DV4UdVmpg9qI\/5en6xNB38xjXcSuT3wIaz1hqsUDZw1p17v0+kBb45s7pXRCFzpZs0LSE0Ytrc5sXJJNtRzX\/9LOYh4tIRW+v1RFa5ta+8yEixGFv7WTt2IArS5cFJseKobVXJHJNfmxSBj\/qlM5KNGxNN0KP+uYFTbEvv13aNwe05PCGoepu\/eZYShlvjG60fvDINJnaTbF\/cvcN4zYVv1klq4qfIp9G\/SIAr3nr714HAhxHhVt+tfK8HNow43lRf3QUa43lJB0xyM+m9OC8P\/hUHKL1cu\/HMP7t2dWJ7p08f0VxIcTyQ4ngw\/C9hdPnDNzi8PJUhyPV2f6uGedNaHb\/8qoX3lgXYKez5eH9SgOIXXQ+PhsQXGD+rhy8EY68rhaPjKdtn\/WWsffDphL3beORFC44JTvtWTmX+Pha1m1VurOlwv3352lyYVGX\/P5Xq7qJOz\/Ytod\/pdOfNOrCIf1R8T64ORCKOqIfcaXGmxurEzjYx95IUb2nR7oe2vd1QwLwnfkBdLtNmSUSX2Pd\/Xvh6Qe2NcIuRch2tHvi1\/c2S2D1m2Rot7Uw8kdbNcWn+gHleEe\/enqLfhSvrSgyeT+iBcnv7GmlKLdf9WWn9+UQUX088cmjiRB9u+TP2s2JMF0X9sF\/dGF2Igp9fT3Sm1aJaS++\/4TRIkaOWdXLu2EkWlOZ8lnPuKIUl+vnsL\/KE3onGl+p7\/7R+HI7z9qcw8RvZDN5ZUaPfgfmMuidVyVGTwht7eLunBYzV404\/lWaMHGesp3N\/OyjYg7aOrtsbOahSe4SpZK0RFv\/tGFIF7jfjuvzo35nvGhuO378PUFii\/tbFM8HYZtpuegU3TSbht2an1HBylOKLd4UJ7T0FVAddz53+R5udSMnItQLdJ+4jOn17EOQ4RMvT8hN8Nl\/7X7wYRGt+eSIt645qJpKPtH3owSCt9gcxAKxwZ\/\/uT53wSxNx0tdd9PoCeUSwJLza24PtFhp8CA9LAYsL\/wYfDpTCQm7LM4WEvcN71z1qpFA49ryy5ru6Y7dOU3Y2NWZvQ9H3G2V7\/elAQTyvb+pCGF76H7tkqQmLon4Ghf2bohHfO8ZWAk+ArMeqxHgUx9kv8hWAhrCrckFfM1CXKTK0yXuAWC35VeYNn9rZgdkzS6OjrRNxzRntya0whCt39fJPFNAHpj5cKek524rAEp9L5mEBG3iYw9j6r6KfO5YbFQ8DQv\/uNfVlMbprwjjP2DRwJwB3n1He1Ih3ct7sKax8ehs6hNAFKUB4ckUlvL9fMxxy52M\/ahypgcayQkmtgJTL2cYw8ZJzjucPMHM+dyWvzt\/V\/kD7WiVuubuTRf0CB1Lg76lk1H+Hpf+fGjHwwVNP5+0X4eBGaBRv2CpE70Fyn\/0meWRv8WWWwWvZNJlqtp5mIQjt6XzqRwTPRBL1nTn4Ma0xi9AUAV0V7DCpHIGWOh4jP5niIjLoUpOdygZDIBQIiFwhuJxa8v5lTgBPK8R77P9cx5iEgmlw9uTZg9hwIft984VAdqKxfKyb+dRACw8eHdk2R8D6ybXzm3IrOd2dkJA1qwY9tXDjxcw14KqufyTuZgSZiyqaZze144Mz4JzchN9j\/9eqCna\/zYKmb1LKBE59AaLPwxjalBEy7\/fYxj1khCDXfSd0ZF4Lvf97a0LDtLco8u0e3dM0Ag8UKis1dJvBta87ujvMtEGH+gGq5m4wF4xeXLj3VAZrX1O9\/XNcG+ZYy\/LqNyWj5qu6ufFgban+6lO9+uwOaFw58W700ZrZvVL40fY6MHlYOGerkRuAl+OMEdxLvT0j\/ydaggrvL4b+b2OqQoXPeqlaS8GJtA6gf8B\/dez0f24ueb71a0Q3EfBvmzbeh1mTjyKbvFGBtffXhqlo13pzW+2nwcPb796MUP9P+CrZbC1euKEkArB7bQfJPAWqubUtbVDnEuhovrNrzGso7XR6uj\/8EkwrprvL8JMgdj+hAPXu41x8q5i6VDpwcLucCL30FFq9gnm2h+3E8cW3pwo5c4D7L4a2rWAOLrEU2da9\/j3IrejRf13+B4gWC1x\/M9o3sv0NEQvjLIVmD7YVbXjzkEvftv7n7lpmvvqtu18PYO93MnGTG3N7YS3iiwzQNRqXuPa5+1IdnlDc6yfTUg4BS8NO\/Oc3oI68T2ESjoBHve6nRcjJE7qzYyudbg+O3zzz5VN2I1JrS8i2Xa2BfeKiKvUAltGb1KgguL8DfbFMKqqZkmA43OLIgtwSvarzshUt9uLr1Vcnw9i4o21esvMa5Fjx\/wxOhth7k22hjfeV2PczT8zNzLRj8uM9z\/Djm+9zqY\/evlddrYELMrpdVrQ9DAx4P78I2UDP95HmlrhkS3hxjP\/OwBylK0tv4ouqBbHYgKDi0CfxOD9nr3OnFLVImm4SetQBDbykyp7dk5ipcjzsVUBaSydi\/MObPIC15x6V7K4KQn07+FuxG6rMDdZpXZusZ0QG2lOoaEM3R0\/Qa6cPGIpv0pi\/NoFze2jRiGYnNvut4lx4qR9KM7uUsrueQtbBK63aCP9gX+hz+7ZSA3ralXFc4XIFUqb9Hj\/wZaYNmh+LDG1Fo8s21Fzv7Ie1O6fVobzpcf0t\/V7smF3xWWL1iJX1Eku2WOzzdVDjErieieakcaPZnKqTeVuL1hFW7BLKGcPX6KUHN6komB6e\/4VqvykEyxJYOOokodMPupNd3DMIKkEf25zep2fOnr1oz6dNQD3g+3DN990guDrDaOWpHd4F\/YxNXwmw9Z7V\/kPbG\/RV+edrN4eY\/DASvBM4TuXbL+tOmKlhHGM8dg0eApz7uHaPTB8HJc6UpClUB4xzpI3wB++Z8AaBJ+AKy\/rsXZvJQ5vnfkeF\/3\/Z7253R2d9\/hjtwb8OVfNjG89hcjL0Kx3XKvjh00fCqHjVlUK0Iels96k7erQOxz83kyjelUHyhNsVxSz3mxYWZ31pTDo0vJNrbg\/oZvG9k7DW+Rz\/z55y9zkLA7VdqRkMVhYO3ystnz63oTVebn\/dB\/+nid2JpTah8hcyeuKwB5Qtj1HantsIxA4OWZ7yNeKDfRVdJhQR\/ja0Ktb1I8EQsTuTezzoUXhCe6SNfDTdXcQobLi+Hxa1T8azaCD3By8p\/\/aSiuzX\/8QmvanhZrNnaFRQNnWyZ+h2XqLiojWKfokoj9MwGCozrwE4pl4\/6Ugd69+J+N7mkMbkqCizRt\/bfaoCeEx9sZ0zjsXjYZgVPTz8sXtj645ddC+xPPaFkeieEkTMJ1CXL7N3t6MyfM65\/Y7DjuPSL2fvEQ2eKEyPQzEL5y3HOXkZuG1NH8Z2Y024WsjhicGwA5cuKJW3v1APHVNSu+vpaKOTwUZO+XYkLLyV6+R2rwMth5ce0B2mw66zOLZoSDRz3r5p8EFwG2txn3uykUCD2k\/2Apx4dbBz124OdS8GChty\/H9GhtsYnhtU\/Fe32+JBPaJSCeYievW5LP8OnA4RPh5nHKBVmubxSqRs0X6t6ym4oBSIXEc4Uqasp2ndDpDBvv7dpORg9GZ06vZQGt+bmokDMRZHwxcPSEI3lru7RUGa2uKSgqR8lC5zunbSqhT2dg\/neR8pxRsrP1sGxB2njqf8SplrggfU++9aIHjAgvhdizwUKervFmmoHYBPB1\/Ym\/JK3r8pJchvQkGXpcl3Nmx2oyXtQP0+BzJg\/4Lz5A\/ac7npx2Z+GZma+Y75VZOTb6bNP9UoX\/hm4fzU8cgg+iRi82lWehG7Zhp4zHQWQr\/WtN9SfghJ+SYkLn5ZAuXvq8e7dtdD3JFaSPSsP8suG8gcekuDYvj195+O6wdtqk+\/voRIM+ZEdovO0GQzYcDRRtA75XmZLqiZ2IWW7Sl7XbN\/fyMaqI3e5Hk4N3XtuHtyF72+efiCg3wMsI2zqi\/obYZ\/tFF\/+ixjo1Y0VZP\/bgAGmaV09nQ1A4pE8cTs2HtatGMhtet0KYbnVFh8DaJAftVbHICcdvn\/P1gtwbgUut8uhW\/dSwMm0bpOLXDTEWk78Shclw33ba56H\/8723SniM9c5SbjP5JBmxOoOFNJzYPm2qhXaTWOdLFIosD1a6burbx6eEqtgeehJgbeXtw8GB1HhMtfHz6zLUtAogcZ\/5hYVij3P7nD\/UAqmHOm8DhNt4HjMiOaWR4cjTuOnTprXYk4d26Zk47c4I7eoaVFwEbTMcYRhHkcYbt3Rx\/d1dGauCEN\/qCDWYrzkZCHkti8K4BkoggAlJ6Ur0d2oMcB1LXTFJzTwoYyrxxci7a5amvhlOu4xmzQyrfIAkbVm8NGvGHmmvspte0FHI3WPyvGANxjQazlU+zwJd71azrK1nYbGLN8OH0EfNMjnn9AK9QGZ8Wk2iWXdjJxGIHIagchpBLdTEkvTVs2e2zFfc9XedzJy\/GBXX+ojB84wZP0Q4TpzoQRL9k0M7n5AwXzrCKEjVVQsyt0R86yhDfleBXhHDBWhXYnlClkZCrp8FnfsbGtH+aNxFt\/Ni\/HKlnKrneNUbLdbrql1oQ1tsp77HB\/LxeB1bi+WbEH4wiPvTFKPg1odK9s+rWFkGVxreKu0ADTu7TA6p\/4CfpQogYfZAPby\/Hjtd7CTeT2VLL2kSJJDeDw2UpBlZRtc17nwzCErBMPSDgo9VhxAjjnfNM7zTSPpv3mqTF2K4GPByz+0kvDW\/kKdTodeODUutNgoi4Lb7rzZ38eSBuMbVRo9X86+p6r6D6x9VA3baGMWbwuywfXBmPx3g25wSis7f4G9FniuqG6\/fKMdGHkvDF75o4Q1WyUHGsFNNOhG+boOkCDmTqYcCV2j0YPwI88hYPXuKHw5pwtCtis6+6QEQ3HBTMEBLZN2aJaOpmYuJeM3RVNppelraP8v69WxjXTIoTm8+\/ElExWePGAJPtE9+15z\/Mx3IR\/3HDJ20FMl48N00dc3YqgMvRlzf0dwx2AedwwZdSPhi2TqPQi\/JPPnDH2IvKyIwa5zaWjxKzPy5F8asP\/qWiyxmYxelhu7ShYnoqji+lieIzQIMO28qLiJipGTB1fee5eO5OA6tvHZ98PYiL6K7RgV9YJf8K\/4\/giE+QN57Bd0guKKh1vzdnei3Uxv\/ZVXfvBl8eebqNoC+ckDb1Ud2\/HmaqlXv1mzkXpHxoNzrAFksqk79QPbsWi3TwMPWxzmV9W\/L3\/ZBPeWJFvbHWrD8SUfDj0M6IADN95S3Tjrccn3EIHL2IOfLvPmfFQtA+cA2UtTFQPwJ9lp20h9w+z7ULjWZ2Mr5BB8JYIDgoTOEObpDDF5mQorf99XOPHKUK9hVS8cz5l43FraAuR3y9lDrSsgUcjdOry6G8jdzQsNfjbASv3Qb8vkB7D8Tz55zduvGPOloFi1vwU1LDKSJlRLUOsCRzn74x6o\/L1w73N5MrYrX9vZgsXgOL6zu9S4Byw7O5fwudaAIyXdvdWqGss\/SZ\/k\/9qK6b\/3KhScpDF0kjBPJ4mELwPm+TKwfnde1822Kjgz\/Yf1Z00PRJv86+fzIePpC5bGtKfFwL9zV4tNfgLwuYC5gX4\/sHSdE2qMrwL5nd7CtLdJEH7mMccNw34YmfNpgvecTxMC5vZ66LM1cYM0dx5o0rLHvMSGQVz4yfPU0M\/YpTIhpSpeCAx99S7Ch3jv9cLxojcFUPtNzZflxhAYLTM6rH3BBfcRfs95PhSoy7y5hfVoGJb\/5LPxGBtk8qzNstfv5g5pZfKzGDrGRJcO4ZCuPGTk2DPyfJQvHlWwCqTikd9oUn41BeJeK0leT+5CF0zkJHn7M3NRiOcXipVjXM+pJEOK\/HoZ5KICY06uF6TW+WRvKJwPWDx6RYACk2y9rgfs+kDc8WvH0WefYL1TUb+1AhXuirO+PZ1XBqRhrS3L\/ek4sYknrDU2AVLvnFJdatiFGy5t9kpb08Pkpo1pHOy6UE2CpIOB6Qfj6dD3dPNpVKbBGfbfBXc4aiDuifUzm1e9SPhGmfoZ3cGxnWo3e2f79BemV7u9cNWMinvqw0YcWvJgZycXCT3YJ2IcNIZAbw1pSK+kCLUqFZ1zlcrgwZyOGhg5b7eEppO3LKwAFnb5Y0d1huGq\/sJ8xTyEUvnsZ14iRTBdKTOjaDMMYempJzgPF8LZBzeDThxqhkDqrVZyZQsobFT6sOisDwpIcKkdXtAK5tFyv58ZN8K9Q7993Cz8IaF8q7L1oQGsPZYgZtM3e84uW\/b0yG0Sjl8LSdvzsB8VnjrI3hVOxwoN4c\/qSSQ8+6jI9Lx3HK7oORwwQqmDwPJV301iqJi1obvmLC0XtLoD1v7ObQA+NnXNMaEO+JJ9ar9RXhFsW3PTZ3y6FjyG4\/\/UcbVCEys1VMziI5xKXfnneNkoTBJ+aplVyQ9+Nl+Fx2+t3rbUDID90otSEbR4WNK72XC5Sj+eILjDjOdIdHTBhUVjdIxasvQNn2gzJlle1Jz2qEDbrILqx+\/boYy4Px0IfbjVjs6VNrXtQPDK\/z8OC6bewAasmpQU87dLQo\/Hri3p72qxKGwzRaY0DGq1LyanqwzDX8Pjl4ey4mDnwl27s0P6MSDjQsIUVysjnwoJHS\/Tz8LgXBdP1qbdd+vD1r8gcb28GdlyrMIdFjbjk+o06obaFDTLCfxNelePv+U7fi7SoyAvi++zPzz9eE6i7GlTTgsajLRPT56ux1aPRqND2SPMOQMj9ylrUb9p0qYREFaUMNat+wBCxPUhzkEkzkFkPEdW4s9P7NOqR8GlSq787GRmjjfF5EKNOrkIZjYm5mReGwQNDt+ZYska\/DN1xOppWQtcH+jK7GEbgLKglb\/la77Cmd3DC6Y\/96GVxh9xNqVOjFtz+4gEqRBSgh0beujd2Hrb6txfcitDLwpytxxSb1ByMbyMJywtsx+jaBoD5I42tOCjW51+MwAE1xKliZw9Ii8RjszlJTJ12kS+IhB6JCTm\/0Bfh1dkP3eDTW29x8ldJbji9P6WXGcaeEssrD9sPAAEH5PBi4Qz\/93v4wJiv3\/8i1dOL3sevtIo7\/dT7EbjU5Zm8bfpeEp3p60vWzYeW59zesqsBysWmOjLKtLw8twcA+fNMXDLf\/3dTB+Zt5Rd5HfrIYypcPq58nA+bqE+5+ddX40iB+wPyRjSwU1poeyPryTkNeleqXKajKxhaoeHDlNA8JrPntORZWhYFNI34UXBeX0WI38eDuibHNKbGkDnY3ddzp1tglfO7BuNTmbj\/YCUdtcCGl4c47nPO5oOIQUChkczSHDtMvv9205dGFSIKwQeF4KY7qUQHd1q0Nda7Xs6vwV9qqb6391pBdYnrO+i3aOQtEIv+DBLM5JnfF+nr3KEQOkSO9FjJIjJP0qpGmlFicGt5w3k4iChIeVs71g5\/Hnj3jf6YLafF\/jQ0R6ZA38kJ9UuOGaA3sf4ZG\/z2Xo1IXX6\/OpoEN\/mbr52STGctAOVN8sHMDhn4pmLVAZs6TTt5lteAYts7hrdvNGFapwb43\/5p0Pk115794hSkJ3LSQAiJwEYefjOzzg8LN\/14jLBXeImVWSQFt06OZBZjiNz+QxA5DMw5pYM3xDO8w1hwgopnbR4CmYSn2fwl8XbIiRuvSHjqYUKSk6z95VCu+VDDgcKFmS8WQZmtdBYfuBzbUAfyMk3XlQUTcOMcpvgVaE1OL2+dZj9QzmQ1TaIWo9nIrWrW15LqBUUWE4HKb9pRxFpl87tG5Ihq+5yyfuJHnyg2rJtn9AHdOToCbbJIaGleqSz\/8V2kGFZppIY34IhbIPfLVgOY4rqN7HKz62w6zBry\/4HZGy8Lih4hq8IKr46jr492AEjD8dMNkdQcc3Ih9BjH3MhYo4bC\/O4sQzOLMzjzKK6vpbdD0yFz2pRzdvWtoO9vVFZv0Ac6HYvSQ6vmP2ck6ZWsCL1f3wNWVeXTvxm\/M\/OZbZv\/BOWs25fej9Mz+WF4tG+idJ9mq1INt8iU3Mqg+n761u4NPzfxmaU2DY4mNlfwMi3h5T6nU6PtrdiM5GfwNiDd2zOCsh3acEHRH4Fox6QE4rgOrq4B2dGN8r7rvuMf+wuv+p2+orvSgS+6+u1Y\/Dp2MEsyuw5V1\/DoaTZB60Hh9d\/nv3\/1+7M5ti0aQArCH8ToSuAeboCdPO8yGIW2cnsdwi9E9qObG86Mt6Bpvkmcjyve6Gy7xlbVE89MvKvCD8mMvKvHg1ZS1vX9oBCypq7h4NJWHXbcLnsGzKjrgBxIo+CMRcluEVAcIuA4BaBVvLGc9SQdvhuJlYm3dKGip9PXafplUPfX7J2281u9OP9IKeZ3AuMfI95uX\/AyLchfHbY8V+fHRI+O5zns8Nvc7nowMhFZyc4DlnGKnHe\/+jwZ46jzTgHIU4nCAQaaSChqPH2tAgNOfo3axmfa4CrGtXpRWk0qBrkCPXJ7MX3c3lBIJ9eZSiyvAXU80wrTPN7sGcLBmxeVQ4WIX92WkjTQZVj3Wb3Pxlw27hs8u54F\/RyeDbwLesGIXNxoyX8JSAZ67RCdSEZiOcX5j2\/YDFXDyCxX4OnRE7g8VHl1JAtnXBWcE3hF61efPbqjN3xmFp4d8dZ97VtPk4SfooevoqwmYZanLyzUPNsTi8jXwsY\/A6ZPWP7W8K7sXFxlIJ0Jw0W\/zzt9acrGcU9H1\/4OtyCUexfTu3Xo8Nxzxp3h5BmXHepLXF7ehf6l+2kqen3MXWMX3WDhlyWtOEhfhrHidEeOK8s3nukpgU3\/PrmqJTfy+TaMPJG9LH9VvGHbpSz5Nbg+UED8jHa1NMngQDhm7mGQ3tQefyffvRsvxNE9Av2C\/o9OZ734Oa5HDBImfOXIe\/n9vgxrirwtHnnNrM5HcxuXq9P5f0KnK48\/X0Xq8HuzcDPl9eTwDF+kUJXVC6kjLs\/5rLpQd8cxdwg6R4mP9H9mKbgMmU6Kr\/QVHnO1Q1Jur5nw5fn48lNT8TO99dBjkEUf4t5AUyf\/aucZJCEarftNo1fz56t009cE4qthceZnYWbCnqQyAFgzhM053IAcHTOx8E4f5l8q4zEveu\/u3Qhff3DtvXWPaC2PuT0k01N2DL9+8ktMgXDpFLeh\/D2gLn92O7JmRqc\/JeV+2n2OvOZJIucyyuAfYVCJZqJOfjjuE5SEKkRJXVvXNsmkAtrJjPLJrrysVTrQ2NnRw\/4TbRMmS6qhb\/9EpzLkmf7VZ4AUmsADbTE\/7BkDlAYejxkOdgaUKNWiQmHFv4rCMrEJc\/MN1ZuT2F8j8D4HjMIfbIdfdlF6zVUuNzp3ectQ4coN7N1vGuycGJ7huo2jzq0usTpuGdTMc5sMLU00w5BmQbnq1NhrThJzJc61EgSv6L6kJibYf\/c3IzBgcJHD3uGwqrb8ExD0cZNM+2YcCHFgnddD7oO3LimYdMMC5WrBrNKaxDm5j\/QTntmSTNvAMUulRQhnga0X3a3LC+7HyYk0sLWveyBXFpNZuRSEtRKF97UT4pDYt6F8+ZdeMvgx4FGfwr6Eb5jhu768Fs3ra6vnTgksoByxL8Nj9yVeMvh2I3uOQYdtXXt8OC3vOqKYCqYmSwYMHpUjP1yyyTPr2yBavpVm7dcXTBtbbOCS5aGNj+3SHkldYDar8RoOR4yNA5vbta9RccIkZP+arpVsEeJszvs4RD8msvrgJQUR3LUZAuwXIoWlebpg9zbysYfNT5i77oTFy90t0BIl12K6XQ36B0tnD5Bj0eB5T6\/O5IoINr07M4jjn64Qug96iOtqwU3JOHLhLKjLSvb0Liqi6RSTUYS56LXXpJPwK7owO2frLUwFnZG8oZPBC5WiRiu4zeHe2cXnPAKbwShbT1CC9e6Y9Q+Y5PE1GrsPHecd4JKxrbAXS4ma3pRzdc4zm2chKd2VSZV5XUi+\/bTcZo\/ezF+rr8Gtrn+Go8R\/Qhr\/0jg+VW5wHpKKWP3l36UXqH8XvZmGxI8SpjHo8Qjizs2rfjQDxr3ze+18bbDCjHDodx\/OTi53Uik\/eNsvU\/k5OxKjDkuc4KGBI8D5vE4sH3QzOAfey8wcjAY58jlx8JreN1IqGR9rLehbISZv+e3v4h9\/UA9M\/+nk7hvCX4ZzOOXIV\/PQ035wgYIc7h5W8pu9jwq5nV4MtSNjjZbD8u\/rgOe0dDgVwqdWKfPm1o10I16wvsjwiJIoBaxZ4+u0mtIVacXjb\/pg3m5c4x9GSjp3fYK7YmG1fTDa7zzemBzutebz+U5YCZhpOnAGQLW1ZNPbrB3Q9pacwXzoyVA+q8\/i8nFyKrcGtELyXC5pVEv41kvHIs8dvtEHwXOUJaWlSiFg+uXCaWZ6mJ8lLKgwlKBjL3\/9n+wrQ4G6sqyywI9KWjcd2JcfHsnum22kxo4U49cmlsMSmtLIPh8nlfcs2ao9+OKCTtSi7cyHZdeTsgF7ghuh\/carXDrz5HSi9CIA3HcoTuW54EPT9Az7eB26OyM28S2rAg+NQsf8oimgGlQKes+xR7QYeNao782F4N7HUy0VQdg5xt\/Bx2ZSiBy6pDIqWO8V4G0aMGurVZUvE+21FAw62W8h+GuMX+MsBgFNe4UZ3BNdcOj+JG\/GyProdPmkvHmv9UY5\/NFn\/qNxtz7p8mbT57yaIRv56vko6xa0E46PGnVQxdsdptMuJHUisnSLX3dARSM86wUf1hMA+UgiR0F79uRyANh9n3NY4prZb06mDn5jPqKm606+cOnNsyQslvW0UzFMLm\/nPUnqXDDibby\/Wo6pPVL8i2WKgKe7DJuVXcjOCE12XA7Jhau+J6t0iuuRvnwk2X3WGbrOGLeRcwTUIuYdz3Oy3f40PsOR+V0UnarDODDTMGxP1Vt8GMuhwHm5TCAisZW9tMqueB8Mni\/7dV+\/L6hRvSvbxuk6Y2v42h7jaoKwS1i\/NGQ73a5+JxGDNrpqdE1z5Aw9oGcoaFuE7IJWRUJmbWC1KtHqWZbi9E7aNK237MZtR4aSUr\/bWPk8cK8PF4g8nhhXh4vTKhIfQs278BlunGPfzd3gJyR5PYBXxJ6\/A38evFmEYpk2zXrHmqFiGXddpuE2vFREJnLkqcf\/V6OxTXspMKF20fv22ytxlW5L46LLezD1rkcIeZcgtDVwDxdDUr\/l7fF0NUgX8oPWv5UFtwTFRwVkqkC1yzfoVB6OxwQVTN0Zafgwc68sdSHNPjzQ6JUxLEKnLeue7a9eAhUiPwlhm5h+6UCKefbnZglrXOQv6YQNb0WftR0IWOzyvLzQvrVYKXv2xFoUQ9qj6x72aPbwF\/Kk8PcgAIC7irnFGtbIK11h0baSzrW\/iiHOscmvNz8oJdHoxOehwYXXXVOQPl1kkU\/J\/rwSaLDpufaXSDspGdRufMdOmatlFXnHQaXp\/450eJpsNOVM\/3x43wg9vg4b48PotTx8M07B1E4u5dyQaURvnNU6ci8joeQo257r3gNoG++ZwYntR6es246vkonH7KHF4if+twAKSaGO2M1SDjBPb369blOtHpZ9vCSTD1cO7Wk9MTLZqzs5J46uaYSL10dUjs\/2YlT\/donGlNfg0HNWGnJxnIguOEwjxsO1M2q\/Z63+3Fkbj8CxHseot6LXYjkGmByaRm8P8bnGfsUxucnf3K8ro\/rQ\/d\/pxz3L0xj+iAYP3eZ+zkzf8A\/+cyGLN1W+HN3Wq15fT64RZ1U7N7cCcNa+7wO0wcZfAdk+HMj2bPiynOHwcm\/NWBIIBcHdFMvZckUgNWasIK9KqOQuCSly\/PnbN1JzPfYDZu0U2+OQtfazr7l9zKYfOcDRd73HrDkgx27\/W0X1zCQu67hveIJBcSDY3xHd3QAI9+M4AuAm\/\/ixItPU1Gk7MJ54ZI4XMzj4yL2mYY3Uw8PhW0pgqwa7husSiWw2lN2miuHilxsl+9c9J7tEzMWqf2sLsLPn\/KOZHxJh05hh4QMdTIcuumw1zStCwTIQ9zvDWh4WlTuzNGtZBj416xbL9bBvA91jpaaWNWRIYI6ZmWyPxs712mt8ntHRRHn8k9LZvvLS1NSpgIqdNS\/9io93YKC47LcrfGqA1i90zH3VGctXmppcrO3zcN9Lxc8fdkygvzWvcFGT0m4ZC6XGG1n7Npvp3Sjr6DLhLVgM4YRfWWxvFzkqQ2FsJbIn\/QhuFRdOo\/EFrIUMPizzDln70KK2PKfeSB59faIu9sgRuivuH9ott\/vzPAs4nQKgUcsvpbPl9DRK9dZ0uZ8LZ4p4xisJw9hacuHGuOr+ZjixFp\/63fJ\/PoKGfVVhCH\/j4zhTrBTiRaRc+7F1epmm36\/rsEr+jwzQYoU4B2xztfdMHvd7\/75q0nrwntTyx4L+My+N231a08cKAdtcmzbyN5WrIj2WxAsMgh0vaaoY22NMPpi+tOODTnAtz2Hd5FePzwKHZIP2VYPHjwyT0p+xwGLnZeEi3QvPLxRuOuSbT3Irchq3mQZjet8o\/rXT9HAx9j0pHdpH\/wkchK0X+3KFKmigcD3Xb9+xPQxeZRtW26IyT6lwvXjHlwqi3vhikdjyPemeNRdZNpRf54CMp\/UvwWUDwAjh9+v+5n\/UHAjdLKb79r+rxfc+\/lkTDak4y5tJb029nZwf2ZRNDV7fls8oSxpEc5Hnqst+8pYBqEhP0zhUXkDnDsroVbTlovG3HLPPn3uh13uezwTJTogqVDj\/mjuC5RYkBgQ\/T0RAu7dHc4+3word9wvMrzUwdD9AqH7ZXC08ZfVQR3qJBV2qD41BU8yaMXZl3HwtuC04\/kPQV1tWPJONhxlupk8TarBl8uN41044Fz8WvAbCXaUn+w8e6SXOWcguJnAqA+v+obeWVrZin7jAjPDN8lwYlvUXxNzGgayPU2o6+\/APQWHlsY7dEGU0D7jnDYqVgs+n7ifFIL7XT9x9XRVArmr1WOR+2U4lCoz\/ijgOUjlrjXR5ayF3B\/bCxPIryFJ7r6g84JC2HKgbJHsknYsfiguOWVWj4XfhgSz06kouZm7OMarE9Nrr34scyiF8c335Xkr6SivptTrakRGvgU56qKNRTDv+2LmA9dYv3UQ3kYGaSNxdbDswyTV0AwS72ucmMsxY9YtdgSX5+R\/+1kkcu0Y9w\/yzd0\/yDgvLIPOd9wQ6MLxGwaeUXcp+PDR4h53xXYkONGM\/Rpqz3Gi8cwcBw0JDhrum+OgIdld6LyBWCdui\/GgcGn04YunEpt+\/aqEVPGS4YLnFFR6+DDxsXod5g7stczr7obgQGpHOqUdz4pPX3r6px25\/aS57jhWoPvYjPBXSgMm0H6aTmsN4D0V0hur2feKVtuhcpnyTuTuydQ33NiHRoc+L07wqGfU+UxfBlHnw7w9BXPfF6Vm4nJicyP+OSPBuae9FS6J6uxgE+8DHqPgzMSjQ1g2xyfCZGJeMXXpOsd7gWE8YOiqSGdtQvm5\/F58Zen8ZGXFAF6WTGdraW\/EfPWzFUEnilFoI\/9f4WeDKEDsQSjE3OZP\/5CK0Ox1ZOxNGHMSrQ4vtz25A7jV9NDr7m2tKJN+4Gs+x23cpbYtu9W\/ljlnY5yD1uwv3mytrUEBbbVGKfYe8HyRdnDDDAWMO8R\/ityqQP5S9kX4vBvae9hUBVg6QcbjWZ\/C1wpUnPv7gTEXvS8f85d9pAw17meUF65vgNarZ7bIJg3AnUiRkpWjJPS279eN665j6kyI5xHmPY9QcfVIqPSrVpCUNbox\/riHqYdX7qWz221sgw3yxj95Vek4Pi6eOfKSDAb\/1Wcy55BWB89OTyTl4lV+dq620dm+sSL6Y\/qkFxSZNFWm1CYjS32aDHQkItdh\/uE\/fG8w6WWf67bHGehRUMLy2r4Nh\/YKdAQr1sG65\/wRj3zzMHGaUhB2kcTgN8E3HKtY1ZKHo09b03dy1kCU1uNqyfVDUDyzRGDZbUSjEN7lUo\/LwRPGFxW+G4Jj8hk7F+QW4+pKO6nO8nKQqeYarLgyBArCysFHX2RBmnj6dIXnVwjQX8r5LYQOE6Js6vFP+9AASgIXxbYj38Is2fL0Wszec\/\/4HcUerL9Ap8diO77149Y021yD5O3LfrqGt2Lsluqft7bR0WBszGH6HAX2\/PslZXs8B2MucS4sOt+EG1hS145ENsM9NfUm1exStLNu2Vxa3oA1XU30EoNmWKxwuOquaQ3WJ\/7bZ+DaAkpjrO79SdnQN77Nj1+wGvjcc48fru0Hw6Oe7CtqWtGE4D8SXBJmDuS1IoOrT1i6mBxwRs7zJ9HqmJjHXcAxcjNG0qsXRh7m\/yzBGqxVNO2Z7iNDbNF6VkNDCnhQRdfTWxowNEpfOepAKPzMSzb7Oftc9PRvR4pbE3Ka2k5NzcyeX+F3bN\/PUKFnjh+HPM+a9uwfb4MYxeyRJwJ0kDev9lHtJOOa1Zdlz\/O9h3Of9MSTpYZwRf6vxa3suSDx88qI2jI6EH5YYPAQb\/04uUDqUAbKifulb0hoQhVFltWl9AKY2Ri\/N\/JSNxC5RkD41EDDv+KxqhwNLl9bryG3uwfk92RYX1POBT3Wo6Vb1ajA\/+BZX+CBbhD0H3R3G6iFCLK04y8WMsiuLyzgjaPB5rfavNq0WtjmeFbo3pFGrDO2DDjh9AGTjJO2T24uQ4FqB+\/qvCYUjfyyVejfGxzhPnPwa0M2bkuykem5U4k3Pb1PyNe\/B99j+pvuz97fQRvvfrOrKsUweyH9z6KRuOv9cFURWy7+U5LCwWYSrPgkKto71A9yBE9QPv9aCnd1FcTO6atBnNBdKwq+Eku+Xg1cx2r0b1D6wNTBMFbnVRvM4\/wynms8+l3jV2kQCWsnTnfcOBQDp4IiH5G+96MeRypwVpUg9+mSxH0\/QqFS9N7gC9l+zP\/ryR96Jhab1DeLSDk2g3Ez\/0fn22\/x7WeDrpHfn3FX7uHbmZWtENtd6mcakIvHduxi4eCtwX20GF5J7QLYtn\/PLREJH9CNXCB+5fAgHr+XsNquuJ2hi8CokTj5H+J5yMVn0FS\/vga\/rVUNmeGk4raVD8J25RfgI\/PR75kHKjBf5d8C\/QV0PMO538VrdwYaUNRkrxwqQOcH74Us6+i4yyD2oWtOPoZe+N1g1pmCtOxujOmhoH+jjfGp8Dy0GloekpPtCB2ra\/JDBWnY7rRC4\/nTGszZ0GRlohOL6wXTrr74WIfCG\/Syr4rU4+rahCO5zskw6WDsJJrwFRPecW3dcLcetQs2myuHPwHBjrDj8YNV6Ch36lzuKAlY7oVuC0oqAJ2+dQIPl9Vid\/YGHdYiEoiuYBtv4S2A+vadTw5wDMJ0KL\/0ped1TL0rw\/fhX7eqQ3ltLRiR15rKjqVACq9iur3OENx6G3rPjT8aE6qO7r7hQwU512kvXYVOhp8dCT87En52EKUZZq+4XgqPzIubbR0rQe1L6ybyFjoe2y\/Bl7G5CFYmiuXvdqxEJXQ5dESdjIEZt\/emXU2BtrQ9G6MXFWDsTrFI54gOHCvpFFeuyoRPXslHfNlIWASbzfa1tePS1w1C7W8LkXu9uEjxqg+gY97L6WNRCAvLKZUh1iRkv74k5ubrEKBFS7wcbckFkZKuiDKpRnxmuj64p6IV+eptthzdnYKBmym7xfnIuP\/z6jrv7Umo+sA3X6A\/FeIaj3JR9wWgHP9jSbv2r\/BOWXND6qtEEH4c+bS6jfT\/uG+E7yYpsb3\/3Wg5bGG1C63TDGHmyej29l1pD6wCXbH+ZqPj1uhi2KlK6R8CXf+X78f1qnHmYPPSN3+L8YX9wWXH2MvA1tAWq1V6UW2xV1mhXAfO9E598eVsBLPnpwxnrtXA4207VQSoXyChNvW97c0yDEsmCdIE6uDqwEIWh80eoJvTJZs1lgc2uoWUSfYS6FhA7i\/NJMOBAt6NM29L4UWtrEHz7L+L7iSb06kUePg73KFlTwFU+OlI79xbjt\/XfBxw0aOBh7n0YK9aLUz+ujRySLkfGPxNEyKHs7TaWXFveAPIyQlFGxbkY8B+fdgjOlv\/Nae9tkq3hdjJSf4Rm0pQPbj0iMODNEy8c9\/pGi8JFL6Mpfhp58FKj+QnSrc\/4OMk9qUVs\/WrWIHfkSr2YKSc+moqUlwNZtovelbM1rtGH8sv9exMRItHKQVXWNugj\/CLWc75xTCY8Itd8LnlNJNfAEf6Sq9F00tR6Hg+zdiCDAIDBTqq1E+Y8MpJhezcAN6trfwr2\/pQ6PUygV6Dh2gvRK6j29TCCN+atetI\/WiefFDeKISMUYWvDm1Uf42m9xy4sh3JeN7KcO2h8zW4JeUtl2RVMwT\/Ta1\/t4uKGOjkLsXWgiYxW3ZMcDZAWc+4567hHrzHFrP6mGccpmo9WnM2vQ4qRFi\/r4IeNM9vW5oUG4cb0qvG1t+tA8JHhhf0ef8JFEehXV0Fp09BI5g2y9BYK4axOX5LB9UlAkN0B56vV2lg5twaC9C3d42kY\/06AX2N1fXAJ3+RfSt19ucLOQxYc4swkuAWMX4PkVuI83ILMUx6xsDcOxlHlkYsTLnSBNp8\/Hv8FQfx8uNvd5\/HpWLZHD+d+XkOzh0GNdZ56C9iYeZAbwWGf4o0EzFqviYXLQl+H+P\/pRJY4a4jSYEDPKMWjssr8MbS41Jnz5Pn6+0ZXAyoGNR5cjycisKEj4PIb8GpW\/T42PEEhp6NOT93sXlxClI+A7cQj8kUCx35bC\/LTH7rRu1ltr7J6X4wUO6icESbgiuytvc7cfXhLaFbEwIs4XCsnYVXeJTKzIm9861+ifPxGBBQPnbl6V46c27P9vLtxDXBCHje+Uy\/N4eKHAEB\/pa8vaiYmbn0r2UJNO6OiyZtnO3fzLtcK7\/0YKHpvl8Ox9sYXB6GXwCFH3M7sV\/pZORoMfwF2D2oVsa2oxVqaV25HoGdoOT5YINRWje+e3mx1fx1KdLV367fbtqFSa7rFofez0Xl1HVc72urkZ6rYuP8m4xPSOZxJVw5+MKUpvM4uACrtCpnTuhQ0P7Svah1mam4rFPyyMakMkx7MrWmflUnZtclf8pMikWpcz73RK4mYkGnq97N78mz788VQ7VFxfCkjdc7khSLkvzb6I9sX+PQR5X1x2vKwNrMxfS8RBWSXEYDM45kYY5AUItSAgk6E5OOtMnRcNuDuLIcfjIWxxtyvmCrxoHRrOfJNVl4QEk65uokGfekqlh0xdXgtd\/CyuyGDTge++OhT24jrFbbc30zdMOGd4n8E9L+kPX1iu4V53bUHFKDJIMaJPI8YV6eJx64tFp7aKgHw9k3WRY6U3Fs7MbU8osR+O35yh4xThJKt+Z9bFwUjvaHHrjnK1YjW\/D38PytZXhBz58HRaORbYzy48KTOjxl2XJwrXoJ9n6nqe5MLoI2o4Tge9Q8PLVCJ1HzXg1qKnAO\/03Lg6BrH\/xGF8\/+3luashpdtfgtZDHX4w8FsLH+0fe3g+WY8tL9iM+3bji\/TXZKgtwKYQuPLbNJroGUq3HiWwtbgG9\/0WSaTw0Y9lMaDEoaIEI9Y9MTcRpor6T9qEhvgx2Ruy3zPAuR4C8AwV9Agr+A8qpvnljfKIaymkfm77cXwd4T6mxvJJKw9mK2Ap3XH7kfrFvKd7cNPperBlisI2F292SiWUQn2Jxxu2v9iYobVi1NlHkZBgWSX6f+mJHA\/kzz3jMfRoDRv1+Z22cBsc+C6Ll9FiQbd6rqujZAiVO8dvJsP3mB++2lV1b5sGTfL8np6dnzku+F18YrUSBye831Hwal6NL12myP7Uesf2Z3afRIPXgL2V1pTavBkZM3rrWHJuJB6YjjHNGN8OtXgXZ+RTn2PKs+ftmiCI3+tLnFeQXiTuH3r4O5qrA60+qJnmckxHh8OrnybiNwdj5f9009C\/cUK+8Y57TBvC\/H\/0QdbYHNVdRfvc+Ssa2l6vWarbl4rd3pZvWbWhCpcXi6JLAAbeNyvy9akQwXrm5JVdlFAn5dm94vZSMY\/KJJJyX2K\/z5dtv2x2g7PCG4Wobvp740K5CYOaIMDiDBU2bmzBO+P5QsbJdZnJgPjHqS2C\/jAMdL3p+XyDAh5ung\/p0GnUu0H7ArpqDbWrLoC\/9izPF\/XL0htQkam5ab2r+oAvqrx61cI+VY8dKq1v5RPURyF75y6iSBRNoN1VVO3bgvburyU65a1HzI3m1U04aXbT24THYNoGLD3fiZxQW4eF3iYk+RNoxJ4w8wPfUVhjK3dX8U6oc\/vrL\/tDZ0gIUVi8HuHRVweipW+Nz6PoDfy64tsuuCFSnbr7izVkDFNyOf3BPdwH17+P3Tv+2wZ86vjQx9qdicXxu82+0P9BQmQA3vd68v99+haPnGsJVvy2HIpEPUT88LuBSt3dfcf4Gn\/m26uJOvGvy3vdUWTG1h5FqDxFzOFZRmfbtveN4ReA70+Aw79YCM0J7vduE0uN5lqrdwUTyIG4X7HxnswbXEuZD\/taA7xjiQwY9j5tk2v40r5cmafZ+rrVgYOkEDmRcHTN7v64GsItVKL9+PuD6e30whiAovX67KPfaSClEFeVfCLMLRbOvKgnuLXSFFSMqpf38ZTHZ3WfkmJAPLuSVxdmVvMONN7\/0QgwKwj7Dnyd1VDY8eWj5cdfw8tvAfP7Qluwca77M+VjnmDkGB2fw6t5rgwiqZu6OHByFlLjd49v77v7nBzFwyF69+RzdaD+y5doHj951KCD+WHKSwLw\/clp53+ZXQArqKzvcDO2bLiZd+PQmH+ubPE5AxT8hP1hJSdhzCbbQ1l6vlGxi5DZB05+wbX+NB\/EDkntElpTIjbLvg+4uTId5e\/ci3ZuhFmE0u3Pj71VJU\/f90debhUL5RH7clZY0WRIuSkiSV9o4lUgkVKiGUUlEqJMmWLUVFRZIkIcmenWPfl5mxzNjHzGAsSZKlVK\/3bcZ7\/frTdY3neuZ6nrnv7zn3+X6+HWCwRHEoxWoQqdlNvGkWhXC87Wzv8tcUkDpiq5txbniOk8Y6f4eOTfZUA3o\/5t3xuhfHWQxsDrmozepYv3d9WCDU5D7\/CELCk1pqkCMNfis9JCwnMtBfXqA5bFc5WMWseb+Imwp15BV6inq9qEre6Lc3uwCyPod\/3\/OZDqFkB7+iVTkgemCjiV9NF\/h3uppwadMgYMHO4t2jXfhx8Ozt4IE2GDpPNHyyLwuq4ze8ERbtw5Fvrid2b6+GeOZJp0liERh\/3+PCuD6ELVHfvymNkyDq2ta4oZelc\/df8Pf+5zjqoX07XOUFO\/Cmy6klO\/dVQdeNmMsL17Whk2VqQCBS0EAzK7RbjgBCnxQ1nW9QkHcHn9Lgkc+YzurzsLkZZlcYN3mzhpG9zrD7nzV9a0V4IwZxTLRtU3B3A4wKknY4\/m5COZKMt0DmAAa7u7rdlyNBU+GYfocCGYf\/nhMhOwecPf+zw9Wp44R1H0b9Ksn1aq4BB54G8NWgYSjx47rQgwx0mvppbbuxHqqDppf7qNegrwxz8NrdQqiXS23g4s+DlsvBPx9oD8KIN5KPpfThpYU\/ApQeRqISKXzrj62NqEzk+Ho5qh0vTAo+iH1GgeDpfb9emt6GGmVr51JfArC4nXO8AsLp6MLMRTXAyhNHNuf2uP1J52MV9RD6Nm84sG8I03+9mmS2VeI6BeLeAtlG6HqfVsd56zOyz1u90p66RXGSIGH7mhpPtSE0EXZySm2oxRmr+oefiaUQUjvQdqZuBOt87N4ExVXjlHFR4kGDSsgJNDv50HwYd2TX2axeUoYSDzx+2K7vR3ntk6Vk70Lc8fVhAPNhA0qNHRZXti2E0Uch0yNPC8Fmif+zDvM+cBfluOKUxcBkEZ6J6qkyzKg1IVe3EdH3cErRd2cqdPAObOXT7Z3jqrXSfq+rEO0Gl1WefW+fM+bO5QkiNfOp5zuA+jf\/Gtl5mtspHNxyH4rg2tZhtbLGTHwah5fvvi+F1EMbkte8KgMDBom8\/m4ZXs\/VElckF8C8+9GdNOVC8G8OvmVbWoG0DZWamrN1+RLJWwkS66moeb\/+rSx3D3qlb1s2\/3gD6idKfNPkoCGHQJiJ\/sNZfbz5l4A+Lwm1vl+zrnLLQ4F2TvpBziqMTTJW0TgcC5eVtBTF3jBQWbtS2vMaDTsdWpYIhBHZ3DlkceeQnQPF+7IybEchc3Z94Ohqmkdl5wPCsOs+GyvTAWTxmVG5XlE0\/nkljLxRUNnr1I9am3YsO5BKxQPb78sP7K2GlW82W0Q392H1tSQth852nCptHvU+Ugb5us+sSgzp+H36\/kiXZw8WPo5WcWbUgJ8I9Ytwaj+2qXg+Vt3Rw84fhN8tQYvjdvXhfq6gzeHPulG8d4XyVX4ymA0n2FXGzNYxXJNST6be4ci66MC+xnjI3rJfOr6pEN4O2hcQCwYxy9OFVzOMjBqefMV0vjJ4GZXWN312BNn9HyKRMZy2MR\/yAwyPTbaOoBUr\/1HUXp2qVJUFhRa7P2g9GMb7cu\/8QjJr8fyJzD1R5GKIcAxVPbRoGLkzcu4n7Segtughq\/feyVBviyUSpwbxamzdovXEYjTXjjedOV0ORTsF829HD6BdBKnr80A1ynMPhS1zQiw\/ESCS8HsY167\/dHOfWBWbR4H\/8CiA5cvD+P\/68mD3\/+VVvQP5BK0tymdeg\/vE16r0gS+g6vMo29okBnhyDP9cGQgCikWAhrzHZzCqkxHLic9AeZaPmOU3BJmYyhWvBIvBPEWayT9xDtO+lHNf+VEJZD5pxzPuRLyjaVQ645MJBeO8+10+d8HTjBiyPH8vaH84tefYyV5Y6T0iQPuQD6\/7s1tT19Bgb9CGrhWbGRD4Yql8y+5ckBxvWpTKw4C6adrtzAg6KI\/Wq9o5pQPP8uWt\/JME3FZ8qL\/pQh8GNr2KPHWyB0hKVTf1Arvn\/NRs\/mEbhSN4AaMDfilKw+NBBhbzLjQuTu0E2Q928Tr76sD6645Gv8BGqCmMf3PUpRZD\/qtD2LxNmDwjNJYj3zKXrzHUcXV+jhIT9tUwXjvWUiDcqbei+kg3xlyfsbq3vQ9Y837wz7wf0N7Fask\/JqCI0ff95isvoUSC1PyD8qW4StD2mft+5lz\/pJfVf2bllUDwf\/NKgMCrmfjgYTOwOXgsDiqwuGfA4p6BOaufLKD+8+y6uM+gMu48vVGQDKzcN0gt5x4hZZZDWNAETUqtHG5883LiHurC2s77KgpJNDAK9L7o1joA51m5mbxWywvuEcrAXHq1y6dbjzEQFdcYbGtBgTD\/7ti6CtgllHtKuL0C21oUxXI7iez5TJhmzUOyz7+E1xioEs\/QwXiexr6vCaVgzTFh7\/ymFw6YX7kW4NUKfVMv3ATWdcC428mtN37QMb6vRNEohAKEfDOF3gudYLDGt2HvZA8S91Qrn05qRRt6eWfYYjKKjGzz1ddNR7\/WCQm5kkaYWL92cXZxBMSaq\/y221UNbfmbKlY6V4DNZvnft1WoYH7DIqdVuR9ubOqyMNnxEZlO5Gff+fNht3fn7wVyFahhnxtvuu4N8jvU8XxfWwU+x41LdxsVo3V8zy9yIBM9OtalS8vk4WPBhrQH16rQWKcreHl5KoqcXebBGKyDoZR8DvXVTdiU\/GtlcHUP3Nloa7bevGOOd7r6v5xqtn8fZZqkDfbINeFB\/5HzppffwZ+cn5ter6WC0l\/+LbL4t8B+7j5Rp7m12sogVfrRJqnoZOjaIiJpW02CtVWReUegCq5OD03eW38fSOod1OfJBGj47\/szd53CR2vMm0uIYLU94fDwrM478dK0LWkfE56KW8hLLOoEihd16XO1Sthrcs\/0vCwV3a9LCRu8b4fMJ7vcLzJrILG9LkjbhvZv3YTsuims1ybRSpIO1RUWhqrXq5CSO2qVqk5FsqBZaHoYEYRblzf+Ci4GmY\/MLpmlw3hd4G5y3SEC7DftvGlKaoATpgd1C72HUL+pXO1aWQOslpczfBNKmOtf3TXnFTqAlXAgUdP34\/kKoIx2bnAQZGLY2JGzqdb1kFW6n7ZxcxWsYV0\/SzvUYVNyI3zI\/7xun2w7Lt3aztQ614ul1IsGYg69wNLPaMnyN1Xal\/pyrmRAjp5aCj2uGdl8VPt7lhfUTFuggMeb+lWMMecXGLmvG7s\/YHZfevxkZbAgY24udMOC1NMW7RQwdsytqfebXadXX0ng9aKjiPrAjbcPEDqVtks+ZvTBTI7hVm65YphsTFqiuoEGkd9X3ZCcreNmFZ2KzZUePKZXmHqaPxGD9Bc0KYf3QrKuJe31OB3HFxOEXmiUg9FRzQPn4ulgf39Jh05UHTwmdZ3PGAgFv8GavX9m66jkXcFOKScIcPh76p26twVww0NMlBTPAN\/pjfsnbiME8tjAfKtS2KIv5pdxjw5epffKV8qUQVBantrxyWxY400M+fCABvoJkR6TryqAoE5p7f7cholL1n3SkByay+mWUblTST5CQ\/eWaHW8X4T8b7d9yvbsRXb+dcXf\/Gtk51+zuBbI4o3M8du3j+fv0vBk4Lwodbs8xyJUKxa+fdyZjupED6PdHHQc7Fq9vkv2Me5PbDu6Kb4Tt5aMZh+d7EVlZbfiPXlRoLK+M0njcDeaFS\/fk3phVtd5ZNS+\/HoF11PMpTbO6hFOj+TyPco14Gk5GrLyzTB47tizvkaiHlr+mwswt7+wOBvI4mwg6\/vi6rsx1AdHBnHb3xxDZOXWoQ+MKR4o7UehsivfAiPIGDnJafxxVk\/Lf1z94XXUMN5Ur8m6aFcIeyuDVbZl1SLX3ewLuv0VOF4V1crZ1IFfIkVLXs2uo2Fcq9ZyqbXMzZ+w30+\/vxx1\/IejjlrTH+qEThMhidZZGyNXhxSzA3z247O64SPJYUt8F1peu1vsRSiHscST+TqnKyDylpiFS0IjsOYN2OsDsnyUwPJRznEv90jeWSshXgpG1wUvPoilgnN058HLyQw0ctn8JpNaDWUWDy5anugGZd329ZcuMDGPxp+1JJEEtQkJ1ZabW8H4rkJK+NYB3EUY1KzJoYJl3acrKypbQHShyQKzwSJ2Xgb8k5cBYju550c8YEL62J201Ho6dLN8jjr33Fc+kesD6yOSDXGLGdD2jsAbQi8G3V8SNi952oHRSvXfHtABFZFf8PutXPR8UzktXdwFMUw9T9HLFNALY8Z8VUxEFocTWBzOOV8Dy+8JrX\/9nmzeL3Jsz0im\/2mE3aK\/XIXah8DYjvBWuC7r3zmQuX3QuemiXpVKIxqpTJzoUCRjOTF3QV\/MAIQwS7gNLMj4VJE3Fre3YVzKK2EvYSZ4F78ZeUOuwZ1mz384Hqag1yuBqY\/H6eDs7nu8yIEJoi+V+y0aq+fmH7zzb5HIuX3AED5vJT1ShRY6ckWB33rg2EKuvcKznxfoztaYv7B0jgdocnAsV3b2810nhoqK15bgCY0Z4QV3aPBFuSB2ZVoPUH1a72mfKkRb4fD3vHqMOd\/WP35wyCu9xP+ksxdoB0vb7e8U4Pg+DT2pZDoMZeXPK75DR4XsmEfuB\/vn\/HGZIWv2Oqr3YCg5NeH8p15YqhtAdU1txirD3uy6ThrK\/O3zsHlTmGyS3edkz8AVS1zb+XoZkPpeczBGLg+r1Xz2C7vT8dM+gw29wz3g2CSm+vjpJ2Dxe5HN72XnEZuuT1i8\/HktGB95R7iulgWXdRrdl8QSwPrsKrERz0I4UpZXeaizCjTqvkz+UayBqAfjhamZDFTaZPme0UmFhs50nmaTYrxa4sj8pjcAbdn0H6XWjXCBasovo0YBTk4LneNVTPjzd\/2HONb8f+RglbBPVB\/wEb9l5XrSIWWma5XJxUeouNrWcNdbGjyXij\/YU0aDQ69kuQXNC8GoIMhofh4d4s0+uKi5tcLikQdB3pdTISpofcu9PgYErQ2Mfje\/A3afU5Piu5QLu\/vKHK+VD7K58ZDHytFe\/3NUsa+RCfxfJmZW\/uoGUtsxPsL4Y0hXuVS4Ondw7jyC1ddFkb21GW1J7WC\/dOrGwOzzy6iLDox3zEetF48cgj+0IoXyMdODRsepglf6qpk9+PDkqoMff8w+r\/V3tnGt7MDc9OGDuk97cOlphpaXXQlY7jv2cvAJGRP92pg+ju3op\/pV3NC2DmYubuOcVWco+Dw9zU27A1WOFHxc5VGBjhdIie\/\/9EBl+JBzfH099DskHJG4WYg1DW89nf6Xi65i\/XGxQD1InZ\/RPJjsjqtevS2QnSZDhG1E\/I3pErwXYfVpoVsK2lF7frge6ABn7m7TQdUq9Kp1iEyw68Td1fd1LyzsAu2bxbdUr7XBKNfW1a\/M2tCS\/qk2wK8FRHYekJJ+Xw\/G1\/XyRaKzQeNLbaoWdRC\/PXKJ2BtGAaXYb4d5Z8qQ1Oq6XLiWjr\/Sxwx5s8pB8VaJjMeZKFhFCDvHt\/su+jMuybQcZsBgd++ZpxVEVF30TYq4QB8PkW5EnJaiAk9CupD5aAn6HHYk3UhtAzcR7cXP7lHQWmsgVL+wE26sjdoi9aABksUlEq+at0DRs\/54LBtABlmw1UCpAwQpxJuhO0pgxL5v+x9XJu7loX63DOyCEUND\/VNCdZD2UfO8rWonZFQ0LhRUJoKRTcxOkZ3PUCb2U5O\/GhVcU5a9zedrhtHqZ2InngbjXUnrOGeuDtDxMPc\/dKIQGEvuJC\/6kInjrWdGdF8PwKmd19pXtEYhR8DAVcmQLkz\/bbK3yasf+Oz83IaS8qHvQANX7c12XOV\/LcwuZHCOP8PmSrHmqOGfOWp8ZyrxvsGf+f\/XT9QaH1nYgwc0fMWPaPaDT9qiJHOHKEzVUWgWf0XDpSfJvqL0PjavlZ1HDE80qyWXLpvdf4L\/LK7tokKxnP\/x9dxkOJ8wlCRaMYDhlmXrBiTa4HKpbO1ERBWycsHwn1wwlLB7\/vB90hCy+\/\/1rP6SoNXSQ1+LPoMTTeqi7FgqCrxIK3zEVQ5mOyLVDB8PwgvxzjBGRS5SjD4yr5CJMCotCEoebcAUvb3iglgFxIev4tkm1AZxrxxWntShQHa6pJmyUA10Nb60SZrd937Ttx0pvjmrD3+4Wyf1zuovewGb1geNIK2hFEdN7gdq9q7Uffd74OjY92E\/j1Q812b1UK5kADauzOB+n0mDlyxOuFHZ2quPmENAUnnsfc+8CQoELeUXMd9CxhMG+dvr2fdBqOweNwcdGg4M3zmzIwaZzY9N9kgwkM3B4+t\/WxqQQcWuwyYq6lNUZIyVHX5ynIrO+s+Vbzl0omRR3eu7r2shKNY7+dShLtRQvjPJQyWh2bg5T919MvAyPuQrWNDQdqr34PwrTRi+IvdevyoFeILVChP7qZh+2ifUz7AVc6T2ulyuboaNW3ruXj9Lw+hEn8VfChtw\/G9OLrJycpGVkwsJ083rCQ001OFZlPgotwf3K2Tef9g4q1\/4vC\/vTu3DSN+go7\/W0JAr\/Nz27s2lcJvFf1j6X90CkTldby1CGjFSmzc5ZPZ3NrqZ23k9oR\/EJytT0iTb8KAqD5DmtcDEQl2Bg2a98PqcGI\/MaBcepeuW\/XxUB5XvEpJ\/z9bt1bxjJ1\/L0qBRyfyU8vkCWBVz0euFQT9ySkV25nLRYVxU+JHtq1Ac9Ei0\/zL2vz5tr+k3GgXA\/TyxLSeGhC6pXlsVhVvRfmvkK\/qZewiU2xm7tbOx2bvb+ZBXE6puaCkJb7yOjhMRf7Qnu8BINWh+0qlaHGZGnPP2jYHDYkoG8\/lpMPXk\/EpqfxkuGRf8EhFWg7Upw23TqbPrUPwPynp+Kj6QDfyxxrQSUw87WHC\/TAOpyCsUW5sO1D6kFSJ3ohA1K0yjxVeXgmK5meB4UT0qFJ1OMmgoxrIVpg5fbmUAx43DEfZ+taiQGiK8dqoAeeXUyj\/KlkDvvdSvi4vLMM7pycLjPmnIXFA03beUCpvbCSfDpwuR\/3XbD85fORjVtmXbVF4FFqyMHPv4koYUuZ\/R9sIdeJzYvODiphp0Wn19ZqbmClzavjUklYOBUfZjnWdPd6MR80nWT+28f\/Ob2POZaLe1WOZjTwEOr2tM9aMU4YR1lde3A6VQNSP1PO9dD4blemgc2d+NJP7n7vqC+XjSwyCrpK8CtnUkmHdZ2uFpusV3J4kq8GVOdL+WJcCygI5DZjlEkG6jVKwIp6PNzOi7YcEKFLMSOHk0sQCWcipQvvpRsdK76GHALiLEHXduP7wzA87FLMju\/JaOYSbzg16vSUa+SRnh3x7FmF6re8rgdjUorzTKISm2YMLO6\/VOSqXodVW2eUR+CM18bkuKvW5EkZQ\/dy6EJWOt+PJlYkuGsfPw\/UufEqj4pk90\/e8VyWhddZX\/YSYTdQzQ8VBbOxYUphx9WRmJbo0RJU96+7FklYXmtdOF6NLyYnRUtxWYsGdBvt8g2nlfqEmeqoe9hiMRKbvTkG6xLNF7IgR\/bP9JaniVgx1u0CVaWA\/Owe2ktV+r8KLhb+PtRQUoWlyrLiyRC0ueV3FJl1Gw0uP2UIJGH2qT3F4yiBR0vhvOeKdVjszn4l2H\/vRj3Hw5EJ3fjfUR1TJWRkTkuXvE+\/EGBgaTnMLul1OQeT9A1SmgBjeycirZ\/Ul2TiVtZKO2rMUwZAy9C909XoMziZrNVRmI6Z+tGt7y9sEtyrSA2zSd3X\/GwLNi34K39YLOiXHJLHMaNoU2HVC53ogf95J3VfTXYx5n0ovvv4txVdeOZvG0BjD5VLjmglA8zmwc4HihXgWWrXzuiWEpENoIbRzvUzGUy+3n8P0q8JHwFdHRjEV3q0CJgjwbdFSP6TbJewM+DQI\/rQvL8HaWt\/AaGyIUvo+duGPfCg5VdpRbye0QEjOeFvGgAm4tO6fHeEsC827PYVfxIbCszBWyIGZCWiNBfml\/MhQ+czpyjdYNNdHpa38UJUJ0T7iGAKEIlmx2Dlkb3AlN1ZX8q+Ynw3nJF6VCT\/uQ9KJ0NTWcBottAlzlFmbgFrdeHCD0zeX\/rv48vO32lxRUrxUmK9n2Yrmh12bCBB08Px2WcbaJR79NMtHvjHpxRdVlC+3pLoBPbd8X385HI3\/GM4e7NMxx2fUsZ5oG59S\/5UXofYK2u3G2a+178cZTfotvRDoE6jXKHAj0xwc0rYwGlR6UKtWcFNTqAhnDlC+62A5WKvxn1KMLMc8qv95afHBWl6lXVvAPocrDo0Xq14kwdowo4nOGCE7O\/dkJRbP1PpqcD75YhMe36qe5mdPh6Z+Lp0p7i0C5Q1DvlFsKyJUFyX9QZ0LUqV1e\/QGfQHqP7DKfhfnAxc3f9EeKCceaLx1Z+qIY9Sln9WWy6iH0lH7yCkY\/sPpC+E9fCErlHgqdeFeJT9cs6R\/3JYAdi1\/6D6+bPY8Ej42tdwwPViIhVbDTdwcRzN2uGF9uHIIm6rj1SmodbmuL5NnxuQY2Bxc6EcaGQOveT4i2ykehnvp5hpEE4KMmp498GYD8BQK5y\/gawEe2aaveZiJIaQ0c9OkchN01BX37mSXoJTux4KJKE\/SvXfY+7vYQ1AjeptNuZoH6tuARxrdaWLFnyUZRxWFwX5VutFyvHM\/\/Svu4X75nzp8V1E7meOIYglumDI\/7uHbBiY2ecotCBmC82u\/PD1USuNZNVKyupGHGdeMWbenZ+mFm5yWPE2Qs+eu7nzvfbGNxJpn\/9cuDOH90hB9vERpfLPqlUEdCkNeV8C5tAj3\/JwHaSpX4eFlBgTp\/M27Ki5pvFNcIWUvjSU9bidhVZzu++TEZfb7\/iouQbIFVV2\/5j9ALcfRQ\/I3NE2R8nicy5nK5CXj3y6rFWdZinnRsJim9GblsDtcEzGsCVt8M\/+mbwUSF9J2nb1qwJfxqQoA4HQezx20XN9BBWX+ehr1EM6o0XiqIeULFUt35iqavZ\/VR21deiZxW5Nug8imMi46iE\/NCFfppIHCz87reZTrMzGvniOBoAp1cI5F7nC3oqjSkI\/GnFzzfKdQdySGBUq1Tv41\/z+z\/W8\/7spwILRymOv1xLaBlP8ob85yEe4bPC5T2FMETLp2KxUebMV5j27l0vgFw0vJR9r\/XBI0bH0nuM6CgqoDHPE6tASARWj58li\/AJanLYUiKjMaSBScdZNJh+KOVCMdpXzDjv6D7QLkBz165seJQfjxILz0v2lRLg4iIF4\/se+mQmrajzCO8HFjcNmTPubHPp2RyJH8LKTXBjzrnK0bGHeBJvWzjtIkJFM7dixQqWuFJOU8qVa4UxZUd3NN\/dqH8PWH\/Befa4eOgnMWmvFqUMRXLeWFHxfCzLuF36T1gd0Y8bddMJep43TABYTpGaGysed\/aC5EEPVNvyTTUFM5Le9RKxZ26w8wzR\/OxLV+5ipLaDwY3j\/byaCGODKjZ5gUk4Z7Do+uGGmlglHZrh7HEJzRxUCDIPE9CyRbZN+b8TPj6\/kIw5+kU5FpyNTOIfA8t9wiHiS7uA3+iz85XdklozhiaJ+l3AGihHHxrf\/XDwePqW3akFiCdbzLi0Kc8XKogbGq4sxcyDp9N+VnXgWb\/5VMBuz\/WeJOy27EtBYVNLaylXzJn9c9J66MSVBTbgGca9hTg8xsJr3bzMMH69HNxyksq1qaKhFcaDaHl1M8fz5pqMDhxhZHH707cU5Hj\/kB+GC\/UbJmOt5\/VBTcWzo\/KbcdiqchAiTXtUHCS5319Mwku225od9r8CaNHcpX1bIbxcvOkSbdyNEaSJnW5xUjI0Cqo0ymoBkmRIZcc8gv0I9UXuW\/pwaB1KzgTW0kwoEyivuCsQwXGoEtSCBWVp8sT9i7ohRaPz2drKzKhVafNPsw1Dxf0MwzCrrWjr2dw7MtkhO2P7hj+OVQJG7ZKbPn2qwWi1lXK9WV0wSWZx8f0gvpQZPHwrkiBWqAwhc\/KepWBRdCULO+p2d+xu8uXXv0+UKv5Ibypo5dd70C51+Ql7hIG8AoU13\/PYYBGiMmxR79qoS5Wu1ppigHJJ0dtfZf3wmb3w9ts5peDQCOvpWguDTykuEX3X6eBqCzxJ\/FDDZuXAv\/wUuCAvaNi6fc2OFlBKBneSIEagtiGecezcfR+k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\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\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yvrQWsyOcZOaxWxFlvORhjO8FHY\/tOzpecXGcdN5jNCTHOz\/c+\/CslQaD8Lu5AVy0yhaERrKC6LPDcufS\/zhYN0hTwV\/Nwq39d64D1cSzrIq4J07g8YTUZNzt4hfHDx0WHoe8YvDJw7u0LNmQbHQOyMmh8L7o0reAkps2N0XVHlp2oAn9+I67hzi4GUQq2ugeRhcpu9sWJq1GPa7fZsu4WDr1s+Tb11HEdLw6whvcy3KAtyX2BBuaX5xQT6ZcEu60y6rz4RbuLTk7r7czsZdIetI3YX9OMG1IMKsqhJ3rp87J004\/sClUK35s0kOky042JVRC9nnGwX3b2DCRH6T9eELLNxS1\/PSIfMvOxhmrcrPhL1i4WojCxYWJ6rNziLzbyd6zdH4\/hAq5ZQvCfWOIOOFVeDwLwp9quWnQs+xcCNdZ6uSH5v0a5Lz7TAa22KuCCi3jyB7a5874zEDb7i\/y+9YQ2PA3kTgOTWC9cMvZcdeMdDB05ZmqUPjS9Ds9Mzobsg7vnvOVd6Pi9Pbtq87TWHevBv1jScG8CKHKeKwdBhXLml9\/lpOoT6\/arz9bRcqNK64MT368YAVu9uU8O6oekpASE4vpE1qEjInBhAXHb7LJJKCYtU+9mGi58qj9ekriJ7HysRoNRM9t9CpHPqh1A7f6V3v0od64SzQzpu3k\/hIQEWxeCwTjFfl39y21yC90Ox2YEkxvHl+pkQ8YkKu9oF\/XFQNPhzyVVGq+2\/\/vftKOaN0LwvP2jbv6vzYjtK37h4i18vw61Zu34UKJpZ1+v+ceaweewW3\/bY9U4I8kzH\/DXlMJCTtOzKWX4fvAdzbNpj97\/Yt59N4cciOuw6HRJv5xR3bsC77nUz+TAqmciFSy57V46GVsd9hhQ7M39CQWShJ6tooaDbrbxNi37xxrdHpRuoN5v3ZKyjsT17IeKZBcmyF972AJA52Hn92aX9DMyy\/Frqs06Uh4Bo862UOB6URnzrd+ElOmhJnPiulMd+m\/5kN4dg7hf2DlEYv\/HXm+Doa09iyntF1lOTtn5l\/TrucbMGES\/fnXeU0kl0vOzAIX4kxP7y5PdyLOPUXIhxyPCA0J2gN0fmtKi9PRC3pQ17G2UnlHa0weLr\/RaJsL56L+GnVbiQ+y\/ALkZ7bCakDNQu3fOpD087L06l2FJq+b9qd2tEOG6lDqje0+9B\/4V15xl4K2lNeIq5pHciY\/+nWhvA+eDAi4r1sKGRUUg0u490o3WA3343qh4WC+tzCsxQColXrvu5oh6Lflw0fp3qxVHgqXXXX\/26\/uGfDzRPH3tfDiGfPkhurOiAn8eLRpjkUYj+tDPx9sxbR4u2fP462YlXDQM5xomNpc4Xfx+bVYqIupWRcvg3bBPWL+wg\/JN9PDp0IaUOMnN2yo0960TfPa0bvdpLfQjx9xV+2g\/68WICzoA+WrPceKywoHIXSoiMFXfii8SiE50Q\/zp\/t660g\/TU8\/0TTaqlOhJe1GhSQ8WTY7hZ+R8ZTUHl9DE9eLwJnfxTL\/j6A0MSFTn6k7wp\/bG2xfd6D+JQFmSm6A7B5dCJzMpD048ZnMX8Pj8It5cdJR1EmTigWL1u0mUZC2Bnz42aDuN7+62N7+zBCv\/QdWdpJYZZQ6+Wc8QHkGJi2uoYNY\/qFtdNYI4VUp+3KzVcG8TP4fOpmoRFMRsTsLuilsGZdduwuxV6kRhg4Gp0agOT62M7mEAqz\/0r79y4ZxDjHbIXNR8KHJrlHtdooOF6NEugwo3AnqtLzEeHQFFuj8YVpdbgWb+Xuc5mDVxE6T5Y5jKDg9e5Hwu61iPtWdn91JtHb38qWZ4UGcbhA\/cRqrWrsdsg+Nq7LgVW9ZG21xjD8Y\/m8GnpqcLf1TODbEBaKb\/4V7NzfBfuflqfCDcox7HtJXzSbjSe6B3qDlAaxOtRthothNSqfRJbK+VRBI96sbOJ3M9E\/WwmV7\/9dJ6c\/RtkUqpG+ZpkqPwxtQ2TsOtlJATK\/P5vrZz6owPFNfEm1vM1Q7WxTd\/rCwd6+ml513UpESIts693XjEfzA0wejnP+Z9wSJ\/b6sMpJJi5lCBwxty\/H5T\/VDz4vK8a9UzfW4xQT91y\/DS69WA7h4YiV0yuKofthw0N5PyaEmyvDpU9W4Eyv2Fwl0\/\/duql+If70swlM1AcHWqhL1+J6wsu9IwPFsMqaKcEhubKR+WVs9EgthsbeH\/w8VYzPt7v2\/PudVHal5zuNU7VgHrx80OJXMepe9oYIZBL9P7Q2TkClDgOtzuHKi0uQWC8pKaHBwqPTT2TcrrRihe82Sbc\/pdDZ8\/P13y4WPqqt8s7T6kXmcG9X5KEKtPZ6mGU8ZGGh3\/1Zj5Z1o8J7n8qO0HKcoRYIf9zGQszmI\/vieNrxOYRncsimDP0ju\/QP1ZMc7TnnOTdXL7QMN1jXrqvAoU764XZ94t+vTqVl7mlDr5SVlIRGGSRvCrroEJ5XXG\/3aq5KJ2Zv9RuuJjx\/vO\/tl9ibFLxub\/FsGaEQJH2xmyqksCG\/tuVeBE3qxDlPh3Ds5fGzUheqWfgbYN56jfhwSrpru30LhTBb8dc7GKRPVk1rXf+ny\/mJjNuE61Ymhs\/mmmLiOFfW49nRNJwXp6pKJNKYWTfv56EgFooMNr34mkx46Vik2rvfRKdOnuswJpwo1uv90ZpwhEKH60uLL2xEZFk88VZvwnu1ivBrn2mMtU2G3CR8veOHfJn5QCcGWMtnHi2k8TDnzZMl4TTalO46JtEdUDyh\/tJ4msJ5E4vlHl\/ZGEhxnBGp1YSGdcxoc3Kd3Ny0YAlynX3fzefzZnRi2fYfsmU0hT+5a\/hNythY+SFZ\/kpD4\/9Mt62LilReclcgiOeNt+6bJsQ9HF6nTXGgaHxMoGh+Bd6JNXJc85uQzZX15jY5fu5sn6+qUAUU1QLPq75rAlfdLL9d5PivT1vq2ITPix1PtYiT\/LLmQ02b7R4GDvZ69c3MIrmldcqrO4PGeedQ6b2XGNijM8R7OYCGSpdl3p4HNLJMaIP3QhwMtVZX0y00DCZskwU\/ES5tqAzKTh9GenHO7IjHNFapas\/8S+Zx58sdSqxhJlTf9u81SaKgMpre8fsnGVdb+4bT0RSEejcZ3nlGoYe+y\/pK5u3g5wf7tt0lPrhZdM4OYw4ieAtEGEwOFsdufbCb5K4BsT8B\/\/7fSyTHNeDjawreXO7QXEsjvXp9cqIeGzZeq7hez+HAb2fvlwzi5zELo5NWgo0J7tRuORkOZBrWzVv7hEazxkWjF9tp+HGXzmk+SWPepfc1zEsceF\/fO8fzNuHTwUbOLnIeF7dLyJlxFnLKr9r4PKURH\/nn\/v0XNCQnMh6dT2Ri+B7fsQ9FNFqUr1mPk3zzdUFPW37oKPQNzOzWkvOeLDX7MZ1Cw3ixqBltTPTrmzD3IfI8\/4Vprce1auGzfdaUBuu\/dalpYl36I00WmNm6Y1ZxrUhfG8Sx4y1D5PhtPxGS4376C\/MYL6+BQUSaU1xhMfg1tlf5PWTiS\/UjeqNPDaKFVxZ+rywGb\/w3H62DLLxad2DmOyc29AtXxX6+SUPU+l5ciiETL3QFXq+\/zMLksxFPJuH2u3MbFnM1szD4if1gQxEblu4V7zXukb4Z\/ZnKdZSJ\/ls3hqISWNheuPdJsg+Nit\/DdqeWDWNnd1JSivkoyjuDvY2EaHy+WEOyTjV4R\/S+c9m14G9TuHTxDw7cfNavzFVvhCltpCmY0AlzCy0\/XUUKx59995XprYbFniIFzY8tWDDP02XHNAcuTvESvySaEX30wrmTW7ph1OTN\/ree3PBWRUhOSBOOJVS0ZNV0YcAxy0N\/GYWCb2MjbytrkRl3X\/z5sjYw26JoPX7C+bFMhQPKDOiaV0v3PmGi5OGetDX7SP5unNF8+MQQNN7EvEvOH4Er330P\/ikKV2ftCpjNGMXsbw9Lw4jPWHRNKJia06jt25XeajWEvXlUEOflCCyi1ok4TFCQXIbULc3lSN3vKzb4oAlXIz8fiyQcGnn9k9iB0Vr0Hbx+M3NLG6Rjoo\/yEE5+dv2JSvBUFfREj7X7G7Rgd6y6AxcZn\/jY5ZbDYXVY4rJpQfdUG9TKFIRqhcn7355WO5TUAIGeN7orl3fCfniqQ3g+yU03NzTsy65GZGdDcO+zFpjmHD5a\/IuDWQOibjyPObBT2ftWfzXhrYUaL38Q\/eLMKX88N4OJspOPL5\/pZEHmW3Tnfj8awye3LLk3m4m\/YbL5f2xZyBUNff3Ng4bqopWRZsvZyH52\/6eBIOGD46mvLEifh5C5Oxo1giUv\/MPKPRhgGF8tfLqCXL8vYGfdv\/8zKhyJ6rnFRu+n713pRF\/XuAX1fiM+kpCi4OOzqhOrt8skJ4yU4a+eTdBWklNSehNa7hfUodN0RYALySmmiiu+b89i4vQWHXsn3Tqs4UqI+768BBaXGmvPLGPhuNj+OdKLWpFROFtj2VAp3NRcclN6WXgZZxbL2tgLXUeNlGD3CvRIHB4qLWJBJe+P7v2bPXhzhKFQKFGBb4uPqAfrsbDc6erEUaE2DCfdNqlWKIM4d+VxSVc2rI8aG35I6sd1invs+Moq2A2ZNv2IZWGt4Jw8SeVubDm4wHPwRjkeRatHVeSw4MMTkyls1IMDr9UvzvteDj9F88g5TTS01hslcIi+lgagpunMEJKYsWv3kdzyPbTqiP4zGnLeZ6tU1FkoL92b3UHy7owz0m5zif4IJh0eGP\/Fguyo7fUVFTQMa9zTVmfTcDw2lmq\/ZhS8K4oeWO2gMXjXfasU6UORyrhZcwI5UOccSu7OJXptobssOJPGxnfVA61fRsFaPDyh+IwFSev4D\/oB3agNbNH4nFqOkz8PCtSuZGPBfbt8POvD25szsxJPVOKJWr+O\/h5SH2YqMZV32hHHqWraFVgGxxm504aTLHjalQZNxBNOj5+g7r6uQKK\/5sSQDws7rzzRYb\/vRNbF2UWDguUot7PdlPCbBdcmv6XHPvdiOOWUuGZlBcTGlrgvPcUCeKYPrn3UiTUz18\/Q5ynHqy7rcG2iR8eNWq9qbO5CnXrGwIa15Vjg89vBZjMbWDDfkmdGP1qaT74felOJjM9rFafJ\/DZF5Hm6h\/bASGR8nufsCtio+XpeM2MjaJXW+pLV\/Qg+z+Og3V4Ja4FTTx3fUxA\/\/TnuvACNBx4LrjSfoaArpLZ8YyuFt69lGgIUaVTWyXHfMyL57kuv\/L\/7crY5Z6b9uy+n0Me6+M3EBzWuNZd+CyE6n9Exw+URjZRXKmNnQ9mwPSw1coTwwQO3P6tvEf75kfHEYzKPhWtC6ckmxHdbpi4PfHxFw9291Pt5OgMNSmuDBhto6IRpbnV8S2P1mKH3ralBrFL5vOEEqRvZaa8WodfEr+zXtjmcZ8BqXj0s2mi0bysR5c2noTT\/7dSWrSNwuv5M\/t+6ONkWdb5\/6+L0Z60o1v4yDP7jYu\/HSb3ZKyctuEDqTee9nAnvIhbCFg9wRi+SvPVj6XIuMxZadbzvj3DXw6xKlLNnNoXFycn+iaEMHPVn+mWb1mHq9Wj61WYO0pck292PH8WmXX0\/L3EIzzbV3aix5uDROkHmTJKD\/sh88uRdUosZSYn66wrY0FlmYii7aRCP66utD9hUY0BH9RI\/Dwc8pmfb+W2GoB56K3qLZs1\/8k8phu8+TqjC4teVG1ylWmBrfTK2muSXNL6IxH3fK2Hnt09uX3YzaiNjeSwniL84H34edrQSTjzFkq7ezQjNadez\/crBxS8ntoXn12GhUMtufrV2RGwpa9AUoXC400HdLovkmuBegZWSzZDP82wsJbnGWK6oLGorB5\/XnE7JYXOgevpV8jXCIQmm0vFDcSworX73dug+Gx9CPSQWkPmOKV1z5vIwB5PektovjhBdVujrv0\/6VuTZn2UyJmxEPRTxfbCQA1oyb8KG1MVFiWIds5ccOHT6F2A9hZ9KF51Fimnseeb7R\/DgCGTOdx6d3MiAzN3bEZwlNKKLtiZWiQ6gudxmmU3LENT6ed7\/LaDAtlL4GXxmEJ9c9nGafg\/DPvVF+c0ewsHaHZ8GSJ79aFz+3ozk2RWPPh8uJHl2ak3F1vrMITQHsv0tJ0dgu3HPwL\/fY\/XSbE7dcm4DK6t56FtkL8osEV6zjcLuQB151tdWEMzcsdOxl+gAFbHEmAIzOTp6I4f48tXMy\/Z8PVhWqWgev4ZCTEn6JeO2FvTanP1aXdeDPmcFi8UbSL+Z8ulkX2uC2TcLoZ31XeDLfVm\/j\/h12uFG1HI345jGPIdda7uRHPlbZxnx91Pv4gWcVrFhMX1772ByH0LUJQSjT1UCi7+7zf3GQlq7V5zAvV4kfJwPk5cVmL6V4yN0hQ1u188+PboDSA2mnBfcr8LGHYf1Ms6yYdYlq7Bluh9x2yP4ozyq8PQBl+oY4fXYdG9T+cODmBmnmyTlUw1dpedvPilwcDfSeIhdNoSbB14k+l+vgemi4a5UkjMO+jboX73Bgpq4VcI2uXpUla8QmEl4wbB6n+m8ITbCW7q8b0s2wWrbl02qARzwVSTPkt0xgrrjRmX+h2ox007eyI3U06PGiObdP0Zx\/n7T3CzxOiiWcT8bIvx6MsmyuC9+CIpTG15Uutdgq31d+w\/Csy+d8w5HJJMcVPRj5asa4ouXZ1vMI3U0Y3tUhyDhzcDW3giVHCbm1Z44dsGZ6I\/8AaOoqzTG7VtO1VhwUJNvqrDpFo2RMym5M\/7tN65d4CS7mI1D8sr1osI0NnspLnMyovFs6uKiaJqD5fyT80Vm0ji3o3CVqwF5dEl0tp\/kYI\/CLAGFcSYGEqzsr4ixMRWjeujUJXLd8weSooJGsJ3nZcocOwbx\/Xfbi9RoUC+nG13tmRj0jXTbH8MC95mK0NBTJB+8Ftwb3MNAwvHf9+Zps9BQ4BLc5UrjmO\/DvtLoYWjne2Z0JY5iVR\/vBcO5NBIvifBuncHGQpXQw3kjbPjftr+ym+jaqj9ctva\/2DhR6\/ZieRoHasEe69SJjl4Jlk7aak9B2YvWEyimIKogGP1CnMaf79OOqTLDRC9PO4RvJr5oJWp7T+Df94wFq3WTCCfYSpl\/ecTGxYo272zS10\/VXkkyW5mQ0dpVeIz4MUPqwm+RQBpTY\/FK9DwmzomFtI0dYsGZT9\/2rifh5LcvUsHLQcDGH\/n6mRzMlnDo4SM+bLqrK1EvhMKbh0H8cnbkdZo4dm2C9Ti95+SiRn7S3xlKbXzSJL\/ky9rfDm7Cyf2XC8aJzj2q\/nlcfDED2o3NP7csqgNt55PCZUtBRsNZOJPwUXR8v\/hIUR0svu0oTWrhQNbR+7FAEtHnHBU7c7oWCzedLA5bzMH60CDHIfYQ+uYMretPqvm\/\/34U1tK9LZ6Jolov5l9mDSb\/Pla\/1FGMA2Pa\/o45JP\/Y6AReIOP+MjzH8rsMAzn0+uKthBPfPfxk2kvy4Pklm098YDGhdZWqvEu46KctZzkvyaOvrpyJXP1qCIHaLVv1m2nM11zqcuQDyRWTt1a4TQ3BNT5pj00NDe6SwbxXpM5vjMt+MxYegHqipSd7LQvjvEL7vyi24fbZFTeXKZdBpvj2EqvbTGxt7n4l2F+Fqbnh0zH3i3HzseWGFzFM6JZ1aZ9RrMHpu2dFlxQUozhW670YqZNF2vmfu4ooWPXVTwhL0HBrW5gV\/Y6FuxOfjlWksCH59FSe410aZj31J2pPUOAKvy9xr5ECn23G+gck\/9\/6+VSl8QELmU21m5Ki2LgRR334d3+2yT\/PX3b3NEAw7pLGHftOLLGZtztHjsKlqkJr3spWXFnBuD5zdy\/C3EYXDRiSfHu6g\/e5USPirRc\/yn3XiU59tZBfJB8dqgyPLR9rRco2hp\/joV6ULPm5VprocA21UK3OvBHrN3iedSvoBETmBe9TIvXOffKe8ONhPHKSyd6VMopMh0AjaSkaX44219t878Myp69WF74NQlaWPYcrhYKOMc\/Vrue9uOUa25I7NIBrmR\/4c4neOf20CWx\/1YFHKO\/YEdEHu9JvUZdtKCz30lu8cgMbczjiOkGkbne81NMWJNzKV2fZq2hOwVnHl\/8X4SzJpUWS\/EQHFrvdUH34kw1lfcOasFQOJLLWv5Ul9eJXcSskq5GDJauiG33Jddef0lcZLaPRoRmom7aWwmsDk+jfzyl83RH0xZzkL+77YvJTfwi3X5nlMUr09vnXaElZogOz1A8aJ28ZhJv\/pe8HmoZREbRvNK6D+Pt73duxjaOQ7nyReMeJCSnr36qbzWiYi0elDpoSnWEkr7U5OooHPcujqkRojMoNtt28xIRb9dhH4bWVMJTGuTKnYjTUXi3IDWYixPrmhPGDStxaoeLC7\/3f+d336GKLBY1M5A\/vu\/L2az1+jUaKe9wvQfmvI0EmJEf7V7404HiW4WjJgR+vZhWjz0tgoNWFCVk3GW314VKYisiEPvtVBF21jx4Kh6pROXFP7feZFqya7t0Q+PO\/vy9aeOOvrOZkPQ71dd1wPd6BBct1g6bnEk6Y9LEJ6q6EzSnGh+2pzQjbI3tj+hsH8pGyAeknq9B4braV9u9myNk+71MkulOoYFo2VNeHKBszxpzmQRjlGQuJJFO4+VVRIJHon0DJ5OYKwsNTUxIRPFNs7NMaLz1AuMexZv2fa1UUfI+J+D36S2Hn3qG09VE0GF1fU949pcHu\/Ri1PpyFNVvp9aVH2fiy\/6CR7wail1pPjkUk0bC4elf7ylHy+pmlrU6CFI4\/VtWeIjx7Kk3vSF4NG5lidxIP3fi3D\/c3Pl7C0bkKdrH9ZP6N65x9fQnfRh4zg5gyC7+3JMSe3U38R3H\/qudnabSu8vTK8OFgdZ7WrSckr69Ikcx3X0Nji5xXb5sk6V+bmVpf9tHgf6R3Z5rk4Z8\/ggVUjxGe8w1027iFwkPv8Cmb1xR+\/26bLbyO6N3UbF3mNIVk6Ul261oab+Wu9Vwhud7H8sGvr6S+LBsyZwj4kpyX42ebfJ6D0Vq6KOkCDYmEFIOpGBq2a0X7hGU4OGSxZZ79S\/I+NK4c80klx28Nh7JWMzEicsm8N4JChuTdsxfZhLdkX5\/eR\/pJ4K7IHeWLJJ+ocqL\/kvGP7VQyq6fZWN17+LeKFanfQ4KPBvxpLO9Z+1TGg4M7KuNzj3YxcSjldffNiw0wvxqZzPupBEtt8m5llzPB\/0eFscGxHs+U\/057+Pz3+pwq3YHL\/s5EDyfXNXzK6cC9KOv1YhVl8NI7\/XxmKBOLVRPGeglvSSzE+U+3i7Eh4HhVzz0m9P84njEZrYat8R+9rdnFMIw+e9A6h8LzHK7F3oQ7zOSi1RWJnlJVWYpbHThYtcrP0oOLwv6L1wOHPhEe2c5w1ZSkMc9RRPa0CY347OBldX0ctOu\/fVn6lwPpNbpC4v4Urj9dNM1L8tXNJ8tUQ4j+fDDNF976gYKBpedmy+X\/u\/W9Ca8tVzyb7MTQy+zBScV+pIfdf9PtTIHhyBDLKGyGpYjfhENfN3T3frLbqUVhdt7bzrVLOKgvig+g6zk4LuDldZL43sfTtQvDpYluJczR+EDq5VEud6FbOwex7GsWTk8pWOQed4r4QaFA6nxgagyFs0tpr7lBFNSebjDPJhzf+OXVbwniP\/XZYdeLST71Tpdp8yT1cLB5w55z\/Byc0A53GpagcO61V2v4dQrRhd9CDtyhEXKr1MtnJ\/FlI14zN1KfR1PnhVSd46Bg3+lj46QO85svf80gdRh7mtrlvYwJx7G1PoHk+msCC7bsJte\/os+j843kX6pd5Mv6ehqDsr0vFcg86R3ZNvt43giu\/jz\/0IP4ZJHhahFH0u9pLtX6CY9YiAvP7z+cNwiT3m+vG9eMoPrhDKWVw8R3OazvL34N45LAHEGFb0SnjXqSFUn+Xl+mdtjEfBDTdXs9bDqJj8muqzPrpFA7P\/mJTMAAYq21GftWD6Pj0RAfq4JC6KVPlA\/dj6C1hyaZOUPYwVygciWPQtiviPibjF78LXynf1JmEFvaTl4viKJwxY2\/7jvh0FbPF0wlMi6xBz1uP1rLgUHWGbSSOhrrqOH7TvSFf8gzKTSJgRPJ+cHXM2hoFKwN5yHHu5t1TF5WMdAtIhrXSXj7ivrtok7C2zaCzZkahLdfJo0Y\/\/s+fWSfe7kKOf\/vMdER81IG5COW3PG1ppGxavy3LdHR4LjttWdcODgVtPrQBWUKnWP2P9JaGIjtnWiaOlIHzdA\/g1+JHsfpPfgyh3Agj8PW6m2EA1ULRPKsd3Ewa7uLQVT4MHZvYLpqStciT+SFeFk2B6Kz4tqv6o7iY0FAm09BLdiGnIGeMTZenJELmDlvCN7v2S5zflVjVmhi\/SJlko9dY8LMe4Zgw5f4ueNBDWISJA2MbYjuBtc5btShwC8gzn9CoRWb5paPmZHPs82oaYs00ctFD1v9F7xuh+i1YfpvEQ2joG0KL4nepwnYnaxS6obeSsupmcEUco1dZewPsBC9TfIUZ2Y9FrSkhZl0U+j927zW5BYbn4Radj0xaYRLIL+7L6m3bV9trpmRegsoGpe+JsyBsKud0spQ0gdpAfHcDAqr9v8t3JJPoWKYa6XDPXKdg7O0Y79Q+Bwf\/5AvncIBr2rLt0E0xEzMV4o9JLradWyOWREbmjuOcKfdJ5z15Kr63TEKpZeVr9US\/mlKz8zZEUJjWN8qaMEjojt2BzusSb7\/X+lGp4Aq\/5vmCqzW89JPXNSMiZWi\/OvGOPBZrTW3dkclHnLv3\/jOoRl8xyMvMMY5WJa6UrWuog0LI+fb1uT1wmwF56SgKYV5O8+1X\/btgq4v9Yt3bz\/WelzcMeBOcsUqvtkbf7RgXr9RdwCnB1cChuTV9In+fBvk0RTqxOjZ7RKh7\/vgKiEvv8+OQv\/K3IJFI20QPt1zM6GyF+E7zExHyfX7FRJPH\/VmQrxkUa318nLE7RFOX65cjHm\/XKK3kdxnePTFevPCRowvml3zRaQUm3Ijzva8Y0Jh4Mpomnkdak68luTTLIFsktYVwxEm4sfWOozKNEIup+rPh4ESOMxSuXTmCBMCPavvTmiXId322vQ7vv\/d77MZRz9zcdqZeCB8yULdpgFuiWHvTr4pQdmpmutFc1jI7i1Zd6ypGV3Vpzxnhpci+7Cr6pQUC1l3Omfrfm9GyshdT+\/7pdCre5av1MGBJs\/sgDsOFMTqmWlB5YR7Rqu1ckl9isaurHUn9bllhtzXb0RvZeXPe9ufpiA+\/WTdphYKGzU\/n44kdWoRXvAqKY7GkiznV\/\/u226y031y8SQT3ywk0l70clC5U4bJRfxDN+Uu\/6wKwsnz7W6cHx2Gq7ut5oKhUTw5+kBZW57GfUepuzPD+pB9gD4SEzcIc1Weu10JFIx91n07ZcnAld1eW6sqmHj9Z0+BKdGXqL9b4gVEhhBhFVf52msEVU8OPqnnUCRfN\/vqBw8ik32yf4nACOLkAiRvET\/JcIow+LeOurZo1F8jsBO7n3JpFvwqg+1qf4PL+Uy038iRimuqg0FGd57ynhI4CZoGib1hwmZV6fy3\/HVIcZmx7K5iCfpxeXOyKQtX31o3z9rYjj8eYhrf3Mswq6jEMDWK8PB48qv2hGp4hS7Z05fx\/2Pek1YOf5rLgstobqDrYDOezxi7WXCnFM7Jz5wjBVgoE7XexC3bjNv8vSssHEux543u8zUdTMQN\/tl+zb4BdZqNM6+\/\/d+tg1K94chj\/rAcjuzcI2cvNKHELeFEKZvwbP4L1pwn5TAZ6hOaDmwC096vqY0cf+i2ZsX1qHLoSS0rYJ1rQtrGnyVp5HiTfmG7A4MNr7D26N7xQXhvK63i76nGreiYbtceNj5HvpCKLhrEPdOfb3NyqpEhtyHrmSobSseoHWn+fdilp+8ps7cSnzxkdKNYbFxuXlA2Mj0IjxUTdU7D1QgvPjZY3MzCRY0UjwnJXtxZbDzv7PYKuDoHVObnsWDuu8R1zK4HXy6Uqf\/iqoC2zWJmzGcKS17VF7SL08ha2RbSSup057TqyZALI8i8miOpZM1Aeeg2GUOS7+64fPUdM2Tgz\/E7v\/bmMHHML9Xo1H4agolJvfaOI8jnz9ZfaMRAZdq12lNLaUgpCB4duT4IXgH5NfmzRiC9OEyZq4\/CUGzjoEPSIMlHkk+2LxxB7ExDOn2AgtanifDq6T4UyNt2MKcGcZO+UuVBdPvD8XG7+mrCh27L0q8l03A9uSn7UW0\/XFus0\/7tq7n6NGbMJX5lu687dqycAXdby1O\/a2io7axyEkqhEWfJWFC2cwA1D6uFlrbQqLCPD7b\/SM4v2D1fz2YY3\/fx9PAQLoo74b\/DnHCR4oeQ8QE9JgxUTc89nWKB\/batqKuXjYSaJ+kXiB78EUow6OWlwD0SuLEzkML9GR8OOL8gnLs2+mdaAAfP1KJlfWWIj9UWHRjMp3HOJDpmv3kDtkeLhi+r6YDoqVXpN+dRyHEXOjj9vgWtUp2TbzJ7IP3jl9KS9YRzzh4xGZvdAk8Xrxw+1R64u9lkNWlTCOBe9\/mgejNKRO89V7frhkn5CvPLKylkZxxtUNrZjsoo+nTKj17UxE4c091FYe3I9s2dp5swwnDKnMzvwlNFLcbHpf\/3\/RNmerStX3CoAdQ6o0ftfR14f3Fguxj5fP2c+VwezB4sEzh5RGrPAGbxmG8PJvwayPuh9civFshOrHZ0oHvAbZVSvkH\/3zrMk7Ybq1sx9eC54d\/dveA+qWs7YUjyTpkkla3RiSsHTGNTy\/vAG8eOiran4Fw1t523bgheq55kVQuNQrhpxj7rGWSe1NatMUkcwqWRMBVPxgguHAhQk\/lN4UWL1etN48MYv5ksX8geRe63tcdWKhC+oIUbKqNHYXrRTLdDmwmV3AbWjq00kpRyhA7+HkXPhYOR7peZoH7mTe4mefLgkxX25WBguexN\/53vmfjtwFc5RnLX3BG43RWmwOrQd+GcZEBt24HMfoM6FJ4S\/iy1iY3o9DMHMib70PbtqI95SiVavySvmnWJjcFz8xVXLxyAkrAow+dqFZ6c9juY\/56DPsH3nn6rRmFTUBqimVuLXcKu4t\/J+D32WqWguo8F0fS8rdr89ZBfFMYVlkth\/FaqdBzRg9m6D\/d0EN9LlLmz2TqCA5sfrpYbo0ew49QHH5fAWigu+Xq7Io6Cp\/ljwZZPLMjK3Txa7VEP+yWr8o9eJjy5asZuXocRPE0ul5g+UosqQ3s7m4csaF47+yR8cTckxZX3qN8qh0em56p5+9mY90xl22vHfkTSn2Ye\/12J+zJaHNUANvqcruqIzB2AuSyjovJCFaREix2Yi9j4+Dh+2VrvPmjqR28cM6mEXF\/n9TniHNSkxoyUhg5hVdN5holNDcZUBSzPGbGRd3FNaYJQPwyuP\/j6I7sSJTc3Cyi4DEMoMr5APGAU76xGNHcRfZqKPsnHMB9AuLHG7pkiw4hMkPqzupSC71i+B5d9P47kHsn23jYEWuDY8Pq3hEe5P3+ZCu+HwzYR2UbvIdTsOam0keTra4soPnfRHqz46i9a+qMfWQ6JB7rOUfAz01B6\/JeJ4Bm3C4+ENaHCR+Cl8KZSDLt9MNyxiwWPe\/vShk63w63o8PnuM2UwOBeTu\/QM0VVL69iCpk48u7IzlW92OeZ4Ljw1soKF3O\/rjixzacXAjugLSpOlmAhqHPVMZyHh2Z20jIpuSMV3ml0oL0fS7haBe2YsyLlaezqatWM8vbAk+FgZFr240i\/QSEPzHtfsV29p5Kq9ZfEKDKHRa\/NAcBmNC9yC\/kEfaCzYu7GoynwUp7NWa6+OoSF+Q0Xb5t\/9Xg4am4Sas+AZZOL27z4yHjmRnhN5NLb3lWXYGY3grb3q6eZgwhEuDjFfHv5bbx\/ymyeeDdVFpV+SiM6ul0h2zyP62ZDzWfSIORN79rhcnvJkYrRAQ1czvwyT1V21Y1LFeL8kQfyGBxPhZ3k\/Hb1ThtkeWlV+Ev\/t+zEJWxuVspnw1xnxsj5Bcs4d\/rBna0vgWnlp8q8L4dLxlPhuZikudp5drz9dBA119bGX7kxwJRzJ7bMug3roktu7hYrx7q5mfNV8NhRPLl102LQP7JNBr7pWVeL3UlONMMJf+t9srYT5mmDdsSB0l0IpbCt3yNVwsTA5dH3RzfgmhO63dgozKkW4f\/fEgkI2cCd8UMNoEFnUnyM2dtVQkTAymuLm4EhFiWO19RC+D5gXyGjWIExtmaWyKBujz2fmWov14Qr\/r1JDnkr8+azvZCrCweCiLI+ioCHMmVMrab2nBoFvigtPgA3eoXOfN9N9YIakTbYlVSK39B1vDYu8H+3G86dO9GLFg\/upL8Mq\/mfccvdSgfzAz2rM4Lk807i8BU+NLwumTnNwf3xz1QirCgbm+7S61rXg0p3LjvVTHDDvRq\/a0VKNRufu8dtZLTjN7t2tRs6feYDP8UM9hR2NzWeNXdiw+fx7zuexBozdjgh9RHTpsOHuiEaiS1sKlbQtbBtg9nX74rldFJb9clmkdY0N1205V3UMGpEU+8X\/uxwFCe8X1xrfMyC5282x\/WAdEnP3v2QSH1sXzG6Z4GXC5aPPgv1+dfgwPXBk9WaiY65Zjkd2MbHDcku4w4M6uG8WmPvKsB7xUxaLW962o6\/8SywlTmGWz9g5GZFGXNiwRL0gpBMpr111Vij89\/rq6xuLRW4drcdc7ga9nJ52\/HBarikx+\/++Hvva0o0nr6uPgnfPFnOJAQbWWKqsfbCBxmt9z92WP0aQZcVU3faBQXxUScdVl8bF9+\/9hjU6oPjZTGTAug959EEubysKK2Tbls4QrYdK9dR+m\/Pt0C8v\/WknRqEv9LKp4IUG3LQxC13P1YnoUK4Z\/cR\/bX3eWSs87oKMu8bVC079mLrItj3vQWFkciTsb1wbzql4qxum9qKgLEfvpQmF49y\/nR7v64KVxjTP5i39eHFFuuTmEcJde4vejIa248GcvJDsuX3o+dFZvnXPv33trkyGvG+DUOhmscF3vXgy45v5yR0UlLTsZyjP7cZuKX\/Z6EiST2c7nxXxptDBu2p+VyUNXalzwQcSaTznUci58KsPR11nysiT4+XJb5pzEwhnbjCp7nzeB6tbP0T6GmiMTkT1WhN9G6ha8WTu90FUWO1Q6ye6N4aBhsAsGkd9eg+7HB5C3PPowyfIce7KbSyBXHL+9RVen2NGkOL1Qe9oHY1wPvGDpTk0hKTFfoxXjYA7fHoBd0Q1ypXqwlMjWnAngfJY\/YuDgj8uSo2JjdjffWMVY1YXNs3KEpyziEKJbkOss1ctapK2L04vb8WnrRct43hIbjo0T2KKcH\/qYqcX06Ukl3+4JfyXcNQ3RWnvtyqt2NY96T5DqBdnxTnv7oJw0bnkhXoidVhjpvfwtGcb4fI+DXGB\/3td\/QoMPlOjV4Ht939f0KxrgkT3fM2\/1H+fb3Wqyao\/pB58XLOKfabbcX8Wv1srqWePKQOm7UMKXZ33ZiVmsrD2vKbzlwP1SLS6Mt+DcI3Er1F9o2UUJI0eFd\/gasWDdwWtKh8ovD37cbPNHDa2SoscLdNsQH72zDPL5tHwCTE\/HLiLAy7Bs7eMRJpRyp0k+notjaG5ewv+FHGwWXl+6B2ZFvwRqelhuVNIv\/6zv2OcCTfZzHmMrjrkyEqbaNxgIXPH47cRF7tQeUPP4+qucnyXM+lurCS6XcLFDrxUD2cn4fm+\/iRvivcpZxN\/zFYYLj9m3g7DOK5jgsfLcPOz4QY1FRoRefQZBz8OdopU3rHwbsZr7VW7v4JGunyN8dsWDo6vVfvlYNAC1ROLvm8ooaGThv0W92mUZFZsXb+yBylPjg7JEP+jm0XZO+bSYMgqDQzJt8O9VmjPMVJXjzXHAhak0+jfvuCzEGcAWV0GDTuraJyRrR\/aSXx2idYrTWO1fiitqx+c9CE88ClHwecMG7GvmtUXhBGenK\/b4LuRhR3HCzO5zdiwc2fGUNdofIzz\/7iF5C1Zr3qpwHIK81v5ZS7z0+DXtrjZeI6Ba3q\/y7VHmVjn8SSPc5BGKs+CLZsJ760IS2zbsoSCscMe1vNCkocYa5WM1tC4elXXr\/cwjTULRPsXPePg8Ma1ndnkff88uK9pM3k8cZjfK53FwOlr6\/+KltK4xzASYbyn0amVvnGR2yi0\/HIMN1lSiFtj6byD6Ppgi9Syb4o0Zpv\/WSMaRThhXdepp09phNwuqte\/w4J+79U3DJIfv2z9UjxHgsbbLb\/bLJz\/d\/uzPdX9KJFtxMJWMdWrksVtWFW7ZCjUtAwW6q3W26VYcJannEvZzbCa\/TGnNaoUWb8HlBcSHqoWzxtUfUNj8toOaeZOBvoNN\/k2kLznsv\/a+GaiM1U+jiu2L2JgxbXc24YkJ\/ad3PnFn+S3yn2ysuozBhC\/qmT0BeGkbLc2wY5Mwv38Lr6hA6MYTudLNiY5NFHct9PuOdElYXFpvTv9kNWIL5Mnx0UWrfYUIMfX7KSplkv9sL07J2FokIlVCh+zfCYacGujtXViewnhHXQuqmZimt8781FUPUY7Xxucu1RC\/Es45X0jE\/eDtW90TNdDX6oo9s2DEqRs5RfPmMHCYidP4RXpTTjcV5U5sbWU5DqbzbLJFNzV093Xd7Ow3il4lmJmPTYt7Nj4PYiGoa6DzaU8CtH2vsoxB9rQUNfufC+BAv8MRa6XFSRffPX4YHO9HsGzRGILZUkdvTOXMDrAgebTNu9TC5pxd\/zwVzEyrz8nxaSv63EQZVS2Z05zE0qEi7sPEF891XDl3N5cBsZP\/jGScqjDszT5pJ\/nSa5ec9wr\/CmFpimzgzfl2mB5y2HOCOmX1\/4ORyKe0cjrf2x65yjhddETAj1VTKS7zLr1eJyFqnglK64AkvMTboQ5dA\/D4PRbvfVdo8i7P2aiJUfDcUshz4onpE6knEWialkoqPrA5pyj4Xaxd\/NOUj86C+Sr1DxZeK10fhnfccK\/YmoxUhSZ5wDzJWc2sbD\/R6\/iriM02k903L\/3jo1FiyaK2GeInvbxvqtO\/b\/vI1Q9+P67Qj\/RpRLeJb5behGT4cdnebwCwbE512ddZKHx75zNp1S7kMd7zTB1ZTnkjlyIE57Fxp7xoqRmvj6kfchyMpqugGROz5VsOzYkRDpjWwL78XBfChUlWQX7x2Uc55MjSKpPK\/PczcCMWzorlywndTb1rrv1FhPXF597YJ\/Hwpd74id\/n6Gh3qJzqb9nFO9zjxx2JJweveFAxqGdNF4uyTaUCh7G9s911gYkB3uomLq5SNJQPrdiU0XNCPaJDqg13mNAnPuWnKEWDT9LbbNDxwYR4CrUdG9iGAKlW+zyu\/8\/9o9Nu2u\/8zN5fWYiUzSS5Ibmd5d\/pnfieStHZHAmjeTk+3NjZDkw5dESq7\/VhNhvBld5CR9YXdbYNGMVeX9Bu+Rdrdth2ZJq4DSfhsOgsaWzDQc77gYcslVtxm\/LRyvraQpWryuS3MrYeCW980V1QyMWsF3ee32ikbDgy3vnizR+1a\/g15DpQIC04VZXbgqffPzZvAEUthR3KEWm0Xii7Lrw3QgbYzLW8y884uBGBL3R9DWNmw2xIse82RCzFWP\/2MRByF6DY\/KkTn+hyXJGCIUiRe15jH4KDcYJfxRrKPzwcrwQmshB5iGFWS90KJRJrVQMLKIxkT+lvtqUQvwYV2JlFuE2rbGjP8jnk\/d7FJP37\/6sD6W9dxKdKWxZn7cxg4n12a+rvYhunJwIkrpJ9On00cfaZn9HIFN21vFHEw2m4GOhFqLPZa5JWxU6hmDZUzYwg3yOTCMtiZvkce3XlYKmAkycjRJLryYcld78MkqL6JtrQHeQMT0IX9Wd\/Z\/+3Vd8xnmxg+Q61tE1l4b8R7EvTCJe8BwLTzw6X5cOd6JCR\/TwlnnleDJv5an2OhYEwgvUtX71gGuruIrw2gpkeNRee+\/Fwmy1GcqHj3Tis\/i3d5KTZdgcay6mqs1CSujl6SvNrdD+Pse+V6IMR0wZe1KSOAje6lNeOzqCDxfOdMvG14KxOdhXfj0FE96JV7vXMLHSLe3cz7A6mLnyvFquxMFDnS1jETVDKGX9PTA3rAYq6s8XKb3mQKj84DktqVE4B3wyDHlTixPHwxau7qSwdt6d93ohbFyelX3Kel0jhqoCb8\/2p\/H3Em+ywXMKPBljWrNU2qB+3+VTOhnnGwl6+QYk146bvlm9p6Afm+919twm\/sl42nT3TDiZJ8E26WaxTtzx9ZDcSfJyqYLgnyniA6\/lM3rnGI\/A6WZAvy+5ztuyTzxhZL70pY+wW\/+MYLWT57O5hG8X5kyy08g8uzjd5X+d2IdH1nZnXidS8DH2Ff63X1HwlTarVzH1OHdYLtKD1Pl6233OF0mdf3Q+wPOQ1PlIb\/3iZFJvDKv34u32LBzvL3W\/JVSPR5ptLct1OOhPORvwedkwMmK\/7pVrr4F0iaJ87hSFSFbjxsukrh\/\/6Xy1WKYJhTnprkY0G0vSU2c9FBlCwcrXYanj1RBVj+yRIZx7tTwlTLWeAeGsU5feu9b9n3UvpmnbttKOdsJtwk5R2n0w+eP38PVeCvfXFXj46jXDWTD59TO3buTbd3KNklx31fz9hY0trXjifnLB0L5e7JdpLdI3Ilz6xrJY4HArGILzjP8q90Jp9z6RiE0ULm3KEtEl41z11eLBRuKnkwEVddyh\/eAVE+mnHdhoeTzvXL0WB6fmf390jeiI\/YoHsgKfmOiSytrMNcxCRG1npB+pg6XHn8jXbWDAc\/es0s9ZxB8cvx\/LJbzLfeG22J9WJlp\/RWRc+MVCstDJIbFAGht0Bte99WIgUd\/\/mFkvE\/O47c+wbGn8Ln01YB3CwQErvvEy4nvv3F9t+rdv6Qe+9beVS1i4PaT68fB7NtKOPaWLCSd1jdGVMXNYMNSP+SOwnI3an3IRucGkD1XvCxyKZENhaU6PsC0HVyatHA8QPfAZO5q3Yy0TBhqJj7n9WHg4nJTJ8KJxIcx3x\/kOFjZuktoQS3RPrN43KesejWt9S19fOjCEeZNBsutSRzA2nfng+gSFysNrFr05MIo\/KudirPiZ2HOfOi9nQJP8Z1FSHs5EudSt\/suFhCNOBJXYnqXxyfaHibbxMPa8+z7bxnkUvYsC7gmK0LiiuNbKcRsLLQPPsxX2srFsm\/Wu0us0puO3VW76OgoRvHx02Y+J1WLUb\/NdNGKE2rasXNWAgfYtRdYpHbioXKn7RJpCqnhbs93fCmzqe\/iLj9SFTpGIQc0Y0YVvqbZ8AzXY+HG3q6FhK+a6pM+b\/svBmrYz9vF1tdCVMB1uWtkGkdzUBlt+Cg9u3Xxq8KwCETcr\/24QbsajPSV5t79wMMdzwKFAvQG29yuW1SR3YDK29tpt8rre\/vmLpY1pvErSYbmTcRzr5hpOvk7OL8\/klaulcGgTt6+nDNHD4d2UPcm5V5YJXDP8QUE5JfOuEsnnwbcv7n8rQsEi\/3q1KrneEnnZQL9QCmsqkyp8bhC\/yf5Rrkp0qUpxmc5bUq\/RvPxhb4jOSg\/dUCwh+U\/ikKRweQp5vmxV0astNGp2G+i2Em52PRA8u5DMt92R9g7VOCbJ3y2yFHmesoHLXS+iz\/r818aaz43CdNUB1sJWGua2\/dM+xN8ufslI9ykexqTWuiI+QxoNctxvvIY4YC\/e6c53qAWJOSYTx1SJ\/hz6dPJpIAeRN1QLFp9vhj+PkWYu0ZOvjSvPqzuwsOXPyJZ0oifhz+VsDljQqFg2uzZEjkL3LjG+kd4WnPtUy85N+Dd+jePqlSxIPVwkdOVGPbKLeTeHvKdQK8a322g2G5WvOMY\/yLib+8\/6OfSjBxuiOJsP7h\/Au\/Z7qxdeppAiYRjBPtwBl5Iwxi+vPpzVsFw8+wCF\/YoaLiUtxOdtVa93aPVhjtaF7+FENywp+35bVh\/crc\/oFjAHcTPbb4\/oS+K346uKlbO6cHky3+S4Zz++\/FIxO+BJIdE2b3xBcB\/JMwIXwqMHEfX2q5IUed9Wiun1m1NYkHv7vZid2o3WqOMq7Nzy\/8famb9z8f3\/v0ilJPtS0YYUsoVKuqNFpFSKhDYS2mghKbK0KYrslbWQsmWNqCT7vu\/7+lxmihZF9T39Aa\/Pdb2\/Vz\/NdZ1rnsfMmfO432\/3M2MGT1a+sQ4jvibk\/2Ln0GQPAnK6fiqTXH1KL\/DYvUEm0kTut13b14sjbslLHC9XwMXo4vjMbSzsupv74NrcfvgsPVZinVsJziInF\/8rLFj7PLN9NUW4X9cve\/WZKpQ36TDCCb\/df5XgvoXw29kvzbxyhN+CL+gdsjzMwk2zg7o\/lNlQCrQ7oUr0qsmGzxMypD60KsrfhlNQt9DvGj1PQ67KOd9bhI1ep06J2iI25Myv\/PiQTSNiZI6RBw+N1l36Li5kXnPot\/+RYhNuvZD0rMyQ6Eq6d5C9E\/H\/8V+Z+6+zca7EJ+DHZQqRPRHm51spvO77xOoZJuNjlFffQDjFfqvph11Ep3bbDlkbTHVBuL7k+I3HNByy2HaTC2lYfI\/7HcHfDvYpSdOdZH+Z\/Hktq4OJ3kWdLtS81YWTLopJYiQnS2mfzZbRY+P4jqMap782QV4u9qoF8TWfS80FO4ivvbr5UEOc+JqMZbjG6SPk94u3CvWQenkZeYVrTL31n61zOr2eWlNwoBav+JRWRSS1YrGsel4z4b\/DMaqns1vqMJ7d8tlwSztu1TtqN5K69mnyDLlxoxM7um+zvlN9kG8\/PLnFikJrtU3fNfd+xO57c4zTagiaVeM3swnHhZQumOhQ6YbJgR6ThKh+3Gxu+LT+AgWm0LfhMZUO6PtfOWFs0YfXH1duvXKQgskToRvRTp3Imh7juDHah9xayrv8OMlL4hLHG6IJzyTFfnpSN4KchnO7U0NrYeBe4yF5kg35wA0Xu0aH8dxh6QqNjbX4enBDVeIZNgyi9E42cIxgvohPxruttUiNEPjOmEUhc8vYuOuhMXz3CeBYtb4OD0Tkb43WsnHl45WnO+6Nokb9S\/nFwVpwBccuWi9E9K3igrhMyBgi4mzii\/fUocXtj5xybTN4To13rWN1Q4mjaWfmOgprRW3cn56tBkfVC76A6y1gbeQdSP7JxpaLNhslPjfim0tvq\/auLvD1CjMcpSnYHZu7ZYKzFuonOLnjTFuxZifb03MGBZ7kndwu5m24z+4Xkn3QC2VvcflL+hRsa7barAhhI0FLMmtj\/Ag8hlvrXW\/VIvqxStbHJiZkDR5Hn1jYi+1lSzKW6lVgY89qu643TGjtFEkK3dSDazr77\/yaKEdXRlWjViILD4qGfeQaB2A1UCS\/g6caJQ0PNZulmchKXudV3NECqcC0rScaShEwd2nrntsszFS7On\/pxgG8WelpxPOoCmIPoiokHlM4sNH3OW8KEwU5b9dc1K9HBf+Kj9Vrif+9+hKUEtsHk4ASHkOHSgRdD9o\/P4QFO5bM5z9XB\/DSh59XrbIKOfuVFTSYLEzvyEtSnRrElyB9XemhaoD7V2S7Khuf3a7EPJEYRoZb4\/JzNTUo3ajvnES4YKeSQHxPBA3B+6suvXjKwpwEv1WioRRyZ1wQjCe5p5W3ddu6VxTEntn8PEryccvhidatpF4jJRp8eRewoX104Pck8Zunn9yZk38ofL0iXbfal0LNz\/rC537Eh16Uy0WOEv2uzPNeXUiBY93chJPeRFfU1BbST2go3jC+d6CchavZggf+rvdoX5uULjnFxpy3UaJl+s0w+UQpD9wi\/vR4zsHD5RRO1n633O3YBpbtvSWNfRRu2UleUQ9nQUMyZJfoyUbCpS\/torbR2DfiMNTOIDnp9e0vrmdb4J7eft7GmcZEomPxuwDCudZfC9d9bgXjeUbgDOIDnmu4Z\/8OYUCleq38nNd1SPP\/2O5+k0KdY76NpgUTt9r8jiXPrcf7eb\/ib5I8ui6jxE\/gPuGuIN1zZ3c14pljmu7aPyzEb\/SKLDUcQnBCRNmIdA1uhYvPy89joWtmWmDEykHoyBw8lby9Giy7sjN764ahva+tcE7DKBQFuKaHFxF95igtdVgwgLpL\/Z+0m4cgfWGz7iAZN7uxDr49t\/qh+zuk1cJuCHMSPaQP5FDI3n03oCqtFzNXxPsoswYwoTv8+\/BDClqROcVd7wdh9eTb8in1EegYR6XuH\/5362MSh\/l8EgjXMr4l93BuroPn0jsLDiuUYBtDy7O8moF3T\/48jI6ux8rVJ0J+3ChBrUnw3kvFTHwYF\/vTmsPC83HP9VnEB2C7aM4ZFQqaikZNjbEUDm25lr3zMI3LiX5dh8TZKNn7c7FgCRsclnGa3Dk0eFp7TC\/sZOGC4gORt9L9GBcW+z5UU\/k\/H3\/VXMo8hNSXTqnuz\/SYPkxltC96eK4SV4uuBC48z4S4eHOZ37lO8Fiu3mH5vQwGV6tWuphU4J3o15e6vU34eebN85M0G1LvNWKMXSuwM3hxVdREE\/oCUqbYpP1s9VFF67W1mOCSKdTxboWueW1f9kwKM4+JNPjw1UIrZ8O6fpI\/dJ5UGnYTveqZuTny6PQAXNT132qGEi4udnyS3kQh47tQmYPlCIb31b5x0x6DU\/fB3d2yNIpN1RYJZA+jMeVqwM2CURygSrfoi5G88lRUex2L6HWK6BBX6hhuJc6bJa5B4\/5najgiggHT8ZdnvhC+Ypm9DXdzpSH89Fb2ld0jYPi+TKheN4bTaV73j66iwZn+ZvDvdxM+Sb7adv8l+f3va75GGgNQa1GssSC5NTkzWGQuya2N26uds\/o7UKF5cU0TySUFl4e+Dj2gQQss9Dt8rgO1k\/1C5RJMDMRcnW+uwkI3Lfk2ktSzLyfynhOOj1S50\/HyFdHXqIWdZpdpXJcVditIZOJyoVHx2xiic3tue\/IHEZ0IUtQ\/xMVEXV97S7fk33pS4Nt5g8aXDObjsCQWqqzSj65yZGM2t9eywiQaARd35\/vKVmFEq3q\/alMz2rsDreZ9Y+N8QLrJlaRKRKVeVb4R2IyoAata\/S\/\/7e\/nu7+58H2pQ9jza\/5ix9rRxhAZjOGlcPZm5kXO15X4KmIrExTejPtt0R0XSD+3r+z6NmdlFRR+px40rG+GSGiJ7revbETk+zzdRLioWMvk4lALBcfH3\/KWEl1MqDq5eSvhrwWplMZhMp7Gdu\/vD2iz8XTP964+LwquqgWtgb0UBF74G9o1khxQozcy3UFhlrO4ucEKGuP5rh7bCPfnzvHT\/ULy\/+z80Cp7ecJl9x9HSxm342xcpO3f9WGtBxkRc0ietc6ckZrs1Y+XffprcmsJd516zxWRTHKjVnrGrKgBMKUv7hMoobHhyswZ30nek3Vcn7R0Xg8sXfbN+2RM8uhaQfnliynUFy\/5+rKrBZ8NvRwm1xAf2NrElGwi\/n9a3SKb5Ak92+ibPF1MzFzneLiT6Pv6aq7GLtLf04bZdm4dbHx4fFSh9xhF5l1mhG85jYMTF2eZHGJjYYXUrQHi94MHnoxqkvzhGONmmjHFhr\/iEwUuVwoPJSOLWLk0gpR8ppXuUNDeUuLiM0gRbhFNPF1B4bdOwQZ5\/nrcXqbbmOrejof0uIDzQlJfIVXTIcl1GDY7+llQrB2bg55dS+D573VFx5v7vYRzO7CJ84NZV3Afbm6sySm1oHBKLaDzC\/GTmDPHrXIu9SBB8IVi0QYKscnj7wP6W2B2WiKss60HosfcVl\/QorCznPNQ6wQDiyq5Bcb4WGD88AiI9KIR7dBjtPM7A6mh1ySfC7IQuku1fIK0+4vteOFgPYYbJsc5Pzcx4FqbQoda0Mgfq3H8HMHE+cwhh075bgzsb+yTfFAOgX3q2lWEW5o5zbtuEW4xm8XsWk+45X3+mUouct3b\/UslmxJoNMcmdz916UeNhoXdgyoalYtu9ym+Idw\/qfRoaMEoyiyT781uoPF74Kj37XQax5O+Z64NH8S6yuzN9UQH1GUmvycRHbh0IybSTmsAKptsf4Q3\/n2Pvp3PWBaNjJitrcu3DyFy+dcKTjJ\/juV5Uy1hf59jvZ788Vf3P\/OdCZXkDateMXDUY\/z58bFaSG47WaMnVoK0JgPbySwG6j1U1juo1oHL+\/KJvDUlmFKx7+WNZqLy1F4Xfu1uKIvWzVob8t\/fpf1f268\/8ZqnH8zApu1WThMu1Ujd8uzP7aRieDn8KGLcZUDC5GefnGYVtly5wVd\/oxhvXI2zsm4xsGrmjTSa6Mc+D4\/9OZeK4fJRu\/6DABvVxn45Z8KHsPHT72HaugafRJw5XELZ+FE5MP\/OyxG8C\/q9JvZOLTot7EcWJbMx49mbCUOOUWQZMGdeeFmLHzJ1n17\/vW\/KVfBcR6EPitd0ajaL\/+\/+6KmaofDmFxM2jinlHUW9OBoQP+ZRWYFXCplmd4hOvRGI5i+JpbHWuf33il4m\/ogUdfY004gtK3HnfkfD6bJHQtiFEXh\/PPh9J5kHZqJCrwNI\/kzUiVZf5MBE073crw+P07iRZN\/393u4Z6tWCJ83Jzos9XOOt1QD9hdYT4lGd8DWzHP1blEKBhwSO9Rz27HMZvG9BbJ9sD1rVRe9n+RYe4cV2eENEGtq19gv0QlpHp+iF4so6N1O7Jk\/qwOVCryH5uzog5p5Aue0CYWRsRvCVZbtGA2KVZs7ow+yZgpLUvdSoNRTlooX1CPG4grOq3Wg2H5ZmBXJLdRBSfrBSA\/sVVja7L0DMFvj62LnTeHzb4PtHk87EBIr\/tnbtw+38ztzxIg+uMn6qerJ9eCsfLywO9cATFwC18y4RvTbRL8xfmMfolu+s3eaD+Jmwm4u6QgKr+ZP1M2f1YfWYwv3f1s7CLWzgU6tYRTClTrT5u8ZgKntsVhjnmHEqsf6ryiloPPx\/cNX81hIMNrlqUuzkHVL7+J6wu89e9X2pz9hIpBpoWEWysJezSuzGh7+u\/9LYm23kmNtrYfEOlFd4ax22HLEG37io7DvvcywC6sOfmYdFZJm7fA43PrwFPFH59wdERlFNJSOT136+52BXZorHfjndGGtkprRib\/fASiJPn6M5Poe\/\/1je5504aHa4SHm3+cxOPv4LmTSuKcWHp9GcswzKwvRv+sDN9VvnPq+kIaM94uMx\/ztcPvIqGohupR5hKfzNdGlqqOCucUYIHV1TOs30b3b30o9RxPJvPr6ZPX2gX6oyPcm4wYb6g0OUXuPjmBasfJOun0tjvZ\/swgkdddZ\/\/JBWtgQziUGyZqSuvtYOl14QZzCjP2aJ4ZejME3\/JSbilkdpiTVvx5\/S\/JGna6+4rpBiMkF+nXsq8bpJUYZzPVsnI7RW5qhPIxVkirF+T01uDLsWludw8Y1ieTSPPlRxJYrq77MrwVLvdmw4d0YBuUG+CQkmeh\/UalWfYLG6rxZp8c0hlEnni+nZD4KS9kP2Y\/nEz\/+ZPVE8NMwZk35r1jIHIVpqX7Ndwkaeyt+bBeuHcMMmzHHuWuY6Hx+7YbxSaLLndr8ggtG8HTS0zpr5hg0v5Zmdiyj0Vcx0zPUiYFgLhPNeUmEAyX270xy\/t\/vPyrtCqwLSWUgwuNmjE1dLSpCapm7BEpQ5F3m2HmG5CmRLZH3fjJwc8RSdW5fHZi8bNtHTygM0dO0cAYTIt9K13AfqIfKFvOUS0ZsfNm8QZ7v7jDUFv1UkxKqxfDU092yujT+pNxZvOrve8q+1GTeMm7BfcV7mwWNKNhHKhi4XWfgxuEtJ6+l1OGh7wHfk0spbHB1znb7MIaYUMm44uN1\/2z+SySUyk57VOKEy+bG59easeBY8M4XE2xUMNm\/VO2rYC+eey\/9ezMqjU49\/0E4c6NtlMpLJdJu7xnl3EZyLP\/Ez1WkPVr+3cbmQ42oUohXFa3ohFND3eaEZRT8s9S\/iIu0IiRXUhCcveBX9zwjSriu\/ck60XjFDji\/1+8cO9QHydSjL44cpGAZFff29cNG+B\/rsLKc7oTplgeal1dQsK1YVvHYox3lduFePgv7sCndUalxH4U7UmOcA0ot2Dk+YvMVPWi4ZPK5TOPv8\/bCmZPEx0Xz82e\/yiY80FAjMX1mCAVH\/Zv5SZ0eVwiKfUlyV8pmA8aL8FFQPE\/MPUh9PfLI9X5I+OHAwajrhr9H8EFMKMeD8KWJfMS77YS\/4wcK+J2sGBg4vKT7QAvh\/XkyJ9+R\/a1i9gjuODf8z65LnFVL1\/PaStQv3kVzxDfjV5U8bznhcL7996ptdlYS\/k6y+nm0GdWNTYcGx9l4mPXmxMkNbKTflLkZoTqMyMq1fTv7auC76866FyYs+G0b8kk5SPiY6XfE9Gslcuat00t5xQLXIU45z58DyAx8cNZJthrYU5t\/cIiJlnMWVRImvTDMcVm3mOTAa9emFqm+ZMEkY3HWwq4ByBpWb68TqIaMztLchjoaM1Zo6kym0tg+\/92PXNFBaBgnNv4gfnlAtVZ3inBU6F39Jd7do7jU1lu\/qYzwt8MAVxjRd2HFGaw6h14cP\/P5w5o2GgrLaeO\/z4mY2PtnPCX5vvLmZxEXkssy5F893Er82Z\/3Un7hzw4YL\/t2YPMzGidyIpKsFWjUeEjKWx9ox4+PKQXWHhQWPn0k\/UuPifYNakynGfXgddhg\/KSFgcMLlgpvX92ArEe+Hz\/Gl+C65jqmWw4TT3jrFjCFelA8PsfMdqgcR+yK038PM8B1QGAoS7gR5bUt3in9JfiabBToF8uEz\/VbXwpNuhGzRGfVjchyXBPrD1SNZ+JbUer8TuduPM9K1Ex5UQ5Owb2Wvu8Y6C1mbsgvJnVbNKh+zqgEgtzujktJrqyYdzLpIpmf5q3eSp4Vo6hOUDydSvxttlqeiA7JPd6bS\/rnVpHzKDpgp0Hmm4pyjK47mW9O348vOXCczLep+mUchFdmcYTXBhNfSD22XFC2hgHGvpMXQ97TWKi303ET6d\/ziV+PUeMoyp9nFq9v+PvdCpvxifS\/35PlengnZRD2P6I+BI8z8PnblrvjJY1Y8ujBCbGFpdi4xB6RkUzseszRMlu1Gy84500fDyiHe2TU9kvCLISd\/Lo7UKkPUWrjgqmLK3FV9UzwRTKen7rXavqS8bT4db9rGxnPS88PVPLRDLBMnfJK\/RuxWuXu9bCZpch4pfNO4QkLZTcEDiy0ZmObdJKsMvG9c96a16PGiN4qKh53IrnP3dJCSlGWwkG+zX947CkIbo3+uaeK1L9c4eqVM2jE9Ek6+ZLrvmWzJU9rN4W0tpyOQ62Eo+qVtp70oLGq+ZJRGvHbZuF9hYLTLCyW2Xx\/zW\/ij3\/uKXdcpdB2ZceP92Sevmm+AKFrpF4kFzGdDNg4J\/vacjmpf1HLcKVyMKBTqt9s4kE47xiT\/wLJtwE\/ru4ZX8WC89lZc4Jms2FYseYpRzSNry0nh46IjWGdgewb73AGaHF3gVkHCEfGLi13bWBCLXt5reYHFlTNprZ8CaVR\/07FIWFlHWwVfZR5brYhvUQ+L30uhczH0vV+IrUQl3JpXneqFVc5nGXmzSS5WN3BsfhZE1Y3ZofkjXXBXLzNWlWOQv59relxg1rIRbr2bItpRbeC1oLbHBSuMdtjP6IR+5rcZsaldyLxCvN6BfGVIs0PoZe+1YPpPng1xaEDlgNKDr+FKTz9fmBf391mtH9Z8ZE7rRthpoulbqtQ8JoqOuVO5iMt+\/TzpQIWBsfNFx8nxx90zm47x0MKL\/e09HUyKYQeurevOpfkeUMH40vTbASE\/14URHJu7O1osTiSoys33c8fKWViVduPq5W5LLAeyU1+DqHx3u2w5bdiGvL5r1XzCF\/PtN+cYTbejZVb7YdiSb1kxPc9vPqA5OpvsqtctnUgc+laHXei26YTc0dayXXibKl8vCOJ5EHG3V+3ttNYZtS5cJRNfDavYYPXpRZcWsJyjCR1dXW8LN1QjsYmnYQ4\/z3t+DW7TWiMcJ3B9bCXpkE00oKEZiWrknFVqbwgzUXq1GN0nhk\/G+xnBovdXZrw64PIg02aNB6snB9WXcLGAfUfrPcSLXhUZcbtoUz6SVQW+xnHRmLd7MyV9c242lsiqUyuz03d04c3jo8hJXv784JLdaBPRb\/0I\/xu59exXzaC5LyfMVW38urQrBqZcZJchzP8GiVtj8ZwJXfLhpR9ddCwNvuZP9SA\/onrei9OdOJt6WIN9hIK0kWcJoX1bIieXLIi8uEoDHmNtp4bqcX182pF85gsHMts5LL\/OQhnowVz\/Qer8cqUU+UFWPjEw+2MT31wsLD7EZBQiYm8Yiu5RDb2Prno9mp8BFtkRV9IxNWi9Hnpcj9ZwucrDJx23iL1\/v58+BnzSpy3DFW\/EdIMBcapKsm8blBCm4VGyDxJ393GbXGvBTe12TxK93uQ2fLyT\/pGCsFrmt01T7Xh9MMju6eCe9HkeTjzqz6Fk7ER1W9EO\/HgUsr5028JD6w\/+6DoCIVNDv0Hqoo78GnRQ8sjj\/twTe3CBSVLCll8h44VG3UgbeaS1Q22fdDLGEs4YUZB9qpENa9jL7bR4jbR2QNYfs1UbrsfGZ+gA\/fu2\/agitPT5IjkAAIvbky1c6fwuOrY+nrBXrjVna6mTw1gnliYNH2TQne8vub5aBaCCszOO50k\/hq+3yKM6FKHV4d+eyAbP0dfWd1bTfRpgVd+LfGnrrkPCquz2bD6eDTh1DYKfKsHtWVKaHDotsYcCaDAdX5RsBWpC9Hp9Ki+PAqL6hMjmLpk2ynEvSKVwg+G3uQRwoXKuRFH7YfZEJgx51EQ0bnoHt1doRU0Wuq2HQu9z8R8yvezuC8L8xLFw68QPzRaZ8MWE2VCFne+KP5ohqGU6xQdXoof55c8XiHMRPKbmgGujmaImsuNnHr439+jV60MXrEllYk3lW+kpcu7ISRYq8ouK8e34QhZnmwGYtZ7tkeuq4PRL+0Fc+RKcIPXSNw\/n4GtPGVbWkPrsJH3ftGfLSXweCJbtYjUkWKDgVME8bHnEZ9PbPPuhOo3Mce\/90k39XuOG5I6T90pdeT7zy7EakckzCT88PJa8Cf1FOJXu4332xcMoGI6ytpwF43J1WOdebMovD+y1FQ0sQXz8m5dMiD6MN\/B1msn0Z276JuUO9qNstVnURpRi1UvdLmsfrZixzNlaSb5nbqp+Alvjkoo6dpXvdzYjLcLT2e1fya57+r1isino3ji7jcmqs2AdsbCyCv6NFizV1zMlhvFW42tmbF9Y+BoLQ88o0Vy27ItL\/VI7t\/z+fExv71jeDo3xXc+0Y\/zPfpPz+xi4vcnsYumB1kIebVncs09Goz13y8a3WWg7FRNgl8+E19GlovFuxD9CllrZjXFwMR51wqWCAvVK2PfmXrTSJc6U+4oSeriGWN+7qVeKFornPbS+9\/vaxTnqXi5NDIQJ5IhN\/NHPR7MWtFa8KgE9Z7zldWJj19MGC0yVOzGkeXvTWb5l+PMee3wg9MMxE6v8fhs2YSEHZXLLq8rxVB2uJni2wHEXdT94WszDEwoWPXXknrRECvn2twF2fKPndu0+vFHbVttkB2FoIGp9OVFA+D\/bMkbYD+MqIi9QtvrKDh03P19O7wZ716U6OXld6O\/jJX4h+iDoGa+f714CwQCvbZOyfVA64hN4wLC7VfeuX24l9EKgayh6i69XlyeSM5fuZXCmna+1OKMFixR2V2p\/KoHdRZnY39pUrhvo7KvZKwNawoOLC2r6sVNebWGX7soJNwMcxO73oZDJUfMZ0X1IuBRcXekAYXS7RONO8l8nS2vbPR0Rjsmzf2+cPFQsHLIvOrVWw9Xg8fuEWYdMElzdT4s\/N\/rqHQA\/ye2Wwv2VX1d6efVA0tbS6ftRN\/i7s+6KHexDnyee5JetLdhyX3jJ7\/nkfpuWaI8qlELlUPsVbp+rdi0uHvzL+LjAj+EsisINxeuLrEyINv6yl0pzxljGFgQNOfzcRpDHOkGn27SENRd69N4iI0MXw45NcKBZq1qTlcIB0oynrGOHhvG9G7NcTUBkmeGQmtzDcg20PbG1QGSB8TEDzPjaSQ+Us2OIPr1u\/eCZdE1BipiOM8VJBCf9j8aKTBN4fOXzfGcwRTqnKVfjlyh4AOLjv42omMDc+8+GqDwgIeHs\/0PE2+Vl\/g+HiY+sNwlUvHJ\/56v\/6v9yuou6WfkuLoCW+4c9q7AQv4DGquMijHlMsvyrisDv67cGS\/ZUoG21Ngdi\/WKkX+ryo\/hzcAu3pZpllUl+EUN5GaeKsb6uOyn\/IVNkLYZ1dfi6EZwUK7sInnCIfEsiYOVDRCcmZL2wqgTIVJR\/JLEN9\/cH5ntrdqINXITFnOfd0Ldz8bnb95WEbw\/2y2zHsWPP8fZyHdgBbu5S0qIwnRKVc7zcBrOayTNV5JxZb\/V6bhkxsSy10t+0eXkenhL1InnkRzzNcj6zIZRPFYqXtDxkehNjFmO09FRrAo8cPlFfS0Ov07QZHKzceiq4HFz5yG4zXtr4ryjBs\/TUhO51dhY9FVBzGjFMGzO2F7e3FCD0F9mT67eZyPqjfrb0dsjMJ2RtEXBtRYjj7Iezp\/JxgxvydkK+4cQ3LV4zqhcDV6ueRrnmsdGQsw7ykRjFNxmJ7f9fF+LX9vjdvETDtkTbfXFNILCqN+nw+\/sSe6ddP14p4\/42XUH7rMyNAYLaw72qhHey3qavD2FQonXidLPhLN3lXP8+OJDwZD7YNREOBnXNIVDZZ8p8Fx9ZGWR9O++u1Eu++v4sjmV8FZhscS0moEvUl5MotsbUi3LLvtVgCmn6JX6qwlj8Z8LVT+xwWPxe8Y5lX58\/PZF\/aLUEJpiJP3i0ijk8alVLm4eQIfDmc1rXIaJj3sfSa2nYC\/Scphxrh9B5RulDpsMYeXz6CfXsogf2yarzcsawpeJ1Sp5X0dgfGzHeOJvMl5mpVO80oNYnWQcqvt6GPfd318eIflisyon99YqBtRqj\/Su9amH55ELzOXX\/\/t9UM5HDt9uvcCEwwN15z8+nbgx91Ko6u8yrI93rZyRwwAPhl7u2VKHss+GS1PXlqAg23GxaToDF8s7VWOmalFWPl3ZsKQEzTsacoK3U6hNOfWt9TADDoxtek3RdcjcxzHFuZ4Ji6zrMzZNtKJ63uaZc8TL0CnBb\/p6IRNCYgeNmm81g3PMpTDNrRSlmgH5\/qT9vH3vvUs3mnHjeJHgItLOd31VyMo6Bnj3vqdef6xHrIbGz+9+JehU\/\/bhD4MB171JfNuMG3HZ+ReLa7wEBgk\/bIxLW5EhsdPo7J5etP2pnPuR6LZQQ+nNoM0tSPRqelC\/swd3PR4lbFhPoZzvMoPV3oWj6\/3Dv13tx0xV967CcxTc9Lt+e69tRiyPnqc88XVGNjvFT5HCKdcne0J3dCDVmEMq+0QfaqseiMsR3itvc+AMiutCp6rgjuyT\/XBaGn8q\/Qzh5gnzzxc6GJCntQv0rBugd9Y41CWrBDWmI9JbiN919PxMibdowhmR\/nHpdf\/NRfMi+KJW3WVi9vat3KtculC062uGwO5yqNGnqLQCBnqSj1xQSqyDnT21ZN+OEtxPPX1BK5GBCCnelDfnauG1ctf2yR\/FSBayLaMM6xDMdBc7m9aGd\/lRYb3cFCKUG174k1zsM\/Sg70ZYIyalDFfe4ixF0Jh7DYckExG34mQuW7VgTLXN7FTmfx9n4MFoAwNxFuZY8fb81OnDWj9HuyuylVAeFQ8uIH6RTY+FnXhHQ\/9yxt21J0Zwe0OgkEAtDRMvbNyQTyNi1VY388ERjFUN6CT50Wjb6eu8NobG4ZliOouWsaDGy4iaJvulw6exIJOGRKnvtQV8Y8h3dLZlEf411t5rqJpD42hxVE1i0ug\/04FqX4no+WcrIL3uza9nrCb4zH\/5MJ9mw9uuZsWcZpIPux\/0prylYX1Z7Gi0xwjeG+v8zCK5sbLg4Y+COBoPZy0qlLdjwuWC3e4YwtHH52upvv77nnDFDVnxl\/qgk6Z0W7SRxosTcVR\/AfHJxoHarOiRf3b8u\/edy\/1lVU7qQVWo8WgTCtatGphgsmHSUf35ZkA5niXwtO8gedJjcI\/7ExYb1i1vLcwy+khOtf8oWjCIa+uu+byOp5B66eui1\/wjsNmpsPAg1xjE4k\/t27ecRk3WigyVyT4YzZOelv86iFlndzH5iA63vKMOPwgjfuDnvfdqzwh+qs+1bJwi\/LNhkfB45BACxhYFXybXO\/TebhVn4v98FxTcnj3txbyT9Wu9+gbQn7+07QDJLYZ+xxtnNtCo8rMQcyDjMzVXmC8tfQQnRsJtbpPrnXNt68Vr6TS0tPnDHOzHcNQ5J2xfDeH+gtT5DMIn3ece1bz7NAJm2Qbrv+890525ZGlrGo0FfIG8mlsH4T5LsOBrFo0TiXWfm1\/R2MK9MdXDewxH+jsfrG6hoP+Te36aJI34SIXHDoSHOYonzt0i5zHacWV\/7QYa9oYiZ\/q4\/93zPwe1bT\/OTyN1PWYqa9laC45V\/XzzhErwMDpkRcgzBo62WyzWla2FRA76ZUeLMUNj3q7wl0R\/J\/kneQNr8Xx6nxgXZwkadgUUXNvYgSQdA7dHR\/ow5RDEn3OQQrXPqtVmuZ3YdWjX01auflTt1WwYt6Ygdn3l1aWWfXhYNHpYz3kQewey4jqiKOxIPran1b8VUsIrFZrX9+Kp4quUuVsoRHKc3K9C+ObixzLPkXv9OLhjVvBuRwr7fTeaRTt0ItDjSx5zqA9VC9oehh2nsCHI9qG0DoVV0krh2\/QZMEl6bSEYVofiNO4VZg4UctvX99nOYsJmpkz53KE6fHZZZLD8LQVvobHoNdIsdCrZLXc3a8Ayg1t6V0he93iQuXCXPQOnVqbZusbVYR\/Ovpe5VYOEmuboacFWpA3t0E36\/d91wXM6zYaxsxZCVuos\/dhWWMq9F7vP8e\/4oc60Y5ZqZjmSL0R6etxtgmb7r67FbDbsrk7IRkeX4yY77sV6jyaYyNz2aSR1V\/dsY1uGVzm+L1hCuzk24a3WlysnSfvdBPcF8wlPLzU5XfPuBxuSi\/PCKh+0QPmsRIEhyTHHzmU\/sOVlYKR7Qf9ajzo06Wk\/suSjsS1Nzk1Zgw2XhoqExNomGM7RvhO9l0bQZcMtZoLEtxK9vr2raMEF128tn+5SYJ7bYhcyTCFrtFTjYzEFztorxaotjVix4umOGvUurHA88DBCioKcnjIlmdOAwphXtps2dcJ82RsJz8UUnklaBszjb0XY\/g+CvDN7EXndSJbaTHJQqWLLaeMhnLpjsS8tYQTPhQ68bv5CcpnRtq7mvhEcPJjKw44fQ3WKgC+fOsntlkPrX+gPo1Hq0vGFdqPI8p6qPLaAcN\/lpbuuOTFwevr1nS8vmeCbwZme6EzjXQjPomd8FB5VWm+IJVyoMHO\/zRWS79lH2TLpXjTM1fzsn5KcELisZHJWM4v4\/eGMHpqCa78M\/1JlMh4vry1+LEEh5HHtARsPGh\/f97NSH9MQVW5QWjnNwj6TMeUtpP+5DWHrDpH+TVYcXb6M5P7e5QEDmrn10H\/a4X5cuQNPhZTO6hE+97mhKT\/\/XDVaNirOLr3eAuGM7WapP9mY0FfieZtUjZocgYq86BYs3BDdFzjFhu7vW5pnNFtJji3dYCfYi+\/d1e162hTS567fkfGmD7xbFm\/uLRrEr8+prGMkL4nmrb3nYtCFiqXHWo11+zG1d5mBoD2FqewRuzdOTDhHPnpwJrsTK7+HxW7jLkfUn4GTTjJMmLx2bLIeasG72sqK8qb\/9nHt9IKATzIsfPwUFfzVvQ\/9xwe2cptUYp7wxUF1Jhn\/U1tvBpo0wjnfR7iNcNeXK67BniuYsD3SoReT0IKCwoyl8cWlyC2Qt21WoaHTO83HZ0Uj9H37lM5LkhPm3Do3KkPmy32lEq1HFNp3\/Rkrd6RhccE154IcDZtLvb99LWlIxcmdLsxhwzW9O1ROpgcP6bOGpzkHYGJu8qryKoXbI3PUXWIGIDSdV7nZaBivNtLvI6spvNTaITP1sAeDXEp2fxQHIPF41vqlHhSCbnSduV1COCM24GTaaxpP05hWbY6jOFaUdnMb4YqB861L\/t4fN+RJmRxZPIbbR6+2qhO\/uDZ6RreS+IWnQvzpHp1B\/E4Uv36H5OSwW0s4FMnWmO\/T3AlqDKG9mqUbiI\/fbBBLECd+wrV2sUjNkqF\/pide1aHzNl2sxJ407aFzTs144F6h4DLx777XFit5Yo6GFRP7JCuOH7jbAeuLm2LcC8rgeOUFlytnLdxOtMWvMm1FjOEFEfcZRK+PfbDoSKjB7VJBrXTpViy+wblY9s9\/H7\/s\/gXxYXOaceA37wenzd0IfHtOd+9aCp+avaInhOtwS5uh\/tS5DRG3ueuN5lJwnozNCZpbh9ac+QEhdm3Yv\/TAcWrOf\/vsvxrnTw3Fnw4drsYDrvhGjsskN8Tg5oW\/z8nXz7xeurcKU6kGyt2MZnBXByREfWPj9hoXwVcSIxC8vdDhFe8YInJ1arxW0JhI3Xcus7sPrfxGV1x7ByHS07th4QsKM9K3Pf\/zcQQRfGc2KASMYXVlkIKBKo0zZs2D+30GYO08w\/SZ5jC4+2zXv66ksF52cnF+TSveaKXJPjXuxfsbwW4zt1FQUkgz+bS8H5KzQ\/j4RIeQ+SRh+aHUv88vBjDuzevH4g2x6wRnDWHHx5ASz2QKiucCh06P9kI5LKDpjtgg6m451L4IoXDIosdF\/DuZp4IJ9n6yo7D53T4tw0XjvcfmJ4ob+rBD1\/j6okODaDhhdnIOyev6va8KdFXH4OKq9uJGCtGDlxKir0xpSN+\/v\/WuNxP7x8RFDLxZSBrYWHjan4ZXwQw6dMMYbHNN6MsZhFNkjxYbH6QhI1g+my+UCWWZHMv2hywkdEYd0n9II+NEsSaX9Rj++JwTftLEwEfKeqOfBdGFm13rjEi9DVpPDouQ7ZE79yVej49BcYmaaJY1DapFTFH3NskTwrJRTaZsBEleusNIocF81biNTbYPgl0va\/0Ygwyt8HUz4XP1X99NfQmfS1KSlZ8dmKhpK3zxuInwpPBImxfh+aKu8uIbt\/8\/OHxZo8TzHxVQ5QrezqXejDi9zrO5n9noVV91qMiwEj0bZUReHWtGt2rD\/r\/vC\/2SlVx6yqUSTr8DEle7NEPKYbbwPVLX23bHVIkmM5A4WfX+e2ItjDk3nsyd+9+5vq1KVXtMnQkvzwUxOv2teG+6grtSqAwGy+bJvApigN+5Q7bxZDWUdn6bpfeimHDDyXlnihiYITVbyoCjHtZGym+2HS7BNjY7b9cwA5e7446LzG9ER15ZAndvCfITbsSvffX3fskp8+usARzNs4+1eUihwPS7Vi\/R4R3So44BRIfvaR\/sjic6PCcwGMKtLIzyOOyZ85CNA7lnL9YQHZVv3jsQ8JwB39drtFObmLhQKLbA5yqZ\/yr2e+9ZM2AlXqQRF8GEA6vqyZdLNAJeuGukhTFg8VLgxOwyJlS07myZ7fr3u1TCm19+YEHn+G7u955s7HhYLdKV8u+ey\/qtuFU4IrYeATI985+IdyB2F8M\/hnCTkEDymlanekw\/cGr1ZbRjVoehqoUABSjRupUTVbi1ZjkXp3YLPjpfX0VPspGrwtced6Qa7eUZumlETy4\/+47L\/8d74DscS7mPSjTg0CvtZ8FhHRAJ9V6ySJRCxfxIbcs91YjYAJ8EhxaozF5wW5v0o338ev8dkWpw0s+Ht+5rgfmBlcVnCCd+ftzn4EVyU7CzWdozkpu2VVjx73oxAiOnPVazKmm4GDyd9nlKo3Trzp3mkSS\/8THuHSK5aXv4zgNskpsWC61dqEVyU3Lfm7rfJGfNiDx0OpnkrPZLXWLFx8dwKtBGbcqbBuuMs6B8BPG9M+0bSt+xYK9bpnfiJvH7l\/uq3pN2f3eDQtPnLNw71xH6+jUFyV9duW\/m0ohbKjFvmwvJd1tnXrG4Qa7\/Yw\/D\/WT\/T442m6\/msrA39YSuVTMD7FtSv+xEGjA7uPOjQGwJFnoaLY2pZYBR6BMzkV+PQP6BhXN9\/4\/1LhXDxda7mNA+I7CvWbMdneulnEbsy+Bm0nZL9S4DyYHh\/Gukq2DiHKoo5FWMJad5OpJTKPjx8tks\/MyEzGWLl1f66rGnyFVwsJfkYPPfJTwhLLTOfLC3+kgj3q33Fl5BdMQpVJVtrUS4cSondZdFO+QKz70\/+54GveKAues9Glv17OfYKXVg5v0CLq0PNGLnnhYvIvootImjI7mkA\/OX5Fy130ohZ27VQ6QRn3jG29sCGiK+UxcyRWhc6TV+JLybxm7D2ft6Oti4pX86T0qWDUtFg46uejYEW4QOnCdc0yiczqz6TsFTe0yFW4OGbbqUqyLh1\/1VXJ\/X76Gwt2pWzoJcCvyHZsZ1EN4yatJq\/V7LgsHtzz8O+bKhXmWQuzzt39XR6eWRfhK\/KpDUXSbYrNEMsY\/HZ5cQPXSduzP7FaMCfGFH9WTXNmPzkMKwF2l3K\/Ie19lP42vsaye1JRRszwsdXE1GYlEa6\/fFixQ2vzu4Jl2IiczPq9yfMesgvevx+RB3Gg68nOePE58Tbv4a16bUBuW0psdfTAj3azloGUkT\/+u65Lv0awv0BmKvryC6QtXPc11Ccs\/8t3crw3taccVeQTe2gkZWbdSmvFgaSs9CDi106vtn49AuoHPx8ewabM7sMD5X24Jqba+i1mk2rnjqnRozroFR4gHehT9a4Hzsksf4L8LJP\/zF1rGrCD+MNN3d1IK4lhjJFqIn10\/Z2GlcbSD+dbF6268OiJ9tOV8lTsGNS+DbRH4D7r2vS7LU7YTcE57olySXKaSu0d52jQ2RwLl8qdojYLoHFnZa1mKqT5vBtZ7MA2GTq+LSDPRN82Za+9RBI2Th016KhW4X9auN84cgPd9U8\/DnahyZX3\/uBMnxy6oddopVMXArxp4nqLoOl6dk53z9yEYt\/8SrrqOj4Apt3tpUXwuWWaqIvygbVZMq5s5JQ1iUmWRgfbEGUVXLX6jPYIG9vrRzSW0vdm6cF1fSWAEtR7f+77tZ2KEdsilHrR+y806kx3ZUgtZ0mf2a6BaVrG0cd20M9oqtuS9InTks1PT3XTWA4yLU+AXmEOyX2niOF1G4GJG4eOvWEdyQ0F\/cKD8Gunfyq7kMjfPRKx9n1A\/BcosfxzKeUTxa9fjwzZkkZ0y9G51\/qB\/nXnzjfbJ1CEJTJ\/qLMv73dQD9sbzpJ631OCeytHjv3g6cz\/o0IiVMjsd9zY7kAy2oPJI51HCkB5Mae7m\/kXF\/9b5CZ5ZUE05cPvrC1KULKseKBPlXkfnutv+FiEUj0i7KvJOv7ITGcdOLr5YRrguLojvqmrEsUMMzjt0NKzufwcJ1FDTk7pctLWRC8V1ps\/npHkSrZR24y1WBzWccHAduszGSFFvw9uwI4vuOTvo51OJGUH3fOQE2BmeLUsvChjC6\/ElBn1UN1p9Sem+0hA1fU\/lFeu+G4BDRnPLcqwZ383atlMphQbL1+NQOwUFkcB\/JfbmxGhd+ia\/0zW+G\/vSMgIWd3UhKHNSVIMeT++3A7bGOXuzaN6ZyjHcQNcPqMSnBFOw5g64m7u\/Bq8VCEztFBqB\/zEQj2o1Ca\/iw0KaaNqx3s95uUNiL1BTGfuldFA4z23MLb\/Zh7YeE2cJhg3g0sKFsxVNyvv7bHEbCm+HpZiS8oKAb385rJHGoUpicMBa2ymLjVW7W+xUrR1F7ZPdw8etaDIr1Xtq8h3D6ug1r5f2GsXe8f\/dJ4Vrw1Lk\/3tLCRvPA3quuz0YxufmTXApVC6kS\/y1bzrAxe7ny2PqZZNx2nxBZtLUW4n\/8e8ck2WiStucNLR+C2y75MO57\/\/v3mP6rPW5V0ds\/tgyEn+H5EcxdBgvN1TMEZhRD\/WZtc+RJBm7m2W4y7imFVejc+dU\/P4Lf9CCrpZrwcL+239\/n7rI21j2dqu\/HwoNt2kaeNKJHYu\/7ZlNwd7pf+X1bGyzsb8h7En\/XlrXJ4HhJo+yF3bHDiwcgtWnfyCLSj\/\/G2Vs4ntOoi1SeHeFJ6iH6W141ae9Sezvsmfh3XST4imANyRX+ubv6C8nfu1ur8zGbhuq11LbBgn+33r4y1Pwu7\/EK3NH8JmI23IT+qcI+f5qN6Mfm2lxFFTiaXV7QKN6MMVVd6tsnNmwqn2cN3KjAuqOefQo\/mnAwWNdViLQb6sZf6fBmY9kJtlnR4RFke3PrC9jXouhuDt3UzoKW7sNVDamDkLMyvuaSXA391Pivy56wiP9nf4wKHcDns\/YTXr1V2FgXcniBEAtc1QW8Kmv6QAmk1P0WqUT+hsjepJcs+NYXKmn1DGBl14UFp4SqkcEh9e3tOBMXAz\/I\/Qzoxe76xsCW+ApEzt9p47uWhS9lX97djOnDjC660\/FcJTLfrddbv4KJgc2RbLmnLdgjz7rq87EUNyeXpLvtZ0Jk90Pj+c\/bIdh131biZhnOLt20+hHhduruD6mFXPVYdGn5iW+E25PFxHYvvkz2\/8IOWEN0g5Hwlsudtxwcmlr5Wi8Z2G58cc51v1qkOtbfjZlZgqIIKS3VEsLXvIsV\/Ag3lBsOqFs6j4L\/isPPFHsaHpWf5bIJt3x\/UcLK3sXGKf7VbyL+vg\/\/4KfpMDJPqHFDxzffGCjxsIzOqKBQqrQyUZpwiocC7+6mQxTSEjLbz+XR8OZSGEzNoLGlaUmc0cYxWNY4MpYTLl3n\/YfnA+FJzZfCFnXPBhFsvn7wRDkNCeWyzN7cv+\/3duc6rDuKqa3nFp6tp2G3V\/KXCuHYy9MpUzr5I6gxle7Sa6Fx0HrbhRjCq74\/Z7Qb2w3D9W39WT8yX5\/UmvdkJhEeSxQq49vHQNtTG8Uzt\/txNih871b7IYR0B4ecyqEwt35I++DxTjREKX3K6+mDf6MtnzTxua8LbXXL6tvgmX5oVuOHXkzeUzfUJboUueSsvcTlXlwOURGxyB9A9b6z1o1+FNSMdEauzW5FwnTE5ORkD\/qO3JYI3UzhaM4cix0zunAvXYN\/hVQ\/Ds25r65wkuR3b73NI8U0xpd1dISTPJqwrnTi2lA3DnGFZpqScVjwXkXkGxnvnQFbt4uN9YKuGH3qf5fUqbTy+bJmCo5p2i2jvm1I+kI5Tb+icdhSfNU7cxrXvhlnrHnXjkcvXrhxk\/q9PzN9dlcCuV67titquPZjpYjOj1wT8velFDaPFpD8dizkWssyst+vq4oVPGxcfH2ac2E+G0+r33s3Z9HY\/3X5\/rtPKOgtXG6aM0Fhq\/Y8xmQC4SnjEok93hR8V8wSGCFcnLF2VlJyA4Wu6Tz9ZZUU+EJIfCPz4aC4D\/9SMh\/83tgvfuRBY4D\/4tvixzTkOt9H5kyycLZwVeSDvSzIvx+O89TpB1VyyHr3YCVkBtwOrslhQkdfZQaTvwfPZnrw7x4sx5U4HV5hBRa2fVbsanvUBxf1mPw79pXYI2ov6MLLhF3HTnb4xWZkiYbPGnEpRaF6ocu8rUyICaQYi79sg6811S+iV\/afOsw5O7Lecj0LTRcfCYnW9OFE7vMA1QeVODllO3d8FRNtNE+F0nQLou7WMy93\/Pc66v\/a\/kM3Ne0YJwuJdXt93Lt7Ucjr+OhQTwUs1Z7H8ZAc8kBZ4pbO3V5MGbs\/WxNTgeDHOa3pfSw8rvttN7N2EM8kBjutP1Zjnu0jDcdn7YigNTt5l\/bB9MjqU5PGxH+Vy2THBYfh0CdjJYpRvNZZNnsOyWGv3QPfH60cQoGPlf\/aOaNg3WUzBmfQeCe6QXWR7ADcl09KDhO+yvd9FPiL8JU8R0dHYNAo1rYuv226joGTe0sqfurRUOD5E9akNwZj2lIh9C0D6t5B896akfnotkoxs5KBdSsp3gxyHgvrbegBwusZMiVv\/KWGYJ7MjhfxHsFRpTlr5D5RcG3zjT\/vN4LPFx0TS2zG0K9bX\/hOgcadU5rvrhUP47rAQY+A8lEcNHmXWy9O5nWFqOvoKxbix6nh45fYkKOT3mxJJjqlWuSQDgqxL2Ut85Io+DOkRRvIcUr5rhTIPUiBc47YqRPvKKSsX2TiJEHj3uG5UdydLERz7fNbG8xG91mZWUqv\/t3zRWIL\/F+bpDEQ\/f6uXVdnLfyzdsqtFi5Bj6sKR1AZAw4hOq2+e+vRoLbgLdf5ElSs\/rq0gOi8QcD+WNk59djGz7Xv6pF\/9\/2LCPfUik91FUj9qnxdenkzSiuNE1eT\/HXQa535Pt9KFL6+NzvSqxkLL2s9aZxgQzb4hImtbi3MBrb57wxrhf+FrjJ9DpIf2t6\/KLxVjrdW6aZRF5rQ+sFTx4nFhkOK9mjkzwoYlrVN3vy7DjbLdDyf9H\/qeI7yrKRqFMncDTWLboFTcvj6gCk2JtfHa3VtrMVP77JOS\/9W+EzvrhIg\/feYGkfHHWHi8gI35bv7O7DvHV9Ja2oZzhzU5RawY0Kt8raD2VAHUjOWObAby7DR6tmgWRcDZjaPVJw8GqAwtGmqIL8Ei+2nTqdZMCGbY14qsKoDvnPrjno\/K8Pl3u3OS\/YxIfrLRM\/Gux2XlE98n7paBrm7P5dN9jVDSuVQUvhUN3bYxelvV6MguTpdaaihHRf3Bf+QV+1DjHOcwYUDFHg\/yS7jiezAlXOrelbd7YO8dZway5xwfo8W17O+FmzdHZ3M29YDocfuwae0KBS182Yk7OjE41MPNR839mHzSoa\/8d\/\/26ZTjGJjW6GSUNLoo92L8BDn6rAtFPJ2f3rT0TaKx6U6a5LtGMjbY8Mu3U3DU2T5uofrxqCUaOh1L5WB+COiUQ2mNDTS6\/avmmYgpH2K744oCwHeC87be9O4wL5dMcDBRm57jMXqTDb2dzSnDmbSWOPuL66lzMQZt0qFLh0WIuJM467coTHKv6lo7DaNyL36eyojaexd8\/pLhDsLC47kKt\/fSINrqM+s3pZw5aR9pWIkG9cWbnNTJr7Vym1ce5pwAuO0a2f1LwaaVw\/7dWjRePD5ruCOU4QTijM9w8PYCOIMyZp1i0bfgp15nKT\/W2sP3+WKZKHDSkz5A+nHfegg33PSj3eNve7RLwy87fI2NSe+udU1I\/JcKOmn313q1tluKJREL58tT2HwoeDAza9jWF3ad17YuQ62Bc7cxqDx9U11WGgTGwobz8Z4a7XgI719Y9cPCoapz50C1pPjvLV74BUPhbvSFaLbFtD43bf12nyiF\/ciXILbmGzUdIdbGBH\/VbHnXVBOjkuN4SI2bMrCtfhcE+EUki8Lly4JItsz7TrZ8+YwkPL42MPzRM8i1c6F31Mmx6kp5xa7hOSdeI4eHeKDM\/QyWqOJD7bdTnNz\/83C\/U0yQ0GEy32rvyffI\/pVs6x84pwSA5oi3rya1mw43fyzq4TUg\/KtpV4Kb2nwX7IKekV0NFZDNG\/6EY1vXzReHxRjY8GGT8u5yH7peid+5rqT3Jjh\/U0zlYblxPFl3rw0Ni73O\/2DnFfWGqF7+WNsOD74WWN0n8ZMfp5UxxgaX46O7wwUZiFk9o4NE0KEjzIPKbb5UjDYebZC6QGNoQe9GtctKOztU5pU+0BhuVLYsIAoOV7brFkN5HwPX3t1q5Gc70nVAK0Z5HydXruu+SpLuGHFH8mPjykct81N3neWhvWww+5Ekr\/v3Unts9pMw7js7SG3P2zkhKcecsoldf9DzUOfm0bKj\/YbXJf\/3fMV0YdfrhcgOeu8lepMPnYpBqtPyHtPfwS3\/LLev98ZXbYBArFRpYiTEM76Pf6\/31f6LXJ+bWxxOdbypfu\/CGyCnvm90+ZsNrZIX5I2JOPrqXXr\/k7Cpz8LzafpdgaqrmoO7SLzubdkvYki4XBjZ6U56jdHoZ1tm9dJ5tn5+MVR6WT+T8jH\/soZZ+D+8CeOlI+En06ax7BzaCQ6XpJ2fzAK+f1bFnQQrraicriNSD0zfIK23f4yCJ2zpbu1yPW9ZCjGbU\/+vr6fz\/diERZcveZf6JiksNTPU71eg8a5Lmid5P134yxlt6yky4eB2Kao212LqpA0UJZd4VEMnZ9nu7v9iR7wvHbWGK\/C4f3HpiIfFyPMJ3LjUuVGUL5hwV\/jOlGraz1r\/1IKW5h0v5x+K6ZlfvBZivdCU1via7b2f6\/PHF0166vQZCfoRae7A5f1Y5DrjTHDhtT5uVnmtXoNiNcyz1Mu7oDIr2knIzEKK8wutEmFsGFkmnJ6a\/wICjetLHK\/VQsj\/rWH\/b+T+n5dPha2dgip\/t36JxfU4EBO6Nyfd5iw9Vm09OLZLtD9+cJSBuXwtNujOV1HQX\/i\/byP1izIDC6I+81sgOGA\/WZXZzb+H23n\/c\/V\/\/9\/lQZpGSUtKSKpqFDJLSOlgZRkN9DSTlnZicqoCEmJsrMykobIXk977\/X0HOdIElqfR3\/A6325vL6X1\/enLu4d5zzO43G\/32+3q7Pu7FW1ficziKt8Rk13DzNgI2hy9lYQF+bes8zrIwbx4d7Ytl5PBuRDjZ9esKVRs3FHyNtA4r9TRypvb+dims968SjitxM2eU+u7ibrdi1CRoL47QqpJwsZ9oS\/xGlDwWZSj6Wmldf6KRzXrz\/V+Yj02zZK7MFLGik317lrhbCJ3n4ZtiV+3ebnG\/0ISRoTljZqr5WI7lwrVH5BjsfXODz48gX5NyfWded79n\/mN3hC49lmAhVY+Mdv48nCBlzdLRAb9Y0LPfsyodCCCiwzybLNWdMI+2cDn7XGueDMmCrM8+zv+\/mCLw7da8B4nIyAyCgXrhd4fMrXNaDdX2RKsnkHcnQ9Ylw3kHUU23o6+WcL7k4EqTRqduORbNvER8I591an\/BnTbwNTklUl2NyNrfkTz2KIzsqNGpmsCeuCeP+kdmVzL87t++7z6D4Fh7VyKXHEP49XTz24hvjnrXXvlSaJf3Y7adF\/pITGZ7bry0uET0sH1ZYPHWKi+OiFTmPCpW7e9hX9pO7OMXKefuUbgnlJ7vLln2kcyxtr2U3q9Jy++OiVeCaiA6cdv0u4OGKCR+sd4eI94uHOt5WHMA+Jq9cEc6DC57RfzYIL8Wa+GU8TSF\/\/qKe48QXhyNMarYmkXjnTF+VnEx6TD4l54uJFI9WqKaX8KY3d72KORcVwEFWUk1FJ+oPBa69a9WAaol+k9n8Za8dXd\/2d\/KTPnO7ulssj8cWxoVkPZDpwRfPKSsZ8or9Nh6peK3OhVbXYbnVdPfh6Ty4Kyqcx9+huO9cH5Hw\/11k8EGzDT81OhS95NB5dus1eeZ\/0oaT075tvt8LKbc\/8OblsbM6vmuNt1IkQ7uXhZ7\/\/+X0gRx\/Ns\/LXZkN9wZFvX3ha0K6oNLzNtAQn1tP2R7YR\/yPT4Tos2AX3o+oTqv+j3h+1xkfHG3NxerAk3jlrAAo2X0TkpBgIX3nSfibpu\/ft4+YX\/mDCeVNhYsaCajwN36G4ezqFZZXrXw2ZDOFI8BbbHOVqTPm8jG8P8Y05DrNfnXStRcH4+UAH4htPGTj75VqxwV9S43wkrRVaSlceKRWX\/Ov8N7HS7oy8XgmLjFGXAs9GSPY6TS+f5ILfkBL8aMRBKTVLMM66ByMf7vKH\/ynHnWOLPd\/u5+BVGG\/6Pdke\/P4pPC5TVw4To1U5efFsCL\/qerU+hKyf4rBFQFYp2I2\/ZFXYbHwwm57acqkLzpxzvnl+ZTCaf40xU48Np84\/vWcsW1Av9iV1mm0JPipvfqtymo2m7TN23WlqBfMI7\/F31SWQmy9weCHh68lqrxedhK8f7Znxy5fw9d75E\/evPmHjba1pwPaFHcgViWiuIL7fumO3XcIfNhLfqZa9qOhCZkD87O81ZchNfePSf4IDMa3n9lsCerBjm4LRmuUV+DDt2d4Isn9jSc5i\/afdKHmcd8PYphwcn+Ki5bUcZDAyL5T69mHOvb5p2YGVkJDWyN7a3ovTsX5mX5wHULFCowKk7+1r0eHbK9qNQF8pJyv0Ifzx8vOXwojPWGQRY5HfhYtlltq2k72QtOtb\/CmQQkp97PuejC5k3748153uxcLUK1qpDym4+232nkbO\/+kxscDaqG4cuxJS986MQsbNxLZPh7sQFJUQERPRi7NxEjWz71GoCm2RCudvReGdYLvOvWT72zsC5Q2Jnw9Tn1Lf1oILd5YXzFbqhpjPuvXvCBfITrf2f53bjqgZx1wPXukB3wvX8LcXKCgl\/eIz5jBR\/Wt+lLgdC\/vXHC2P0KNhUhPfLS3AQt6uuiXfj7IxfSz+rN55GuUZ2VcvM4kPDDntusmGQt32gqqSMhrWMXFaK5PY2CjwjHPlJQd+X7dusAyiMdTrrJBN\/FvYyCvmK+LfRPQyeB8G\/Hc8e7YjzXq6PQsmwQ+NN42VIjb9w89LOwqhFVx\/7ZczC++ia\/zfvCrDYceAuTqHC9Eg13F0YyaNMu7KKl9rGvWhzd0CzYS3vrLkOopozBnMnJlAfGzk0+l9dlmdmDg+zrSpIn4pWX5rPemD1pdvDh8S7EVUjtmijlLiCw2WeooQP6N0u5u1TaIbL+K3LGU00WCbDdsMEX\/stm7KlcXzB1Hs9WnRmRoalxvicpQIz5\/uUPZUMezDWOa6jVYGNKQslX\/UOxG\/n1OfkneZ+AdWV61XLoXSa9uPVBEOMD0oEfzpPOn\/r8PcZEjeRYeJHshYQsOR76yQog7R+7Cn46tnchEsf7zR9w0XRmcqH+4n56k8ViS\/ZTWFx6csd24LJfNfdmCK2XUa6hsdGQ1BTRB90fo7YFsXhBlqGjKE7w5cdb8SMLcdjfOyZKeu7UF8eWtw1ikKCuYvSxJK66Ab+SJ5VLYdhSsbzJXJfmdN6s0zy2\/CikszpffodIG9pM7\/iSaF9NE+l3TLBuLvxnWW+HcgOCggYo88hQemi9SuZ1XDoXPZKuuVLahJ9JUYIryT5yfbcq+8DG7y3\/fpLW8Av0gj78Iv\/919ZerHo3YGe7AhYfKiwnZzO\/hu9r+q3VyKHdavX6rLsiHbMOeS1IYmbNRbayvLLEZljLas+6Z+JMTmHs7zH8Q6qVlGsV8ovLyz49jba4PoclWYTNYfQvDW864bZWnETn3O8Dk0hM\/tXo3villg2898NWRMY6PUU88tFQPQthfjqali4nFh6SpnMRqdP3rPFjey8Lahp8x7ko0hm3emI66ED1UvTVxMZWKBVOMZsb0s9OuL+n\/aS6N6R5\/qNJLnp\/QzQ76TOku0MtNl3iC+LDQ0+bcWGxE3NispHuLgDf2p25fwIadkXFz\/GAfx2a4B3pu4iNy5XOZkNA09rmxY0Vouug4\/\/vG9josmRs3rNOL3hUI21Yk\/r0DEu+XfA4QbsZQxo\/nTd8ILuZFvZcbYuLmZ8cE+sgtuhhKj21+XwVdOKlbyCwspBucPFKfWQeTsRMADvmKYH7jmY\/SdjRGXxZrtMV1Qu\/t7XD6rDIfmR7hNrWbhtEmOwfv8GkgecN5p71eEH3bClTGtbBy79PPK0rVdWLo38FGecRnOOlqVKzbT+GOUOb8gl0b44UGbvO2DkFgH5ntSX9k9H2\/mkfoKZlfImM4axGuhrRtelBOf8PRWYRfxmTFaadL7e7vhp7ld+jHxCZr0JpuYLBqzHee6BeQzsZTp2bGL1OO0uHRLTiqNDMGXL9X39KGNP1p+P+GXixnvHJYRX5TwRUCoLKsPf8SKf4n9roBrRcin87saETOj\/43wBBfLdB1EdIQrwQ0usxY92Ij1UYsirSb+WX\/t2jw\/j0VWYIpOC3VbpBH7Qxk+xWSeR4zaQvxOVcDxUpyf7lgDVhR58A6PcXFwdI7013IK1G6tlGKyvkd6TaZ3fq5FjWE2Y80MLiajP+RePN2POEZmkLFKFUJXnknp+\/vd+A\/7+1JEWdD7vP2Iya1qrNZ\/6Rw2h4KOd\/QN2mkIBfMbaiW0qnF40a+aM1ocqOX1JHXO7YFLWdiwyMdy2Pb+SDQj\/e4KNTd5tjrx7VRJ1TfPFky2PDAMX0djnVtNveMjLvL8QzykEhv+M3\/uub\/zmw5fNdJNP2san22G1Gh47NeZxCdJ35j+TYkBMadfUbp+TYDYySd\/nxudP\/ms3+8I4Ri9E3fsk5oQvyk7sW0qhYhvfuZFnj0YMr25WedUP2akSwtLvCHzeK\/evTijF2+e6Pxmmw9gRpz30GoGhe++3y0Hv7Zj9kV1TbHbPSh7uifgwyUKjyI1ld+p9oEn03j2ksoBaNl1D3NaKGys5o7JLuuGFl5uN9Xow\/kU1doaovvStwQ6xXI7MXlPO5Sp1gsHC0ZDqzuFZL6wVrf8VkwOhQiNPO5G54cpgSJE31n520WPCzfhput+KdepXcjlNhznA+m3P77W6SxqBJbVpFbIdKJigYD+hCKFE89W5KXxNSBqoHFi984OpD4RtTixnsKdfJNYSdFm1Gvv7fxzpQvBx+\/O09tN4Xyf2a788gZkjq2zVxnqgMqj54dCSX68yfl9Tf1zI3Sf8fGGfewkXLGc46jy7+83kNgo2WiUzQDr43eO7sJmDKWUMRKn\/3t+r36Zxkm4xMJRwYUzb34rgbGWxSPbZYU4ZmqaoX6lDAEjjcLtVD2uskKGy2kueh5nPZ9ymsSvKN2yH6qHzdHvATH0P49z9exmweJfDAzsWfBaxbwZVTKWkc9IXjHntJ0RuFyO5LtNavnXGjDfUPD++a9cmN71Xb2EHkAIq23GARYTTv7GszuX0dj\/69XruiYWLu4UeWP+g406uQdfZ7uRvr2Bb+J93xAWJYdPW7eNDfNY+egTZ2jMutmv225Qgf050JrGbUDH9DDvZFLXYqep7EjZGuy7pa3uFtaC70ILJpTmk3k7blRk+qQe64VOXg\/sboe8lMezgbUU7h80tomfVYPGnpU1H6+3oOfdnPlb51FoaqlTT37DwjP72LjSA9XIOCdzYr\/8P9+HttW9wXz6Mza8q2da35frwB1zj5PHA0phO0FLLe9hIfHitYXvS2uRcW3xgimMIvDb7pG0msHC5fmJO68fZuNg8M7D721oqKrOkWgh8dy3XS+qSXx0muavYhKPXN5qKu\/JQmeaeUF3Fhvn2lcemLCj0WK9iMOeN4B7GSy\/ke1MXBFjH4mY+d\/d38XL2vDb0L8Miw+4MCR\/18N66Y1hxWEuZJRU9uS8LYPMZQGBr8IN6PuiLlRP4jXTeM9uv9OOpWZy6ltMe3AlxPNjEPGz5WO7d2tqd8FF0MXzUHAvduW9wOq7FDqdF5RPfqxD+qpO\/jSJdlxWY8h2ryJ+zNwz1TOuG\/cfryvbn9GHz+lymp3RFH4X2Bsv3NmId6HrelYc6MQFUS32rr\/3OQkFKRaQ+dpiFai\/+1ULCpJ\/ucreLkGRvczB5+vY2NX7fMcWzSaw+eTiz3KLsdXn\/c+LsWycfOPnLOLRgZALOfurkkvh\/dZF8QnxAbkKnmarczoQ9fxp+JnPpXh38ov44f1sJH3JVnGTbcGcVL5X9db\/fJ3xQpK\/5Z8pxDdsTX6v2NQFjUM35r5rKcPo3EjHPVfZqOiojPe6zoGEqsfeIn8auw7LSc1QGIJ6l5OhXxILm9ij3g8MaQw+Du\/2msvCFwHFWwxjNjKPylbfI7zwWYR2sVNi4rV0rVUNawjslYnOoao0atovfnyyhvy8bc1Sm2gWCvNPd3ofofE8Ky4v7hGNVKZ87ZafFI4\/fWm3pK8Zm0eUDsjsppHe2bppFlm\/mZsf+552aASf8LfAgnk0HodFvNq4hYs0EWOnOeX14LZGOCwgOvXuscHsF4FcfHZNrRuMaUBD8IyWp\/EU9vqqJ\/7oZKNURkFR8m0NRruHP7z+RkEsWEpjZzsHp5yp\/a5T6rE06VxrehXR3eBIqb3OfZix0GvFYZ9KTIn8MO3NbQ7Ym+uEzyj1YmTdGsW5oRX4ceXATmYcB7sGPL5E1\/RCu7XSe+3sSkhW9\/v7EL8R7+a8\/ibx\/5amfqH8Vn1g2kXxbXtHo+tNjQtvBg1+zcwRZbkhJHjUPlRvpHFmR+zqYPL\/wrIetsKnBkB5R8S7O1DYbtnuFdxMYefXBbe0+igIh1pNnXGZwrlgnh2eNRQstAweG4xSsF60SnFeMweOyfkRlQ+50HNl7hskfmc8LsneiJzv+Swzt81baDDnX9QyJJx25hhTYrCDiw\/yOfNDLCkYPHBr6yKcM9lqKPbg73uU3Reue21L4do0xWU8Rf++fo+qJfGn\/KxE66kX6spljfiz2zY0\/ScXMZYv9Ez2VWLfe7PGGRca4az9eff6SeKX+M7VuPRWwsxkk+eP941w6AkpO0q2Xyb3zjSf+MA84UOXqok\/XKtxjLH\/8CCm+Wp2lpDxiid+02Q9p7Fbx3Nj5OJunHgT1LOLxBWlT4xVRfx9\/+SAomd3F7qS9245GEQhqvR4aBCXgvyB9hkDmYS7hbQScnxIf\/0UO\/iFzK+Z6tahv99RfK5bPO8g0TfWvlnHNxJd7xRUP\/P3e8ai7EVrs8a5MNvx2L3UjgKd6z7t58f\/jnPp9rmXvUh\/LlAxO8hTXYvgh699AqqLkCzdUWFRSuon+rJVjlkNcsQFfebaFmFhVCnP1\/s0iiTt+72jCO9+KY\/qGGLDRjL9zFzCAUGT9xyb\/34vZmz83YsnLAje2n3lbj+FK\/XlP87K0PDb7C8puoECP+25dEoIjZvF9CAf+T3rZVYGt26xwXtEJHNfEoWuMU6YIg+Nc47zK8LvkZ+Xxc2W30Z4+eRPhT2fudh7pe5sFPG5dLqWezTJs+M3olPG0rlgeuiOGI80wDM0bokg0dUj0aVfBE5w8SnjsPnxTQ3Ynyg7rPOKwjeXebkCZNx13vtOzKyqQWRolK6uCIWRy8Pz7MOGIHb77vfb+tWIX6G3LFeQglfNwvOH7g\/hR\/LMkDM6\/\/79kKzYN7vcVpbDU4Mq+ra3AW+32MTsG+GiyvOHT2IvG5IHdS\/eIpy7RiLw9y3bsn9cr\/yImj8SS9g46hkZvkepEWqvrvSfji\/Ghc60fXG6tWjbZ652ubIVC49NxnuLUmj4kS8Uo1+FHEZmjNV4I7oWPGVxf3FhIkR9iMushddxYdn0bW2Ybn7p5o0lFDiGYs03ZtfC3X7S\/LNXK3Zssg8MXkihvlJYlCnSgIhVC3+27O2A9yrHLwXEHzrdnpyx7Gc9UGT33mNzB0KX+D\/4Kkf2k3v4ydvVjajZOBJ8fksn9nqfK7ZWIvlf78AYMmuBZHlPtDBPN7a+cZ2RepDC1V1Zy5dUN+B2hZbrH04HWt04H98RP3lYXfyDF+GPxHlSHZ85hB\/vlOwKJ+OPvvBRk7u7FrwWs1foFbaibMdHbT1yviK6GUp9FTS2+Wju842lsVIsq9TsXA\/OTvC+e07qunaP13YvUj8RIuY5x38O4Ks3n8ZRst331T8LW5RocI1CXzmdb4FtQlekXRmNB0LXBY+RPJ9yYWT98Mlu3JEqPf6FcPDJS9aWAk0Ulsz7k8wIaIbgL+fgBQ8pTL+gFDvfj42xOxUezKU1uKGnvLDPiYZU8BN9rZfEf8tM5e9Y0gwzL2vd+EEuXKuEMwPPkfzOVK7OJMfTTA1XitDl4MSm+jhlKS7cMprcy17QcPz0Wd4jlQL7Ep33ZCqN6LiOVtnbFGzu9rd4mrLgU2cEhLARtOxWwEZbGv0PlM35t7KQufB88QwnNr7\/ZASWXKaxzN1Qr9OEDRdX+67WkxwIQy32ri+NYZfZ0Y3Et46Zv90mbD0EwRkRta0q1fjoPIX+8fc+eoUmMxOid0czT17YSfRu2cxj84QI3\/SleXzVN+egSVtjXLK9Fnsb5Rb6EL8jw7ZZv+8bC1MPzFs00FGN65XLDC1X0Dgwi3O++wwXb58vO3x2VwNyJvOF2c1cCGlYmExJYSLknVLY6AgDs4ylfEYla0Ht+3AgLLIVJu9TYo4uojAU\/ujtiG41+CeSr4WmN+P07eeBY3wUXuy5uCpethrrd1J+1\/2aYcnZLUrNoqD15MFDudcMnM2q\/l4zrxn3dR9Xu5A+u+3qtG8+PRWY3\/t03hfFRiwLEdmZQvosb9XXB9PtGGjO2Rf3sroJM0RzHzOmUZC9Fd40IjuE2eqFh6ri\/r5H7rDnd+Ir7NzzJrsPstF+xvBtnwkHveW33gXfo7FZYFaPnNoQ9oitUrZ6y4KH+qztIkY0ngYlXJnYwUEoxj0lRbnEt+W5LSX5FbA\/YEKzqQoHFh0cDldtgnXbrKG6\/\/G84VDY1F+dqdW4+FqzwWtJC4ZHP53OFaBgmG51MPEqBw+iKlRPtvVA4tMRaakjFSiY1u\/bQ45rcX5gTJLZDTXVZU1PI8sR6PNS47wpBw7ijgN1V3rAP\/\/QEf9ZFSh8vzkhK4\/GKO\/xiNdZNLwqHp6L+cREYpVAIc9bGuvp+aKL02kInNISF9IfQqD+\/g4HPxpt2PF8cSSNC5szD5ut4uDiwLX2hS4stMwzKChIKUO11MDx5MOF\/9jffGNFiyUqWWClyq\/0D65BRjpX\/IZHEZ5vCj5x4jQLZ63+pKWMFeOt3YvtWb8KMD9L8sca2W7YbaqJztTpQ6TFjljOE7LuXcpytWcbMHx+vvbpwA5sKr92x0GeQj7P2ge9fp2wPLFfnZLrxbCEIZPtSqEtY3P3+ro2HF4e1DVrQQ9G7Wb5FFhR8OA++q73ohnTGKtmpSd3YcNyF+2ifRS+HL4u5eDcCzV1qdDpCgO4qH1Jr7SMwuz9cRN7iG41Cc9f+ZWHC08Bg1\/Zh+qhX583I8ud1JnY6yfsNxQW8sQLLddu\/u\/e5xOrUW2nX46n9+3DUi0bYHyydMVvoi+ZJ23Hl4iX4+wINWUb0R231zL3tUg8vmFG+Wb3cijtmxtSdLMBpU3TxBIJnypb8qadS6hFsXTEmt71bch7L3lHkujC4nssnr\/foTgmqjPZ10jB0WqYIc6kSB+dsTbAmUbc1buRnmE0NvDaZkvKctGiJvmx4gXxfYcuHZWYoFBrPSCaTNZl1ZpT0cpkvm\/nS3c2t1MwSjDKD2uhEM8847y8kIOpWScs0z0JJz8+UCOaQmNRjdhDmaUVyHBfoJ5S2YAf6RNb279xIaIQOcPJvhoN5dHZal3NiHBfbCI5m+hO0ff+2uoyvFGx1Vu4sgGsPVPU\/t735SE\/TfebSzW2Ms9EzhtsRm1J5t3DZHv9y92fLKMZUBYXnnlyajMOrE2KkCD9wYmpuqxhXTkOGVMaLL0G3BiTGL1G5m31xd6em8Q3rxmpimE40hhoqbWbzt+KfYd1gyIFaUiKBWk0q3KJz1j\/fH9PPY7uC5QcJH72w4+BLR\/I\/HjPU\/gl+rETEtrXIsqOkv2MVwp7yhJ+CwtYc25aE\/a\/fVPxfjWNha\/Nv3IcuVha4Xtn8kID3ni8jD15iIPiyxkmZdo9MH\/jrmzFKsdA2SYpuSccUGuykw8E9sJJ0nHDkfYKLJC7uenSZQ7ReSerHTU9YAdnPk7RqYDzyBQ+A2cObjSGpl\/fx4UadW8McWQcC29rDTwlfp5XKeSCFRdzOzfImSTS8NHRL2ATHm37Pd15WiiF92GVe5uv00h+aJ0l0cWCtfyJannCeYuy4\/U+uNFoT7f4sSWXA3FJeZPfLlykCHr7eSeT7UOmmNYHs\/DC1vT+vbhKPMronnvjdSFaBtY18ISwsNSpVKcgqRLl96ngZen\/3B80Za8tCrnDwnNx20lnQdK\/BSNKc10L4cWUWLr3ChsOd9\/7C15tg0pDhP2O8X\/m03+KHy6eKuiQyUaE76bdQVM7McX0rkZCRykkqNopu5XYsN0kNNwz2IRvEQtkNi0swaoYxbOp59lwm+y0OLOuDQ02zWqRAyWQsygT\/CPOgc58Gca4ZTeSefXGFNTLsanvw49UGQ4GcoZT7O51g1W0KGu7RTnsTtJXpsWwkebjwZW63oHge9mBcxNKoVgmNswzysYM4ePRCSFdUFhhOjgjsQzxKeJtpQlsPGGWWvg+78Aak1nfpuSU\/mf95EBKoQNtUwqtOdfO3raqh4XKMydhDhfX0ixHrElcc0dHHEg8ZTHPXUESp1vy4gqjS8H+c3oe16Me0\/Uu7x8kcd9Vyy3qLxKOH1vnv82e9IOUK6fOZjbhgeOfEeGlNOjikclMczKORsdzabINmH2Zk7Z6awVOO25XZbc3wHaPS4vWGBcuSiebHrP\/\/r1rIC99eyP8U\/j2VY\/\/j7\/bcLc1zpxbg50LXpifdGpBpJyt7LF5JI8\/GVTumErqY4f31\/mfGpDe4ZvrTPrJMgfnJQpG5djXvGrTttMN+PXsxPOFpB82Cuppxc\/qQVfE4mN3p\/ajM6K02JTwCf\/EqIORSC+S9sklJbb1w631erRHPoWXB69P6TDoQpk5W8fveS8W3PLbKEH4JcElu3KLBgtlxb0zF3gS7tim\/6jwCg1nT78q4QUsKG2YcqzKlI0Vs57\/rjhPY0Tmtqdabj\/mLD+2L\/PXINqE4sOT\/xC\/pd\/kIHWVjYxXTb7nrnPwYYqqwGd\/oseni3foZg7ieNTs++xbQzhb19GaLU\/DydqpWLB5EKUzq0aFng9B5Vx590bCS1ur+s+lenPQqXg8sH57L45rTI3VeVIBFZ\/MzyIOHJgVq6a4TvTAq6O25t65CpyJTaZ93DhInxO\/3WhJL4wWKGSe96yA4YP9tX9IXaj4K4v\/HGnC3jsVC7+LlsDk+BbvUw40XD0mBHtJ3x9OrsC9Wc3QnvFRIPAWDe3HMbsC8yh4stUszSya8dJt+c7DhAffqfbY102hoVx6aNWcL\/9eHzkZR7LHjpTC52zS+R9G9cgImX36M5uLgo7J2m1\/vz95\/Vb8\/Z9MMC726s0SrIbmtsUfk\/gpZLksp45cHkLL5qXM82rV+BBcfaCG+NTJGR8UAr8OYNmaglMBqgzsmFNfdGcKFwP1fwwlj\/SjuM7rgptcFRK27nunwOFgicHUr3F\/+mDwir\/Xhln5n3H6\/gBx+aoyDuYn2f0MtunDOt8SJX2nSjQldS4oZbHR+DYtsO5CFy7s68jc5fvP\/Pj\/+\/0Sr3glNq21qMRjWdfci3aNsM54aX99kgtxgs\/V5oRvYmRC6kChfRf\/wy0KTfjTrd2efIXoH9sjOmkOG+z4rn3lzGrsj8o7unk1hYNZRx28GoYQQ20VcT1bDYNbxnT5KBeJ51TDg8SGIOt6eovS8mq0jKj26ZJ8l9Ved\/BwNBlfdXDHS0YDVFUOODx8UwMFs0dnX2xoxfovDke3C1NQHVkWsvNDDT4\/6MoJ29KKq4WNbyxJXCXtu+H10Rq4U13ijy60YtVM225ahEKxT0e++sd6FAQMPq\/80w7jeV5q09ZRsNzearG9tx5PT+fGjy3vQMgRiyhpwr9Znnb0npe9WN35Vuz2wQFMJGWfbaqkEFnl7\/NuuBvrLtVuXU73Iclj212HRAoDcXydEv59SPzAiTOaN4g9jQwtrW5yXLsf2Z43+iAmc\/XiZsKraa1NOladFL7xf1PzyuqByG2xMteAfhRN7f4s\/o7CsgWOd6d96cbt9w6dhmT\/0yvUJVzJ\/rWYpqN+5Lh6z1SVJ6g+nFv9aPQ6iRfsbTCrCu+C8cQPo7HWXvC5HhMkGvyf5e2TT\/xefMlE37cmpDpmM1DzQHnvUYEizARSzd6zELa\/+M+noGqY9ym0bdMowrPrv3Y\/XlGGZ27SYTb59WCaCL16Rv1zvnXMTt12YEcVitXz5eS4jRAzV1wc8ffvGxcUOaJ0KaTNJ3upuHp8un29lyL1n3tiMe8PZinaDCdGs6LroVQpH9JE4hc7Gms3MllQzkhji0rXobFeVUxzsAjGgXdeVYywMKBQna1aVoeF1+e+Z8375+didOXVx4QC2NBcql3b9rIdoi63D7uZl2Ktjs96788sJD2pOMaeVoOWEKO0V+ZFeFisWt7\/icZOq4EGU8JZ37JMvHZUMcFRDgoUyqXx4Bl79pNMGp33tEbPcZkQnlqxa3o94bLF4wPlZPu7bscLDl3tR1WWi40GiZf9GP9i\/pGGy9ic+v1+g9ho8WTv0irCnZ51JdIJNEI+XhCbM9yDP8fe8b2qpLFSf3ndtngae0JGWz7m9uCr1vTxkhoaeT\/ZwzNe03jROtlp49qHoSNfv+9vplG1QMpplIwr+9cXtw27BvFC5ww3pJRGz7L2QLfn5Dw8x1tqeLsh+Mq2bg057rdzjBtq5Lh2DtG\/R0d7cM1C3H868cP7qFuvW0NpWA6fOrzrTwc6Q48+OKvDAb14zX3FTT34KH+Ev7yZ+KW9ww4b97HRsX8s79fiFnz5aXLX7kQJVr6wn3VGhg3JwA0RGYJNOFE4qC\/SXQyxmFJbFh8XrPGQg0dv9KNAeaj52p4q1K\/0wodENop\/2WZuiO9A8TsdvfUfSvE+v2RsE4sDxWlZMY\/H+uB7aFzkc3clbM\/4bj5C5vMnZ2umNZnPm4fWPhTxHYTvsgtmFk00wmGhNf6Bxo24hzUyXQN4P4VnWn0FDcP70gU2sTRk5l7NHrDswT2BNzZHybxRm2b\/EiDrvCA1+eLcvYNIk3\/54105Db+iNdUi0USPRfYeauR2o5t5Icvo73Nt\/HlPvIkv\/5MtVasf3gNp+QInRjcbmfJJZUJaXVh5YkTo4MUyFC6YXnUwiA3hM9nN1+vbkTJpPZXnUikeWWisuSTNxp9dLRH5hCsiCm9PM20vRnCM1OWI+Wz8NM6dmhXUgEeFGyek3IuxKDdAP0GNjWtbZKKibjfDce0j1SmqJdB3eN47toCNvvcZp3fHN2Dx\/l3JWreLkXt\/6SND4j9\/nnzicT28A9R59y1u2aWYt3nxHs45Nvgfp53ZtKAN25g1D1o6S6C4iife8SUHQUd2rAz40Au78q\/7rX9WoKIrMchTkI2zv5e+KklrgGKf90Urn2IY63n\/YmawwUrNfnvxVwd+PGycWdRWCsFE16thERy0bj+pbRPbC8OwwNXinAqY94d6tDiywTzjFidPtWFzgP8DniWlkN8aJSl0n4vr\/ZIem\/0H8WB9sn3OTQaied4uYpFxnA05+tHAegCSa87RbQwKsWuV7Geda4O0o7S8S283jBx2cs+d+Hv9Y8B0F\/Hrh7oqdviF9+GCn1DDfcK3F26eWrCqpAdtQYmoeNqPRX6ibzzeE793aO2vFTc7ESY0dd8bqV64a8xm\/uXekJwF17uIjzwoqOv1+Qzxa0PrHKo4FHzL+kwrSD0ksg23F5N8yFsbXJh9io0LyxWTt3ynICCyLy5YkYbwJWs5+QUU7C6dk9LwJ\/7EZheb13sQNw3WlDIcGDDNySkeUuOi+cq3xSYGA3j7nWdK8s8q9IgNCY85UoiLd3h+VYENodUBf958r0Z8TVdLRx6NM627kicDaNwLKskPu9GKuFydEAMGjYpn6UOFr2jUP\/FTU7ftRdkhndkxVqRurwlX9hyh8CzIZaveqSYcfqucJk62T7jt+9mAbG9hN9\/3s3kvbqYvO6pbTIOfj184\/AkNZrPO++bZXeiQupM1Qfh32kCf7wqioyvCedSreZvg8VJNJMuXQs3yl+tZgxS2n1im+5n46o2f5p77tKsM4zvq7to31kP79Jmctf\/junyc74Ifex2q0Bul8nrbnCYk7Xpn6fybcIFiQ6KdQylq555yemFTj5uLd9TsIpzi7bs9d8ECGrh7sr9Lm4bx5aSV5\/q5cLqscuc44eB9TZ6zbiTRuH7545PaTSz8+JJ1JMqVBp\/j3L3HyHkpSVwqyZvFheTODQuCvlHInd0\/coz47KLpzdYjQhQeuU0ZtpDpg7aJ88v8d0THM+VsVZvJugakpXz62At+Z6ci3lMDCNc\/w+SSPNyecNx1k2kP7ui\/ajfV6sdYWpHO8P\/LexseM3iW3ixDrM7eqIDRekgl8jqOknlrmF3rW72vDIMMKdW4lnpo7LlZt5PEr1s4CZ45SvI5RHSmtkY\/uBM3hqLIcXna7BTSvvXA33h4wWReP97MG3o7\/dO\/H89Lo4P+hl714Pc4V+JW2Y4es0UzNq2l0CokyLJRK8fBBYMq70wa8Olw9O+PI2RddDUnPwbVIm9HrdRSUcL1w74PbouR+WkUNf9a3wzNQ7ktCgVdsNFwXmL69\/nlqdtvyzHroXv21lGs6kDKs\/WTenL\/nZ85vDRIOTyfhXKBP8ZV36pxoT\/1tYxJEVTFL4weH+9B+AolG+mCflxMu9G5nczPqIpmUbt2Fw5bfpRgBPeC2b3WYONdCnc3ClyOkGnD0criAtmibqhXrbY7cozCzfrtrgmNHLxYOlX6amQfjjdJujKjKhGezbN+2282IvZPoRcVdUGi+NINqcoyBAR4H33Mz8Up9rOXCxz6YXxi83D83irEKevfslrGgXjCNPWIw924\/G764g2K5Wg87ChltpuDG5wpDzYK9YCZU7FQPa8cHOc9vYJaXEh1fO9uthrA1Vt6nnzTGWhdt+PQydMsZKi78Wc+JzoQffKY\/nUaGnk9PKlNHLyK1nf3eMhFrW6QbkcqjV3zgyQy77NxRe4lp8SPg73zz2glPaBhxLFK+0n6UmzHXZFo0pfcDDo72aQvjc8\/+0qejL+Ah5lwxa4fqTy75xtrV4Eva8nbp4R3Fj4RZeec60Oh1+C1FMdK2Fwo8q\/m5cJt7ac6iZP9ePBy6ew5ylXYZSO0o7+KhTq1jpGwtBroPw\/z33ynCObX0x+H7maDWs38XdXTjOHEj11vDpdAR3BizV5Sf32+oQq7xWmcF83Pa9CgcCfly85ZhL\/bPq9pve5H4+JkGuOjNhdec47wDpD+\/Pqm9vka0p9NfsfIr7T+98+PGO3ZZnFbjQF7lwPLLEKaIFPwh6A3hUxHRT4bXhrTa8YfDc7lIj6h5WbH1XpEqpvccikjfThpa\/mFKOI3pPt92q27sXdN1vJkeyaionqM7i1nwfKL9YTCLhru1053mq1lYol77bugriF4u85dtW8HjV4FA3uL08SnyDp2znZjwtkzQ+XyfBoxz\/VDC4j+PVjISSxzYeKbwo0Te0h8XnN60LhuJ3b5zxa0FO7FAY4S87IzhbSqHTfmpPWg7InG\/Xn3+rFcwNQ5LYeCiciM3K46Gvur3hc7E1+64WSzRzlZn3sZfirna2lI9TmtsUwnx3sj5N9Y0Af5GR8br7uy8eKgeOt80Xb4jamssVxbCpZtoqPJUzbE7wf731nTgU9hq0zW+pXCuOvr6x25LDS5q4WOfqrG9IPzhFV1iiCYv91VQZX4lptufRr6zVAxzUlL31gC1WXiVLgBhWCZy23nH7OwT4U+wfu2Gt4SQckXJiiYKpe61A9xoFPdUeO4vB7CnhcWP7GhwFdr6\/\/oGwun6hKSeTurMe1ugcGnKwOQuNWsKO3DxN6MNkkHohOitx0C5ywehIzwx4kFs4fQajRmNEeChm+C9tViw15sz7yQHiZIfEW6nuuH4n\/fJ2ud3DqbZZqwP\/9ufDnRS+NDNW5vCDeXvwjYd534zM7AYmHJd4QPipbbPJrHRERj6B9for\/rz3vb2bynwaOQ1mzQNogTJyWVytiDOLJHtfF18hCSM3nuzVWiIbTJeO4cEP\/84VZM134Ojm8MGiq7Q8O0it4xyOai\/9BUfd3vhDec7zb0z6vGMNvcQNaT9O+Ihb\/5TAchYlhVM3aaAdtb119UxnEQGTYZq1BD9F7Kal49fyUCslTu7CEcNnGYGaHgRCHauTNg5xsan1z8pH3\/fk++U2eD7Foa6ksPMk+S\/jzLvGO0+g0FectZE\/Nm0dAs9JKscKDQwZhVZEh+34oZdPJbC4UI0a8X1xEufqEnJOVLOKVe9kSLZxqNOfw+PwKs+zD4M6X9QzaNVd5DDb8Iv1CbOScMjwyhdL1\/nQCZr5r0uZVfSB5+aA+Skto4hI5HE1pHiP8pea9ufJfk7RsZ2avfipgINa23q\/5MY3FW+PQHZNzPVvyOaHjKhPz1uQWNZP6feBgmXCE+vzTsCFvQugf7Kv9cWU\/iLqvc3WfFEA4YdrMRWd4D3pmHfGpcaDTIjufLJFO4vYPx8YVCM4YyrXj8STx00GR0VxKF3TrHZ4ZsbIbH8OmTXyxonHtC74sg\/WiOz5eMr9uaYOYem2lqx8JJ+Q+c4e5SCGdbN7G2FWKjBg8704kL1a2MPEfVQTimrc\/8bsrAyK\/l09xtuDh641zOtt8DqDSfurhXnQGb0w3Od89y4PQrc\/cwqePC1Kx7SUoV\/1oHZXjcHeenspC3IjDoZRMDSr7vli4V\/uf7A\/8pniVxMkEjioW1VQcWuvIysLr7\/NSdnYUYf2SW2N9bg\/01O1nrzFrxWsNu5Q0RCjE\/fqrvdKzAi5aIpXE8jShw6C9T+s7FGb0q3pZrdTizOvjhs+42bLW1sHFaSWGJRpKKXEYdvNtUY44sbsfOx4XzfFZRWKQtpaDGx8DoKxPdrWZNuKp2Qy6O59\/7hKWXhqxG2ytxrPZ8wIKcRtyWU3qk+ZOLcLrt+GbxUhSWXzq6eUc99orp1\/5kER3JS3SRWlmKap7moNck\/vFO\/i4eUm8KEx8Wv20bgoD6ZaGhTWxY2GisenSaxqTJgzMbfjBBGd9al+XBAusTvWeJPqlTLZEIPk0Wbv\/J4mZ7sqFy4kRpyxUa6yrvWFeKcXHP+abp9mJSf45PEtaR\/OU7EemlFs8F5tw4Eb6Nwmv\/BuPWAhq5fBNxliUNcOR\/dOjgQAeWzZBturmZgpOqqLpaWgu480XMwlZ3487+w+xjh4k+mpa8mirfj\/wTLz9VEh62T\/gTdvoLqdtfR7Yv5R2EBb0\/OmOSidtCDj\/GVpB6myEdcpqnBymqvy0bf\/TB2AonM19R8F6Gewum90P7wt1mh3ODWJefbD2TS8Fwg5r7Xo8eXCwxmrLYuh9fRx6K8pK+YH\/+mlnw7G40LfO9vHBLH2Z\/dL116TEFZRmm7ZPjLLzSnJ6h84SNkoCDg4m2pA8eHWnn+LNw9xtfssonNuJXbS1a5EBDoLv+uYv9ALac9qmy8WOCZ+2tLVKCNLwefvtSac8GTvBEv3XkYEU23zNrwkMxx90+a0sysSqELfKUrE8AfviWqND4uakhYbh2EI1vUkwXhA9B6djhwVebSf\/vvVowdr0SV3LOBH\/xbMQKey2likkutg59LHVsqsDuxCtqsfKNkG+Z+vju\/7h+MT+c6Sf9uAa940UdCfNasVny\/FMzwhH+81J1x1\/S0NpebchIoKHI7uQVesqCVEG9d8Df76cJOt64QzjlaPuj0uKNLOju+cRv0cOF3euo957VTNxbITvqx1ONNWlvhgf\/EP0zFS2O1e3HYZdQqx3SVbipstDM7QsX4kM+ErfmDMFqMi51SLQazVbHFN+2cpFbEO0pl8VESaX4QPs3Bvjivl8eJdzzpTHwq\/fVfjzSypljtqsKDVyN3ccOkHy\/mWxZ4T6A3Inh2pL5DAx8UjT4\/pWLOrHiXK1FQxD0MrTrXFoNwQzhorW\/OJCKyx8s\/\/ueOrk7GTYrquDKWxGo287F4py4hGvvmViZXqFydpyBtSnUU90BDl5qH3Sm+vrwUKQhuLCuEj0Cze7P8hvhMc2we87HTgw3r8i5rkJhR6mGWn1ZA+ZMNOtdYHYgz930w32S57c3vRqzdK6F9Pr1df5\/WsHTP\/9Q+2IKxzy8xhdrNeLsqi02BvqdqBC7MX5dmYLarkd2Aqvbcb9C9NNbhR6cd\/UTCThNIUne0+XYky5kH2hzL2\/pxYRF8cbk+xT8HjJSzQU6calwt\/JXwgeCDhuyigmHN5xTl7eP6EZYn8L30Vd9WKG894d0NIWKS1pH7Ot70N6+SKs6th+ca25GTh+Ij3lk7jnbqwvLyoy3JBT3Qs7xlzjXn0LgPR0ofm5E8bbsSwHkfBeu9PH+e799bsEOxqWmBpSLn2g3+tqB20UOD8bJ+QYajxovcayFY2Ce6pKfrUirVjEtIOc71hfvuoBuhvy9x0FCjC7MzJ\/4Lq1D4fflG8Ole+uhbBUbx31MeC1155ED0hQu5Ha0npRuQJJtuXW7cQccWBOpphsoiD3+netAfMgJ7+OWC0keGpypKZx7qxeXNIx6pctprFj1aG7zC8LFXgVLupK6kW3We7Sc9KF5hUP5E6RPlSzfNBlC6nJ22kore6KnjLD0qliip8Mq4YyRHT0YGXunOUz2P6c5ZkkQ8TlrptSpT9QPonlxsfoaouMsrZ\/MG0THtc34I3nKmKi2ifW4LNuDhKUy54uW9yN3qVDS4lQKsbPE+fxDBzBmKuliF0N8ndB8HBWhkfyhrVY8jYLUw+ERnQk2Eu6u2OEwWgPz4xb3vEgdn4612rNHfgihSfM\/nF9TjU+fRORSurmYV5t4raqSickHUr62fxioCPAZ\/TmHgqtIbPtl5yF4OlvEf9Sqhkbg6Z\/31LkQaLmyusdwAG8XRWq++12Fpp5DY2tJP9CobdCg1wyhIMDCJnJV9X\/GrYUtyest77AwKnjwl7oA0fuqXd8mXApRfDpTO8uPBd+0p8Vb71dgz0DJ0zsBhRheXn2jqoGDJt3su9MecBG6OOV4CuG7izcfnrlOuLY8uYLXfS4Nkaz1fOuIb7b9ZLtoegQXDob97KsKFDZEmZ7tJv4pTt3bqbeAwtYUjflVxDdrfXLiS7KkoKAc7LnnaRWOSn1IXy3ehFIBs\/tT\/nBx4dgaTeVCBm5PtX\/YsKoZWZ1Kz\/hnEN5fNT3f8WId4mZHaky0taHGsCNKj+j7h1nxETHDFdBxZUibqjbivmJzWi+ZR+kH\/EbTsjuRcUMgaiZ6cWOD7bFAdwoJ7BdKYeo9OPBo\/fkgomPb3zKdOGS9Z+uP3l0Z3I6fPhIJl4\/34Edfd\/ai8xRWf7\/95ox3F86dFzUOLu0Fx3W8eWkAhV8RAfe7+yiUfPupzZEmfnAsLF1pI4W9GtPFztyj8Wvos5\/qcxqnzybTsbs4OFcTvVGSzI+d8XTz0dJBFGbRvD+DGJifVxbYSXgk\/aq5vj6bg67FJyaZK+vR5LLJS3MzF2prLt1UWzGAQuOe7\/mMKhw4acE8n0jh\/OELCSIDbGguvv5DobgGdk8Tluwm\/Wb1an7OmBcb82b5vp4hVgOLb9USXVllmFB2qrwi1IBKnqvxpcNcLD3vlJoSVAYRo2MvHac04MU4r6DO8P94n1J9++Whzipce7RePFKdcKtzaf4wWa+Zr2wOvj5YCg8zjr6SYT0y6yW3phI\/0yN3df+wTin8rmnl5xvUo1phl3QM+39cr7e2MLfZXosXzPwC2exWMD4ISn5bRCFynJ2jHDgIjwZd473nhkA95RM5vJ5GWumm6jB1Dn7wurk0LuFCOWg4zpfw8afUPu7f5xfUC3k71+Z0YI\/Yuyk2n0vhn7tXT2A2GzMSqPujaEDw1qnxxTbFmOET0F0syYGB7xl2pkM33J\/5HVmvXw51E2+7ASGyH7tYDl9xAy7scxpL8SsGv9mBtwwtNmzN2V8+NjTD8JvjpayDJWCwrt23ncGGiLOD8ZmJeqzrpYc2mxTDKeL+s7uEZ889uPoRMh2IdAicVUZ4tuuctmtSLwuCJn6Pi3pqkbjxc8Dv+iL4fIk3KlvJRnbkFcvn4Y1geIxjKL8YG1JnOmywYeNherulikgbXGXXf2vtKsGe+mXSRwW5MAiJmev0iYuHlgZzzEn\/2+y7amdFEOEyV21nOXMuUjU2zbpJ\/MJ4hVxn+FQ2tmUvNU5ZysHlOVVqs27RyPvlpbt2D+H7KNczs9OJn6uaXO2ylUa47p0dXzcRP8lS4Oxu42Ltl03PHrylscArpEjCshkRC6puMx924ea+5XU52sS\/KZ+JDY5vh23rjOlHz\/TgkOvnulZSR8n59QNLWtuhPij1iu9mD8wCRzM\/XyR6JG0k8edSF4rmyb4KzOrFb71btKYfBfFrHzyWgMZxayL\/dVw4b1yL+u2NWFTfICquQPr\/5KMXgnFcZKYI3vve0IAnTWd9fu3uhfNPLaeS6QPYlnRxm2sRBbewq453ST177dG59npvP9ZfEuAxzaBwcE+6wRZVwvVKVaeXHGMi43HtsR0CNEbeV\/Osye3GfbVFXYlFffj11OpsTCzR\/XgR\/11eFMJPRc4266EQxdFoN2NQSN3app5P9NwodVOEF+HTcGpDw5qef+b9zgYXtxNm1TjyRrr7TV4zbo8\/9DrKT2HovoD8HE8a3HsW0SXhNBptwoo3Mjjoezvokk90boVg9uaYDKKrjhUauUJDqD64f3oI4dkXh5eayZJ4kkvvqVVEN36czHuXRbjSRCm57XcYje2GdbrTRP\/9dfx\/iue3NYVOq66GXlqHm5pKCxaHL7OKIjr3waYlK+deNTYOV\/DfHG1GwFXBhNTZFFy2Mj2C1tQgIDtUBMEtWNVy+pLYfArvlP02G3+uwE+3oW6hNY0Iqkrfpk76dtfcMb54vzqsvei19Mf3NnTkpn7VkaDwrTSH\/5BlHc7Oy2Pp1LYhoflQxDdxCsvb7UfavzPAszVZbfrRZoioH7h1bSYFxfdW533rOFj57uNzxQAuXhVZwJ7oV13tsk4ne6IDdTW765ooPHv7NGHKAIXHpmUNU0g+ula47p5WTeHrOcWjH79T4IllJ9USv6oy3VBa0paCYFP3ZfViGsJZ23SmET\/MMDPgdT5OoflNeZdb6X\/3XEaaounQF3U2OJdFdu4Ma8YagwuKfeol6E3cL8DiJX1g7hbBuO562A2eGNI2KIaZUwkMib9a1jmhpEL4YJvl7G2P8rpheGlhsGIhjd33pvOuDKEhPXv5Jy1d4gdz4q\/dIXH9vt1WdSRuzONDPGYHtjpmbnlYTyMooOrmT+LHplXLfEpM7odtv3nanBMU4thaF9+VsYCXVi0zK6uxvcDTtoWXQkbnIKfRjYJsXPS6S6TPHOf3vKXfRaG9BcxbkjTaOxQVaSUKkhli2udzKYzPjNB+N4cGf96DWg7pDy2axheUSN1w\/A+53QojOmjlNCl2tg6aMS5u7GIKD7uPpGzU4mCPsqqT\/8taZJwI8xv1JvW2SuvPdys2TpabL48UqPnP8nxjrNNbL3Y52G8ffRHPaECute6Y7Dfi27yKX087VI4VV11DJi0bMLby52Iekh\/H8l+Em\/e1g3dpIk+5aw8ejeTNlLhE8inp\/NUPmn14We3e\/KNmADvDwWfdSkHHdmN283A3DJSes7fQfTCRsml0Irr+Vnytw6MDfWhxOd4r0zIAmWWfNEXbiM9YL2S3bnQA2y\/MclenmBi+4mV0bPl\/l2+3ansMBpNYcNVvXXEhi4GOIxyD+tlFOOKut\/ULg4VfF41iXufVoIYdPEfJrwisuRp1aQks2B0YCZT2YsCT1Xfd788\/37f5X8X5Zq1Qd9DjwPzExoQHKj1Q2X1n\/6uu8n\/c3nnFL5MxBQ4C41+K+mZ2Y+q9E79knMuxN303v9aGekh+jspe5NGOI0nZvTZryPxf9qNjtjfhbjF\/tLtQF\/okQ7K1d1J4utck+5MnB1FbT7V9k+kFK1NFU9a\/AhFDarkTLoSjjatFdgr34lrLk2mKLhWoL06+yhPJwUaVr4afkohv1BJNLyI+dfTaY\/3DTA7celSzRKk+6FeJbPRorQSLN5+9ZA4XXP19u6d49mNCalZTjn4VhCT79Q+G0ihT75NaO51G7IclNjnjpM+hQ\/Uq4aCk55IGMwhnhU5uvdvuRsZ1ruTxrnwaq68kXmu4T+Oe20zRH5WtEJBMG49soLGzY0m+Wg4Nj3eHDJRXDcD5+KR+TBHhqwPar7cQvYjyMQ+q9e6EbEfoau2kOtx0n5FsLtSOwLH3rXqrKMRoCj7t76yHfqHnBqGlHViycdGlOXL\/rHdev30Lj3pWI3GWnF0iuxl6muI+14gueG2NOqie1IzCW0KmU9O78Gid23HR\/RSc5bLXexypgXdSy5YHxS3YET3meWkByf9Whw3nvcrxJ\/SQxR+XBjy8mumYQ+qunHdYHKQexSVcahdbNaA+5OHI33r8p\/GMHfd3zb3GwGi2W9OWyiYEnv\/1+c00CpMvpacya0uxWflJxouwemzV\/1F8l8vF4uBV3TtfsvBm4dAS4VUMFGYb3ewYKMTTJ5eXOdey4HRg4AZzqAZXDAd6fwQXYcrCt\/P2EP\/1tkvv53gaDd9lmlflXIYQPWudEu1Kg0f5frzLExp2kRO6zdO4aDn2Orw0m\/Rf6Yq0qek0Vp2xiQ00GML6xZGy3f5k+4Lp5a8iadSqeh+RFeDglRy\/4OUHxP9e2DvzPfG7UbF+xzK62UiRSawqFufAeqz63FTLblTJfmm+qVaOwITtR8\/oUhj5uCy61o0Fsa1F32amVCPunNf7k2u44OOuaVTg9CP2wpK9B2P+u\/e977XbwGNWw8GaTAUv4zt9uPQxQ0XhQSV+D2Z9dyHcMnx9wtjYpAsiB14HjjqXYeGWGas6ytkYenV2G7eiE7cYH2RPyZQBviHtpnYD0L16PM7Hl\/l\/rJ15VA7\/\/\/5JKEpUkhJtorSQrUhXm4REiVaJQlJKpbIkJYlCu6RIIkspFBGVaNW+7\/t2bzOKVtvv5fu\/3znvcz5\/3acx5p55vZ7P63pcM\/fM4NC+45t4BQn3mF9ePUhyeP7TwRWeRLeWWE5zv2lGI5kyF47exkDi06TrR3OZMDpQmJllQeOUY83mDhMW+Pz2d6RasyHx+euXNJLTbL3urNK6xgLvqMNEQxAbIafrFk+QvjHeo\/6wL2cAIUZWk4mfh9AowNc2fzGNN21z5j5dO4g7v53ZrcsYkHycZJkhS+N8\/I7l\/Ff7UFMktN91ziAk7kokFxL\/U4\/2FbEnvsFcYVa025NCyIDA07gCGnuENzV\/Ily5\/cCGJyI\/Kbi25Z6fiiK8xH3srcMGGhZX3cfeHqHRffSswYZHHJJfX8xqTaJwPbkKiiQvvn1jeTcmjuRASjdtXj4DOYHWbkLLWFi8mv8hh\/y\/p6hsyrFjQvKe9yEukj8EVV9zd5+mYSRpLiC+cBBXZDNCfs5mQEih+f5jKRpOAXuLTxxkwnb3lgc3Y1l4Kj3q5EXWb0zjObGlbxC7jQtky58wMPyqvnwX2T8tbn2n8I2DEHYLcmZIM8CJmjlfdPn\/7r577\/xw3YFtpXiceOX9fJN6XAo+fPE6yY+LX5mE2mQMIe5IeJG9IROR2gM2fDtpCGRwcSr6ezBLyV1I+HU\/FoTKXivIpfD9e0n414Q+HHDvUdSRGITWtqxgvl4K6L8heTSiD6MhevLPBQeRKT4251U3yT9x+ff3jnVi6PXrJSyzXjhvFdnwO4CCnBKX2vQHA8iJC7zd\/HwIRvzP9LaL0Jj3cNhnCeFFttr8XCUxGl0X8kueG1OoUgy8c5vo\/waztIlDDhxEvUoJykwh\/L5vekLjewrdiS39AnNpzL\/0RuW3O4WvSU6r7tqx4TN+LFJ+AweZcy48ffWIxkmmY4lKE+G28Bv+4Tk07L4f2kx\/GcCnU5SWVy0N6adOkWeIbnRGWLUuLu3D5OedThtLSD1yvbxvR3La0K6OjJF9QyiYyOEtIvXYaa9V9zSaDc\/aTRlsmzocc32tvYbo\/7NJXwX1WBqtxnL5zrKdqJqlbcCSp9FUObLY\/jrh3OyzXOtvNWC2h+ekEeHG6id1q\/YRbjT9tJTBZd8Byw2ameKEf4\/MGss9nUAj7mvnhajKLhyj5JrN59GgfGLND6\/moFc\/PelHXj1y+Qq8GlyYxFcTZVpaSzDLZM2Yrlghph\/bftPoJBP1xv0JxSklOPQo4MtR4X9zhWzZjtMSR5nQtH71hJVejKt8m\/lmjRbA99T70\/uqOSgZ4NIqtKCgsPfH1SgyLm\/u\/RH02tuAh8O89xQvdkBr4jT3+9UUNq27fjAurRLVked7Id+E6dm5WVp\/OMhX+jU7SrcGLZ3it1MyWqB5zPbKwN\/3cZ7IajRbUI24wmTlMrdmiF8Q2qTMQ+Ho6FLZhk1ViOJ3O7o\/rAnGuHH773OepTL65lTK1mB5wLJ9ppEtuOBxbv0ssp39DScd1Uqq8aaTcp2\/rgUxq+2jHEmequoVze0orYX0nYx6e6M2eO0vnCu45L9fn6oZqMVpoo9Op7J3RKZXIbpmcL\/knCIs\/Wgk4vicg02WiRrUFqInFgV9WmRe25r6pgItSe6w891TcpiNhxbnqhyvk+UvGAcjGSzMqzip1kJy1U6vl18ECC98tridPFrIweW3OlEXSd3rF9Srx5B8JP4qo750OhsvnhhmrCS8o376EddBkmuTnz15qydFcsG5FAHeWxR6ajd\/2H+OhoddlVxJOQuclS2XdRs6cURqd6SX4hdcOmDAvf4bE9E7t5u5V9ehtdoxzHNBMQZ+jbiXOjTixqJfOOTaCcnWRQNh6hRMTWu3fHpUi\/mpRyt\/ybfB\/mpb1AxxChr7Sr0rfjdgXpV2X6RwJ2oSDp9fs4FCgz+fY\/veesS7iOiXJLbjQbCX6a2VFMaW3Zmw\/VyH\/jCjs35y7Wihv\/LNlKVwv1AsXf1aE7xE8xyuru9Ci53htVIdCqF7XD6c6eNgIPKZb1vzELhtBVuGZ1TjfqNin28lCwVGT77V9nfi6dzcURXVL5D\/tLiOXs3GmgvJYZap3ZA2t9lxzKsMwnNXXUtvJn7uuHaLilQX9q9a36hq+gXlmpW7B\/7er+529nCpYxdie+oCd137gtD2BMlF\/iwc3UFb1ZP9nMP1K6papRQfXPecbz3HQviNtec3UW24EJ9eNUO8FFNaRi7VqiwcejWQtu9BE472\/TqzdGYJMu+VhNwl\/mG6U6JgzflGOO\/5cDYyuxjritbG3DpGQ3m9WonzAeI\/BoWbD3s2wclma\/l1wpmJCQ1droRHRhReBx3ka4Ohk6LOnM80aixFhM9F0DBr+rZ+nWcb9uRm+hluo7GiSnz0wlcOLD9pLzx7rhHUbeWEuC9\/n6tQwpdKeGbcTd9xi3s3xv9sL3cky3WzXGINCa9+vOUjcHbNEO75vUw43kiDLf796d\/3Xw8PbG587jWAhZsn021JPa6yyeZ2SSa87HciMn4XCzNWiL05Sepa83DckAbhrNAXnktFAoagp\/0j4lc0jbPiC6Lukrw8dIPvjEk0C+pR2s9P+tN4wlDaspTUa1SY2a5ZLDZs3U9qS93txt7HnCH+lD4wcu7kTT4kfvHGZIPEzCYMtfecLxrvhOHd8a4QTQrTVtg6ay3pwRiv1CI3wX4IC+8KGEyj8OJt33zhl104Me1CgSO7F1d+hQfbR1AQDfLsmbaIBVcLT4uc8QZY9UX1RsQWQzVb\/Js\/xcS7n1lL9K7WoSNOVeHsnyLIbTqQZ0X67OCZ1\/FvCE+KN+5ZLbmgC4e\/XlfeUEbDZ8Ern9EkGvn+b\/ivZHSD71Xu8FXCHUm8h3PSyHG\/fzXW7fW+HU8ud\/hIkfGUuqFvu4eM50j8mP4MiwG8PSDq2Uf8Re3qhLxdJvG59sWuQRN9qJbUeSBFcsc+WfFis1Qyn75OPKsO9qLVsPFalW0N9pvJaR6tbcHqFZ\/iswm3fzyzJHA+8SGHkjPJCe401vL5ZcmPt2Dd1XdmGrk0Uq3erBO8THxQbtpOs2WteHLuvO4JfRpVJ3tXXiH87WZ2Y3aSRyNWT9+unEWOSy8lNXgu8cU8gdkPyljdkH+rJXiS+L\/rqjkHT\/7mYJnByGj4nUYkTtUzHpLxOXv9zZb9ZB4F\/XN0H6\/uQqtgsNfVOhp8qitFP7+mUac\/Z3u6Zj9CVVCksrwG3Fazud4RfZb8kzDGQ\/S5aeuPmDxPNp55Rz2wYfagscdR1dm2HOrpph6TEWxUr3fzFHDpxaczRbxjH8sx4qvbsGIRG3JcF0K2q3VjmD3mbylVBufdrotseVloi4kL3SLXAIfXZ47aHi2GYmVjl6ks6UeHx36JnxsxFnJm3f3yf99fcHLH2s9vi1jouK8QtuleJz7oSgVuEf0CCXbZzd9tTOyfkb9q6lwtVFRllx96X4QEuS1e5yqZuOOUwNROqcEZ9lWHe0H\/u\/cs5G9S+qGxuALXLEVE0\/c2AgI\/4rwmOeiRuGt3alEF9nhYh+aYNOLlxsEFp8jyPwu95FqnKnBsc0WjdmkjOh6eZ6f+5OCTgZdyIOHckQs2iZqEN7UYPYNIqEJp4vFi7xwOyiV\/Oq3WHcJu\/pQbJYVVmOb2REfxF8nl+l733MfYyPKjq4I318OVIW5h60z05Yy+Wsr0QVReFe8z0KtCB0+ues4XCjfEo2+93s1G7LO4nAvZtRAyLzq7MYNC\/mSqh+U0NtJT3Q0yuGv\/d++7D6znP36ZhaVHKn\/\/0GuHa5Ll4YFNpShOXjNaZcnG+WlXXgec6IF\/Y7GyyoxyOBTnvAoiPlriaNq95RoTOoaaVm6vqtEpb27Xbs8BpRppw+kcgGUyl0P0hioEDayu2ydGYdWgauqRNAaW73i5465lNSbZldlmshwEmWYcXNrVj+Ce7Eb\/+EoEB5dL8W\/jQJThz\/3u+ABqbr5Ti5tVhZ1tf3yUif5WdC6Uf\/KURtoy82aDMiaa4rNWti4jnMe1mG\/IlIa7lb6TXRkHxp2f2NpChBeXaqf4k\/4be7dh8HU3B\/oByvaPlSi498w7r59AOEk4jD5wlOSYzEWKy9Vp7PrAb\/WZ+EnR5Nk7kfc54KA\/99t2CoH3c8NsMynQvnXV3iRfBJdt0hTewkTQr\/Ueyr4snNVtTljtRoOxacOdtHY2FuTq8Pje4sB1WreuOcnZ6gJBO6sPMzGqGD+mF8\/CpdPbrUtJfrH306a36ZJxyJtp4zdEeHD66TEeonNP3pzf8OwQB1ySupbvp1GYqOQbpQhfb+uaJtXylAll7dkqmQ0svD\/ip\/vkPDnOm4ImB\/hY+LT2zQpPWcI1Ae76Y0S3Ckyvp5jcIv3+ajeX\/UEyLvHfFBOf0eDl+u2dcIUJ\/8T63LvvWMg2qZDbdYZG7jPxgdJ+JsR5lW5mzGSjMjbllAHxG76VXVulNw7BXPQY700mAxFWVwdCNf\/7+b3TirxmZ\/f2I6ZNtCP78SDq3YoWNH0neefc7LQzfwZx\/PwGSiiXgefbfmZzk\/noWW3MF2Lfj0s\/dgQseD0IY1bP7eAxCkln+k+lhrIxXTr3wiJLkl9LFRl\/SF24uC+pWF1D48LE+ceLyXjVlZbJqH8cxNxzG0asg8h48KYKh9+jUSbf\/fo9ydOx7L5NF5ZwIDRxx\/pPXj+sQ6\/oIaASWjYOInvbOZiaZhvu\/2EI73bqd7tMVMHnQsVHxxE2usuuCiiL9UOv97d57c8KvDv+8tkrlxZc3M9TVTy7Gw4N4+I6JhQC7mwrkBFrIDp\/OO6yUQcST\/zxGlL+9\/ko1cNPfy1MrIJZgea31l9N8H8sv2nGTArZX6V+TPjVoMFWX0prrAXnlM4apwr+f97HPdynwSZ8s+4Hp8aC+Gzb1Yhb8iUseGzPeTbNiYLj7+DEggoy7nw+5vUk3980brLjr6VwaRn3vgRxws03LZ4dMaKwoK9OTeoqDaW0Yc1eMm6fdA4yZ59nIy7TsFCH5L7x7z7Lssk4S8jYf51eNwDnC\/kptTdoKPy8bKmZSHLWouaIeAk2bq89TVk20NhaMCs1mfitVk2g+i3uAfgteDRnK\/Hvmz0\/uWRJn7h5Oj4JSGBg1a78nnUfaGx4pbXZifx7tH9Dzo8lDFzp\/OMjXU76uW8\/TRGfdY+KmPwj2vM\/84sv01wW2+79gjEjm6H7HfXIMtx\/0JrmYOM9AX3b+C+IUvjz7PJMkjNlti50JJzY\/ODa8Ray\/HwwX1sBWf6m17nmBFmuOLLkxbNeJpICShzjemohoj2n4lt9EbodO958l2LD7VbMJtPj3fja+6r56NYyjBlPKIROZ2GkX\/an7PN6tHcq9rgbFEPtBtfHyqcsfPQLHkmK6cAb+yON2W9K0WqmvVL4DeGxFWH3+Hg6YXFR9WZqVynRwfADeZ+YMN0SmcAar8bE1jLjdCvyvZLLmx8Svhk8kn9KNJACO3O3Dn9dE65uKtU+eI3G1baR\/KMkF6\/iStE6dYwNYY2nX1oIP7f0VM74+\/u8kjCZlxXPhzBf1E3Fi3DvpxTbt8aEe9WiSutTVg\/BQczihyPJr7WvGr95k\/ktrHHUjDMZgu3Mr0coMl\/vbr5b8OAxjaXzX\/a8cOlBx2yjX+kkj4fma\/Fl3qcRU2DVzi\/QDdqo57My4SLZLt1jZoQbLV9k60\/72Yniz7RlTz2pA\/7LhQ8JJ1d679PcW90PVb30IJ1mov\/6fLNnfaRxK2QSCwwHYfvjYhTPHhZkD2x+e9q+BdNC3ibNOv3v5y0kvtrMGJnGQmocdeFVUj1sVuYHLtYvRrpLvlufUCXSX7ZLOTY2gsvYR5H3FwdPDitosdQqsVh6aXAnsxEcY2pZ6K9\/15WHE9eMP3sqoDUtK+SXayNep8XX60wRPmnb5ncmgMbmx5muY4QDn\/Dx5ymVsDGRvX1WDan\/209tNqSS+q+7GhFSKUj6AqusXhB\/2Gqm0rieLLf0VA\/yXc7AnJLbAadI32XqHf7097nctePeOyZk2HhQm+XMQ+arwvowW4bM1+GPNtZNRMdd3Oxf85LcnLHAbfIiGf+Uu39UdTezYZMqcbq4uQeZaWsa9qT0Y2Dh1OraHAon7iSfvh3UjUBuf5WI2D6cOzfWuC2JAqO676DrxX5cdVkY0\/plEIEf1Q32Tv7v7mfp+uDAOPZ3Ht+5q6g4tmC04nqJu2cJFt80e7TSkUXy7sYg4bFWLJfkSxJtLkFiS2Pw4QEW1k\/zya+z7MIH7YhD4Re+IEB5YdM0qwrUC6R3wrMR8kc\/GB0j4x\/Ye\/NMwPw2LDHY+2Pn+26sjTNPvXqQglXatAOXSA5qv\/xMsoDkoA+VEUbOJAdp3BdwHCxswZpHm5+GKHWjZbfXPt59RDeTBDS8Z7XB9NF+rpE33ZAq5Xm3kWxn+TIZJznpRsyZE1ywZm0nrpX25Rpv\/Lf+J3LWXF5tXIe1oabz3+e3YeDMx5sWkv9e30ZnWVtXWx107Q92vt3cDplD+R1lshTiJZdwLD7V4EWTd9b4plaY3x\/uvSpM8k7A2rIPEXUQVHnab\/uzDRGO0dbe0hSSLx\/rnyT8HVl6X9VdphV+o1MlA0IUasw1xSosa8H3wfP9ipZWvFyuM9AsSqHrVqmp8cNqvBwwmm06rwUFO8s77fkozOwO9Csh+VruxhoZ4SiiE8v7nOpE2+H0+m5NGck1aZ8t5U3fkFxlfCV4r1U\/kgVujr8WpvFHLWZp+1aim5nDfKdH6hEx9OOeeDTJNw\/uGkrEsiCgNnqzTKoGGXOOR5YTHbCof7f\/zN\/3Zi4NH\/Up7odJxpya4kcUNsgt5J9by8LvzXprzeJq8HZblNvrEQo\/c7dmK9SyMXK3Rk2fWYfwH7mSq4mfGe697jkuSmPqVHCSmVwLatWP+R4iuvPpYK6lrwD5xNqVQfNbQMnG1PCS5Udnytwxm0d8Z8r\/ewd\/Cz5bPqw8R3Lf\/WufT1wjOf2XGeuzVE03GMJ+Witv0bhckuvfRXLAtWET3ZHBZmQIVJXUPv37PqCnNzZpET20uHm28GILBB+VPKOKCZ8tUbB+4jQE2rz6693GKhRundt4mYvwzBerq748HPQWvqOWHKlH3R+dMP1LNC499LvkRXQj+AXPRT7CnRvn59aOEF3d1x3zS4z0u+ITW0tN9SEIycfKHc0j49\/KsyaH5ErXtFshQkND8MrI+1pI9MIquW7\/BbJfJ90UJn7WMOGUnLquguTuYAGDLx+JDs26IyjrljiA6a3CV06RfD4neeKpPTneycHD3nb3WCg89\/vT5ZtMDL\/YeIaZx0JaRM4w\/1kagTVxP2OID15WvuD3fQYbi02UmwUJT55cP5G88fog7jeoRFcfYSC0+sSB+0o05rpPnBieZCI4yKi2YCEbv32\/ea0j+tgoqviEP4WJk2nZR582spAl9Sym8Px\/58\/hBbN8MkKZqPX9EnSoohzmQdbz5WMK4dJzVKp+vB6CPleuVKzuwN6Eg4+rSE7Il3GODPFpQ0Lt7hkBJM\/vay0a5rL7dz8qHysJ+HG7DQ8akvbXjXcjOHV5M5Osf6TiYD+ffgNs9teI3\/DogMZZ2TtGqyl4vihcXuNcAz9rj44F3S1I3HzPSYxw3Ru3RSPTSe5Iq3OccnEgxz1N5tNb0m+fMbPqvT+FosYcHeNdLISa1N5J4KqBlNuQ1gDhubUud3WsSW5790C0mruuFpI+SYVbYjlQsFotEfJqEFwTnUXnQqrwzXD30QoDDjz9CjekuQ7g3ALtdS68VaA+O6QV8Hbi90P+bf3jPRigpa49P0fhs\/aZ6guyHfh6yjezNrYH3kUf1j52o2D4zUEs93ErriQ0qFjd7MbYfmrPZmvCl8vV\/fL9yDzJcLXWybTjmOFC2TfKpWiz\/jZk85yJlatkOzXSqlA\/saOglLcIp3vWKWSt6cTtyniXJTy9kH8RLqjtQ8FVrvzk3eZeHJrT\/mXG+QEsCxyWGK+hYGaa0cmrNIjSkB9tz8UYKH31ZudcWcIjhx131WoMIqCudh73Cgas8oPF7y4ndXK4YfxcQz8shl68ERIYQuqhEyUD02mYn73NnOnCQE\/mKd\/1HUx0l\/wef3SAxsPjfqb0UD+Mn9ck+UgMYckFhH2YQbh42sv2cMKxYaed9ywj\/bVyk7zlwSUDKMt+qzVM+IdfZOnZdMI\/rIGYWaztQ3D2fNcqSf5+JJZoLZdB4\/cJm6N\/djPAsDU3ELlLw9patOHvcyDnmS+bei3Jwsm9aSYFxMejh1VPqJG+PNtT6BS8lA3tjnKBr4EsOO6sHm4xaYfC7hXuf1AKDffYD9zGbAR3iJyfjR5Y\/un2P9dThlPV+Or9h4PyNdyL+\/UYwModqXYq1dBNeTSZa8bGryNmO2IO9GC+S9vybxNl2GaWMr\/jBhOPM3y5e6LKYWc4f8WysEKsXybwa1YwmS9vzeiqZeUoVTEMP+7\/7+sd3wu2pvx9v9uetsO9EpxiNF9aPXj5ZwH0ytL31TiRvP5Tfe9S3xJUnZU79HpeIWwMhJov5NN4fHrl6gWhNDy\/nlj4TK0VnrlnymJJjhMwvs6XSHJBWKLTKxunPqz+snrdV8KTbd9cqUdk3O6dW+jk6dqDU0nMLP5Kkkfk7RN4Sb6dbNpk3srogf86GZXnZH1F1bKsxWT9rM6PkfamPVCXdhC9Wkr8\/FnsVv2FpG4SmPurSN0q\/a4v186goFun+fkxN42LEnKBgaTf7Io+yV4ieqvD0A4NJXq7+HpEjGQzGyeNGg843aMwqPJHdNkoBXmVs0mlDylkvPOoEvMhPP1FxMc9lvCs0iR9TZmD0L26MocKiN99O+ZpTnTUQJMu\/Xy7HZWTn0XSyfGODytFV5LjDb6uz+V0ug8VAVekH\/3lt44ImSOk3j7beOcnKg2h8LO28UkjGisOBDRd56EwX+HgcO\/LRqRcl28UqqYxPKhSdyCNxnzpbKPlhb24sPfO6HvC8994zXPqw2l8uLZuxZl1bYhn5fw4KV0Pzk7DpAmvdiyT2K\/AvYLC5Xrfd1xijRj7Nf+HrGInVIxXHxAg3DIVpXPMcVUtWjXFrpuTvo80NDl9cRGF7V+724a56yE1uHDS2aYdpfOskoXkKARuzx3KntWMRdXm+06f6MJzp6+8+fr\/\/X7D0fxOcU0BNrh6q1ZbCXfDfY6K5vCsMkwExORNqbPx7SFD1LGhGx\/CH1RERZUhoUp14zZ7Fk4Nl6Wm3mkFc2qBWnh+CVidTirZJCfwRtVs3Ek4RM\/l\/ds\/1UOQYX6VCyV9aml17rAp6dMnlVsmSw0YiBdwtReqIL5UsEp1hNQPj84abyffHqy8uEAulPi+0NEiVibxwe\/bOu2KWrrxI2iBHE104C3\/qlMiJE8Jaey98OB9F1I1REbDUIMcSwHh0+ktOCESb1Ayn4LQvqenpo03Q+GIifSl2i645junHCe5+2mSPjf\/gyocKeS51fm7CZGt9TpzZlIQ+XrmzQGtFvibVtYZfOuCvYYNb94eCtF8+9LU7zfCVWffG537nUh6Y69ss5lw2u9qzqgpAxE2h3Y0lzCxVfbROL8Vjf2rvnsXaTBhJM0+O3KBhSTH35Mr3WiYpEv4nr5DQybWSc+Oj0aekleADW8LXhb5Bnw6R6Pv9DqG930KOUOi4+JCzZgrmKO\/+DLhPY1OybE8CuKP\/5x\/YNUMs\/TwnapnWRBTKxJb3tkG7pOnH3svLAVP68pOjWEmeB7eUlZ6RTg3V9yHxVuMr9dx8CLpE7Hfb7QFk2kcE90lJWPNwrwXwkp3SN45tUPumeLf8wDZDUtoOQb21TvF2pA+f65e8X3uc6LvGSbt0XpM2BdYT8kQfT48ViqtSuZz0aaVXeqcfqzfbfC+huiAze08o51ke+sD\/d1ieYdQIvHw8dhWNt5+c8up4+vBxztu16M+kPpZ1batLoSFTSW+PVZB7XDcO+T8ZG8pGmYyJJzKmdD7eZG9dYQFnXXyh0d9aRQJfDX+9YONUqfbNY\/TOKiqZq3VIPurE+q7UVePQ3wnPns7gwM9R1lKknx\/9WV5S80AFr7zXvrIF8DGj+OyTkfCiC5IcHeZ\/uDgSkf61IezFOEpA5sbpO872i7Su0pZaLd3FmNms+FLH5UWjqFhNuXDln3KRItz+X3dk1VwXO++N3ayEIc6Df\/vOvX9GXvu\/71OrTYc9n\/Xqe36rxwcqGSiRvKPXerLGihMWzWkdq0Iu68f+N7uxcSjGoGENzWlWLE22WimeiEidWM\/72Yw4O\/3vf3DFhaGA0w0G4\/TiJXITt0tPIjr8Y+eHpjNwEZNF+tIKaLX7w9VsO4NgnJQlzzpwcDqGOvYCyo0nkqtH6\/\/1IuyPWlhpo4D8Ikbk9CqpqBsiB1tV2lcz2xcPov8vU42+VPixWbwCys9qiS+cFBNSb6F+IJdSGRiqmMrnv\/Ktqki472ad\/1p6TQKN2tbmRGqzUjnqlEVINx72X\/Xb0vSd7OMKaZuaRfsEo2mVpF+\/CX+\/pcH8dvHqZpmj493QaC6POYAySn2BzNMlSJpdPKlflvwoe1\/975pH4Yb5UPm5ePBzYrXv2BZ1rxf2PPff3+ocnl1o7Ib4eo\/3PyjMqXoe15zHzKFaNKeM9NHlInDTesyYw6z8JE\/49e1k6R+tPWyb2Qy8aoHXpqdLPgZrXn6nPjQyEH11XZjTNTN2HrRjKsevwZyFB9K\/Ps6TpN+v\/+KFBYsdUJLG5I60L1x6dqN70sRHShQFfeaCWmek8u\/KlXDVFznurV8ETaYzLmWW8FEEFf78ERCDUKGmsIrLxfhRX4W7L6UYnDqxSOFW\/WI8f\/43onDgergjpwkzyr0TFlUqVY1If9GzY3CGRRCb3u0DPJXomyWb4ZeXSOeDd+3\/PaTg8i6G6X7T1XhgfyKy\/dKm7CKluu7R9av8EmS+W7AxmnB5DgHsR70yn26EFr0799bxgtuW3mAHFef6dupD486sFJsmjaTHJdQa6yaVAgb3+l9wa47e8FhOckXJZdjquVWmX9CLebxVSedkGlD6LXIGQ1iFPZvMtCteliDsyV1FEu8FY+qOyNekrzsYaHtHXS2BhuSVGxOUi245vVaxIvw\/KZfSzWOu9XD43Wpg+aHdjxes8MrVJ7CH8mn0zxm12HlQz3FDn+S94\/8lp+2lAJb3ntWgGw9Wg783Fd4ph08Lc3LF674t2+e1LROcExqRmLVkGxuWhfajQvFindSOCGmfMlhohGGd5\/JF7I7EZPyBcs1\/\/v5mYqhBXTLIxacjYR\/vSb5xUMs3PLK01J86EqYzGtiYb1iwkl6SReq3QUgZPwFGSpPTscJs3HCu+NLtmI3XB9LHm8TLUOv9K7evevYmB1jpJ73vhvLGnfHZfmX\/WceiDzN2a6UVIWM0LlR86Y144nmKm9B4o8\/+JxVfjxjwyI7gd3mwkGRmtrt2FTS\/2WCWzcHU+AOPfpbYIBC8pI1ERNFZDw9p\/2xEKdQJ\/XN9l44hRtdVUWWf5\/\/yDdf775sO\/ZyDFaMq\/bghMLQ1ygHCt9va+qP\/53vXhlNO5NuvPU9KpZrRnTa8ldywLZuiCZ2rflwpA9b3X01VxIuXDl0x62ZtwvOenkWjXa9eLiaqSwXSOGn2Iau5V4U1t+hQxY2Ung1Uz5+nEHqn\/FWpXVNDRT7RXjnJrbgyl154yOEE652OOrOc6iCmrfPg\/a8JnwQfqpmTepfh7r1fsb+alInE58m3zWD74ZsufQcwoMHA94uta7C0nvdgiYZpF9iojfOJOsTw\/E0I1xY5zTNI518Vt\/g9OdzMXEqxFHEsZ7wcffPoKQsGj86+5pX3+1HTOaqCjuynpB02Y1M8vnA6YDJ2HQmSkIUM6pqaaR\/ih5UIz63vDbmu9TXPiyXfrqpjSz\/Wml3w5gsz9HafoJntA8i5u9qfF7QMK7PnROZTiOj0H1SqpP4Q\/WY04nPg+hMf3lyOJSBy4EavVJraUw8WPKz5kYP2tz2jp526Qd8owPZWRTuq32RvS3NhOQoK+yCIwufM72+hbjQiKq\/flzmSD8OfvL5dOX1IETN+NJjxyioTO67Y2rFwr3m1JOSgq0oPp+pY5hQAlePnwzlr0yc9atcMZ5Yh1\/PuE91zyyGqvOir7tPsqBHLzCl1rdhVkar53RGCZKvjW3v5GbBYal0yozuerS2yb+S3FeMIwyHPU4kl3Hb2J5RNmoHO2znm22apWD3XWoOu8jCjnrJ2qV+bAyxjr+ZG\/bff3+4eaTPIDalDF4Ssm4CkQ24FVV0T\/87BwvufF523LgMe82HaqTtG9BqF6I9NfK\/e29ggOYWp6BxJmoDoq2+CdXjikzcIR7pYph0z\/XxUmCBqea665t0E5bM\/aEv1V+Mg9dODXmos7Da4sJZO95mFPJ6Lg9ZWoKS8Syf4dc0pIY\/qtSTXFO8kmd5cQADLlXOHV0kj\/xenxuoTOrNUTR1ruPzIQho33tuT+pnPZdrqzHhcA8HSc91+X2EW5Yc3tpM473oR52+PJJ7eAb6RrUHkeep77GpitSxRFhbCOnzx85LVmQd74XmNefdV2KZmHHDWfxFCQvbjBXSxAi\/hiwUOTDvygAETqxQ5L49BKsbd2UuCtE4UOlw4rQDGzp++9\/O3MTBcafednnCoVf2BJ5Lt2GA+y0\/5VbNROaL+rWzrGkEGvgljzxiwL4wobGflwUFAQeOut1\/Px91QaqE6if8yhAO+D66i8Ze1WUhxxJaoKd+THGKScFTZVu54Fs2NLYe3qL4vA5CT47KpxKeeT5wetfVezTU12RtjErowoy4AZVPJJ+Mlgp76qrT2IDjbtmuLRB6Nxw21UijRmFvmmQOjeYCW7ZR5gBOHir8ZHaM1OPg4B21azQibh\/demgvB17bjVj37fuwUFTBpJM9gF2h714MtVPI3Hj311v9Liy1SI3SjeoFJbFp3vA1Cr+lR7WS7nVjPs\/jRQapfbiS271R9BEF\/6jNvv1rO\/HD3uXZb55eHJGO5TLzoWCKC6qnNOqRuGboke+NdvTtmbOz6a+vOWe\/UrBqAM9IgnlTYAeaj8jVT62mULV2ekXIlSYYvk4vt13XhVW9VlkZOhQCBh9\/OC7UAC5XXaGXBh3Ia5xz54UyhYsZSk2sC814liO3wv9eF+I6H++I3kHWfz9jL0SbwC+i9VuRuwudLarUSlD49NbqIuawUWitlDdAsZF33PGsEuHEniPKLqojTIQlSz2MIbkzKXC\/qRfJ\/3RYjMJIDhODQtsH3g2wMBS5cCjiAtGfi41WgUcG4Rk63a9SnwGhVCoyRZ5GjJL929HtDKz\/+RPaH5lg7oD+qAWp719d6mKpg6gwjMS7v\/dfn51OV6wmeno65VgzXz\/EF1gO3jhF+PrMDqqcQ7j45zyR+A29UPF24Hk+3o\/H\/E9nSxcS\/Rca89ud34unD3sjFh0fgLTnmK0U4ejXfJ9HVEnfVZccsw8kfXcxNpKSCGPAb5qX7VnSX7ueB+tcJP1VL\/ngi\/OXPhy5GpHDqCG5eIIxuOMVDadGBQ\/6eh\/8B6oHs1MpuJQlmpxnstBy7jv3\/poa2OZXL9CjKIwZS7xR+MxGpp23x9uiOiw+bGC38guNyOmlzhmJNBRnOD+o1u7G9AQPLXviLw7+6pedcmlYOeaUKIYMQjBJ8E\/SPuK7r69yRP9eZ1KL5XkuTcan6cQGx3ga5pXGz\/VJXSsoWN9rWcUCv30c3f+BDdVr1vpyFziYcVtTZA\/xpfqbsXsfydIY8Nipd86cRlfTNDn9zxw4d0ueH5MZgG\/Rx1uxO4fQfSov4x4vjd7r6TfltgxgegZf97aDQ3hd3mInTfKuyW5B7w3PuzDfAge3MXpR82bigUjEfz9f8c\/zGA+2edgRHksvXFT8kfDYFodrIn95rCbD17DrVi0sq0P0zMXasK1pn+Atwpln+dWHo4n+ipW90ZA40Y5bIzMXB8sRrqh67Sm1txl3dk9XCw7pwta5W6XXbP\/fXXfTzOX6vN+BCZu7hu47R4ths6\/s7bVfBXjxsuWZMPFxb3exmw7Ex+1EWuK+9jNw7JrHPZUAJjjlckFndpXhsNQ3qfUOhaj32qjdeomJSXm+cDPdMmQHj44PH\/13Dmo5Z7+p5wgT067R0RVPilE6sVpR5nsB7jrkzFrr0YvAZUFBqfIDsHDNUv5RSo4303aC69sg1mjLmZhlMjD19v3rwo00BIPNRWWLGCi2M13KJ0NyjJqLlctRGpVqPu3T23vQcSb2K\/W8HylR91cJ51LQm+gUTxBiIN9j6FtFNBNP3Jv7rpnSmFP\/0L1psA8PTl+5+ch0EOy9th8liC7XrYg2e7a2DzcXFassKxiA5UcFDn8LhW3z6WTLz504opyxIlG3F1HbuR\/PukS4TiVLxvdkL0ZCmk35lg9gRqGmdhDZ\/9GL3M7ejT34M9Sl6vq0H3FWcVFJpA\/64iNVhaV7UPdIQ0lpUT+k9Pd9t06nwH+Le5tQ7ACkPOdXdCYPQcR5l\/ORhTT6Kr9Yls+rhOy713s+kNyUxBC9N0Zy0+s9kT7hM9jw5heWONDZhXTq9plfnV\/g1nJkZo8CG1dsbbXbw7oR42RyUdWuDMMTYaqHtrARqzcS1dLfjZFl8ovohP\/O54FZ3gH3fGpROoNpmPe7FVHNZa8aF\/+7Pp0q\/f0EiD85LEk9Lu5Ho8g9fnC9SCvWmWWGzd\/ajP2Osz+5B3bhY8C64zkGFNxX83IVLujCZV\/5TfqOvUjfPKO7gHD1ALe7\/3q1FrRErj2XR3chwLLFz2cPhZCtK+b2vu9Fh8tK63T7AXSb9ApmVFGgr9quOJ\/UhVO7Nt071N0L9YbpMSYkB\/C8nbVdaqQHnYdNOcJ5\/Xg\/kd\/2IY\/CMsXIksjjPRCxaXyqbtyPWXruo78yyfyya8\/0p3Vjc7S89dl3fXA\/P7\/iYDKF8KLKJyoNffBTZva06A9i3oSFgtUQhan13\/3dplOIvduesMuXgm+Vx4p1pK+eRyzdc7GKCSP\/CYd331mwtRi5qXWR+AK393Tm5r\/PV3O2HnpK4YLumkUaRqTOP1sm3DzGwt0Xd9qVnNkw9hBc8OQGjZ3rFrsm8LCguHxkZ7ZYA0R5eHf42xWjeiG9NNWUjbm799s82N2Dnzq329MpkpdlX3KPlhKOXWJrEPG+EzfWSybNkvkCK\/09O56ZslBtNqcq61kLRlKOrC8OLEHC\/WShbe1svMs4WMDI7oOE5jfuhNcVsPrq93qFCQft2DOYG0U4I6g98axoFb6PG7ds2cxBX9qCt4ObBnDrezTvhsFK7DXsCjwgy8FK\/ptm67v6YWAxfj4qvhLOFw+I8JXRGCm\/Yngzm\/iJ\/kNZ3hVDSDU0ydtIdCe5n17LTz7LNtvXbfnOwJvazR\/6nnKwTzjHLGx0EF+W\/fy6LbkKf4J1nMuEOXBZGJLrk9gP6nGp17kTlTg\/3bpu1wmioz45O46THNCwzesTs60ab6qWPGtX5mDgoCungXcAT29ZaR\/KrcTmoGMeJ\/IJH52UONZoMgTNsf1TMuVVsNHI8+z4w4T+tHmZiyPr8WRY+d6YdjGe6A1kvV\/Ggn4oFTv9QiNOOm3g53lfjNNjClIHC5l4dUxj7VrJGhRf+xP\/9kgRvlnFabzRY6BOW8hn5QcmXg9\/9HIhnFAyVO1pf3QQh2anzPDZxkBejFhWPuGKnZd\/Tiq8YeDR2O+nYSIsBIp\/Km20J\/714KeYbiDJUxybO4dtGdjN59ZPKxLdq9tzJD6DAfrr14URwixUblz7KJqs\/27J57qlgjTyiwzql2zhIChCetywox4N9z4GKRfQkMiatYkdRUPt\/rtZH062w6\/06G57snzHn\/M4GE3jtaK3nVdcO07vPX14aQ3R2fZZAvG\/OqHEWt\/O2fQFImmrOgKmsyCk47vVK7Ue+XZRtw0MinH1ofsPSzL+kqXB83dUUGAUrKvi\/Pq3zz7nzb1ZsKEWzez7Kw0yWpF\/sVSjdhHhhrP8P7enVUOj\/dTsStEW8E3J3EzlI1zi9Ltc06oKGcbqWUdfNZE8Ztb4m4t8X5Z1vKJ7Ffokbu+7XtaE7Qd79VJJLrZ21GG6FlRDhHPg6qLVLQh62c2zm5\/wavZM23Xry\/Hzpc7+5tYGlGzw8FUb46DgpNrxrd5V2KQ3L3+ouglZMQudash2to5tV19A+MdrrtfNFaRuh3WFY\/U3Eu64lKdSRrhrg\/9STRWSizXiVLdtoPowI\/f3yQuVNI7+Mc+YekZjjWecXtHiXnx0OCGqTnLNJubV71dJrrmXpqAtS3JN9HLu3OwAok9jimYbuylUeoWfn6gh\/NCukfPenYby6gYurwgazv4LcFSTAz2TgN6KPxSUjrXvmb6FhqdJ7ZIHZBwUJyK6K5Mo7L0zTstMUkhJo849i6NQessw7AOpgw2ttkdF+ji40O2V6keO46HYwcryT2wwTa3LW\/05MNQ+taOLcBdO9qqKv2DDNC9W5Js7B4vXmHxY9Py\/51y3IIfRjJtf8Fww59n+3\/XYoWOoq\/aV8Nuxd3faNctQbRjRYmfZgPA7Wk9fk5zrd1D9Q+p5wtn5fJ5dQ0w8m9pzdMZBsp\/lceolSWxobfu5RtKRg0fjMgxmCg2b6JXPlVSZJIcPn3rqycKdgCwfsVM05o0vrdudy8JclZH1cq\/YCGplZc2+RcNIfE4aRbg\/TrNR0OUbGyfrzPSzSC7ocvLYsDB8CJmuiU131jBRlJIXeH8bjbVKCkVSflVYpnD3u1prE\/ZfkZ0hxP2\/47G3dQd9aqTZmFhZu0XXuRtnPC7P22lQBpP0PdFc5wiXt8x4EzTQhrimZ50qoqU4NvY1MFnj7++5WL43e7qRcIa2vXT3v\/v4P5+TfD\/L5RvJHysfLzMPARv+82zm6UbXYpXuBbm7rygkTV7csu83C3oJ3JN802oxecc4RGRGD+Z\/szbg\/t0HI3N3OzbJFUV\/Tka\/YQ0A77E9eXAIix1EIoIkSH+8qHtxl6z\/9vGMKjeyvtJKiI+T9RsDZRY\/+NmPYMWXnd2KQ7D2Pm2QMZPGifBjBzG7Gz+vRqbeXEPya\/PmH6Kx\/ztu\/9dyl1y3GuuQUvyYF+k717MehfqBs6+wSd9c73vG61kKvR2O0\/c41uOz8Pkn68nyK2AwxfxKcc7CYlzStR7qXPV\/DrD\/vf054lBZaNSIjzlNcrDoxKjsjAVZahTiT\/4MC46rw6vnztOmc7eD38ZTIU+aQmu4PzOM8NJ6pkXRM8JLu4QVgvIJL8kq6XhbL2qG95OVOY\/dujB05eGj7dsolH\/RZ0cFs1BKWWTO92lHlcRQk\/\/uUsjN\/y6pvoaNN8VeDsnPu7GFUTRs5V2Gtf4Pb8SyWAix\/731CtnOowMLon6Rvi1QG58jsJGNyNl72XIl3cjW+6DUEFyGWWk6x\/gTmtAuTBn90uyC9Z3xm+d1\/\/u87DVrmxU21I6SXeZSF\/17MFG31sTQ9e\/9opmOEuR7T66vNkoV5ODT9ZYZp0nurPukrfzOlon52Qu3xd5hwTdV0uTWaRqcreHNzyLZOGTyLFv\/AAc1HR+dDxHdvXEsdfm1eXVoUXK4MP1qG86wtoypL6XQf+XKmunbaTw4rjBdi+j+c5Mzk++CGrFCuUPSZSXJ968q8g4FEZ26EWv1LLgBEdUn1l0m\/tw8KFMwN4TwTt\/0IfHIBrSIPR1bOZ1GjlD2i4EZHGwy27oz0LIem31Opm8uIetPPYqJJvqyg3p6cr9rF1S1siMMSD4f+bbBTdKWxvEn1YtQ2gK7K6d3HCD6lCp0yCniN4WgokHLG4xmfJGVPcrzqwFCgW9i5gp1okBmhFtmA4VeAcXic1K10D+6TXQovhXBIksE1Ihv3l3jWWEZU4sAmbHZzSRv8gma34wlefPVso7D0acaYN7\/uEA3tgPqOw1evlhDQavK0ej8mloUCm8pf\/u8FdszrTJSyHaiLw\/ttM9tQNJqtafJ7R3Q\/JW+VXEdBelXqw54E5\/q6NUTmUl8au8DgRDHWgptTZfOW7nRUHl26bpLOBnX5IKN77U46JzXdlqFi4Z+7ezVRZo0XISSRuN+cyC178Ko8QSFqFPH+BYOsMGz0CG2cWE9DAvMX707ToFQx8xVTCYqV1+ffbjlvz+Prvr31QfmsUy8GQpLrRirwPcn4sKLPhTCJOHGw623mHj42GjGjpgKLN4eGbnnRSEuus94lR3KBHebzBZUlmNeLtL0Yv53zxXRSvApOXOPCX9WjUNAZCUuLk0ff19ViEIJ7\/eXSU5dpLj+tgA\/8S0HjyIPFwo+BwXP16kSPj4+dX+eHY3oba0aW1M4kDnx7btQRi8ez1KPvHpgAJKbg4O5SN55meUbvvR4P+RLHb8+eDsIR\/t4vWnjFAyXu+\/82NuHtFifSx7Gg3DvOXU4k0GhR+7G6tGBQeRsCUpjP2Ng61u2XMQGwo337bSOGrLxqJ0lNE+hB817NmXNry2DpXLVDvUdbGhIbJ+nJNmDtQ1TH8u\/lGGyzCH+HOFU\/gcb4j7QDRAQ8z4eFVOMlXXfDnQ11uJ7YF\/xY4s2TFXskTy\/hNSNVlFxc0AZLEIMD67ybcBcJZcPmd84SJCtvZBNcs1Ho2RYLWlA95gqxSC55sMHkScp55mwFVC5E3j0CyIanzm47CzEp4iqt09uM6G65V1TWXcFiq\/sXnTmXSHiv41Z8pQxsUp7+oS6Vw24Od\/fO5wrwtXIuO5gaxYEC0biq2Vbwat2KOx7Ugl2v1TO\/KhK8tHWCqZdYhN64ndr9HCXYE\/bzDPZb1hINvwo9pO\/E6E1c7jaekoRVWhTcWIbC8NXVo4IdDXDpqncnde0BKPaFkGnCH\/IJBx2pl62IUXErUqO57+\/Fy9vp0E+c1kt9j9ZFqMT14qXjr0PFBf9W1fFw7idU2qZ+BameDSdXQOmYfC21JgicLHsVq2sJzzLs6tIMn4IKSeihXayqrAnouz5wc+kvwOWN7ZsYCOgdcHMLf612K69ztWN5M7zvGK5d3hIX35mjM541YjU+xPBfp9Jbte3UD8bScNpU8yXB61tCPpe1ziN5LggRsKxS0k0bs48ebo5vhtap22ZAiTfXFN0dXFUJLqjdDHbZ2YTXp+\/bCOhRUP+wUkJ3SYOFn2cTH2s2wiT6j\/bXsQSrv5pc04umcbnSv7ICXMWVn9gnLEhy28POW7hJssz0td2mtqwoPGg\/Z404e0ehTlhn1\/R4Hvx5MLSR31IUIqcn19D49OMnzxjL2ksmawNne\/TB60WZ265aqLP\/fyZAYRr1RrEcjrLexGg\/X6zYj2NbYPrNCSzyPaX3jnad6kfIS\/qr6OYRsgSLqNzcTS4jtBCMjO7EJHSr2FdSEPK0uTaqRgajGk71+xw6fjnvCyaG7WSvesLerwYOz+31iNhV7CvAU18w\/X1vshFbOgmG2\/YsKkbdwtmPfwsXYYI9p4zZSvYuNcvKd52qRsuiqs2D5qTvuvfPr9enYPs0nkJE10c3IxMhvTf3\/+muK9PecfBvDwHnwzi94pLetY7FdGYeP\/YdeFaFrgMjlbu02VjetTrV8lX\/83tDQ1ZTDsWAw0Zo1EHwILRcy8DPkca7FceIu0bysF553Y1q60BhrMcgjWJT8oeMGoZlqtEjSHL2rm7EY1z1sQb\/SL+mRw3K6O6FgmifyZ2m7ah+MFU4XbS79+u6kltJ36xu3x5W3cXhdepvhffEb9w3OW7TyCMgsDh2gIHJoXPsQYDYjlEl+7xt4vO4yCST1d4cQ4HZrfNzMde03gTPLtgPfn\/tqGVnq7LaSyfebt7GeGlw\/dVz5kVctC9IOs0lzGF5xsTZa6S+RvQyHhkmcxB2goz3l1kPWP5dN9Ikm+\/Lj+RpHWjG1czWwUV7vVhjp9DwVuSl6xzFEK1drWhcbza63ZDNyY0DHjOHKIg9WdLU151Jw4GfQoW3N4LptXHlOuX\/l4vjni7rqALb2KuLh750YvhxetmD0RSaGDIm4vrd2BHV\/tZ78c9WB5n1TflTmGWtGFa+9sewmuuLsfC+1H7bvvo7vcUqvo+zXMnfRVoLbku5zuFUP3Xx4ZqmtHI8XAV+kghLE2TK3sVG6\/OzwiLd6hF3A4X9SByHLHnYuankJy+S26m1\/TsdsxanLu5gMy\/x8\/9KX9\/57X\/q8VpncRO8NiLzjUvpRH+Sah8LIHwRUh4ggajC00LPYxEyTipjqVYrSB1LvN50nVgqBOOH32pFGkaK6V\/fv3uQfIAeo9xbBrQt3Am08e9HKrxy9WjfjZg2xvNAPFxDqoWtOya\/rIaPCvutTwRb0G4SpzVR5LTB0afml3+yoKuwdVlrUFdULb+M+tYwheEJC+4QidyUJaw\/Sx3wyA+18aEnomtQuy64\/OepXNw7N5dW0++IbgPKrDC06tQbn25elsm8cO1NkuHZ7CR9DhXa4KvFkIjIRs7QbbzY7qh7q4BVOwYXSYxVgkLwx0HC07UQ0KpV\/DCm3boeErttpSn8ELayfZEdw28VR5sCrdsxSelmgVHFlIIWBXj67yyDkrvXxc432uDX+Qmcf5lxKdCO\/q\/tVVD3+pSR7lBC05KZ52Y4qdwyY9V5VVVBcWc3kVxys2Iz7XYu28WhRuxbn0\/ftVAef\/N5THerbi5JW\/7ehEKZ8I0V5XkkNz+JOHl9Utk3nxeuDSJt8LozuqwKTKPa4JY9xMI931UrD2rsaQD8Q80xi0J\/+2ZvzTLdYqN4zOnsrL16sHtr3PTx74OQep2Oe61bdC\/IfZjTJKC9uJCw\/f5DbBl3Vh0vasDw5d3Bm8jnLZyeZDjtoIquAkfc26Wbkbv8tBPM8h+2v1xCpsXzYa7ssD6AO9ePOxYcpxRXA5Jvc9XWxXYyJ60rc4NI3nr0GTbErsyuFvwiB7Zw8aL6cxQVY0eWKTGPD7aVYZhQ6dVPFMsaG4uF5ub0QUHoaKc5Xlf0BQn2znezcaTQ9WGG6r7MCoyObStsAL+Qcf3Cuf14J7GwlK3W\/04v7FXqfz93\/ERXm37vgtz+Br7Cr\/3Inknt+A60kfjEYs7FtnVIPJQgeWX+hYYzWxTL1tA\/EQ+PidrSy1ib9uvic5uhd6Ln\/0zRSnkx05eaywfwNKM3RF7qoagGzm+\/YYYjVXWWxeYdPViUcWGBA+\/AfxYHK50geiPkF7siXeNNEY\/xJy59eHv\/VUN8TyxAzB4MXHPTrYNq4w1Fg9+7kaw\/qG8VbYUNj2YetvwpxXi1Ik2wcxuVIsJP5x+kMLHvJtbfuQ2YmY7x34guxNqm87NttCgkMP3o8H8Xi8kc1\/NzDQcALd3U65tBQWFY3u8H0l3wbGzrWDSqxcxOUemiQWR+lk04vr4Uxcqfo3bpk\/1IvTFl7rCyP9+nsH824NPXYpszP+UfoId243pxXLrW4+XIaPz1LNoHTY8pvTD\/X51w0TZrtr4ZRmuBa7zqTAfAteIwMZ2biZuLN+2kK1N4251QNMj4osHDLXmXiM+q7w2d663AwPHIsJmpv+9brflMu\/XFBo6Im07eU8xcXF23x6eaTQKxCSXK26h0TSxeVCbi0LwETGudCUKYyeMFAwTiE\/ltc4xPkryQfj8w7jAgsVvxSo9Xzauqs3krg2lIZyYNJmpz0bu1\/D2Jcs44DdTrht+QGNZ+1zTx5McvB2T0W5UYqBO8ZU0j1w19MwSu\/PvcKBbEFESTrhXbeHNEc6NKhRt1Rm+ZkXyzXHp3ewXTPCpI\/H6p2pEBy778meYgTmvhnZc0WNBza+NkUH87kyuQOVGdyagGpRj\/pSFa35B1ZZeJKedTCuhJwZhOb5u68RbBqbuHeo\/oEbDO9M8yvfUEAQ\/7N61QpQJtf3mSw7r0RCNnlqieH0Q6wrehhUfYYCp2r8hQYnkyXNHOtqJf2o5MAOPe1GwiJqrLPGJxvCT6HC1+xTOzrtu7Dn29\/mu6om5iRQ0GN5PpDdwcCDU79fMDuL\/l3qmit4RX67JOxv1mIJk0Gbh7z8orHA\/MGUQ\/b87H3K3fbHkIbMqfC2Y4bc\/rQkPFRWe9JB5zFNYtlahuBqWQTudv6u2IP1rSu9hoodZUS73S0hOkJi8KIWl\/ZhkP\/Pke0FhzQKH1GneQzjC4RHRkGBi2aC1IM9WGhbWPkWnrZkwZY+pr41hwWSGg6QKye+iyo7dr9r7oDDhtfid4SBqAoW+i5GcspodMztCZBCz5oXrSPMy4BEwKVYhRWN60InPZmeZcPUJWDr7\/7F25u9Uff\/7jySlwaySJo0kmojSTUoqqYhSxkQ0qDSgEpqQDAkpQkpCIfNUNJjneR4Ox3SGvTMUmnxXf0Cf63p9r\/dPrtdqv87Ze63n874f99nnrJ3IRln+7BIBx\/\/++WSDJc\/hyyS\/O6sms5h8XHww2d5caVyPNfy1zaPXKcyy2plnR\/LBBHWLL32sGvMssiwNNGloxLzIWtTDRdqJlzxxxo0oOyDU9OARBWmhyAMTvmxYiLxtjZeuQUd3zp3VJNfZ31TNN1tL3i8\/Wzo3vR6I31qx8QwXHh4dabMn+qCv3qxVrF4F\/VxH7rx2NmKtnB\/83TfkCicmxN+sFJkCvHvGp\/Wg1Dl7j2JVL6r5Vifv\/0R8gqXHO\/9VJ7IO5k87ptyDpG6egno3CvO2HAu3HGHgfmSc564hJjZ78fAkvqHAc3HS7bxCO26k3Bc4ptyN1HadWl6St188vVZ+9EU1+F3jczRmteDOdIlbhsTHm4\/MEv7eWIqklLIbB5Y3YKVmRQiGuJAWtLZNIH22rDHlk8NgE4T2ZlVc4fvvdfjZ\/kH6861V0HIUMlvr3wSZKW5W80i9HZVr1tzmT6P5jc1uLS7JsYe4L1I+NsO60y5w0pfCK6lXVkw3Ng72IXJMsgZzRO9xppEcUnB6qEFrDY0ZkpHNA\/taQJdH7rR6QuHupdSFjCg2CpwSbQ9uqsFJm96h\/DwKYdKLn6YS3+ur7rmqaf2\/23\/jX+Nmj+9FPKxgIfio53LlMMIjJUvTFt8txKD3GY57FwtjIsEKR5NqcbR9+ixucSGy+CTn3uNQSHR5dz58HY32c++6dstQqDtk45n3m+hA3\/nPjltpcI83Siwi\/p6+tuKIPukb952tDdvW0vh9SDjv3WoKr6UV5679QUHzibdGOdGvyIE99vJkfXuwpkvwAOnX85sU5DOJDnlpaDUTvfpZVpRjQLjkUHHTjM9RNBiLAi4+82PjJX1Rf4EXF6m1KvIFSwk\/qei\/6f70v9sP9mHOqK5EEwvO+zKHPBVrccukSiEwphC51mo9NmS8u+LdWZfNtbgmHu1SHVsIM5+wJYKxNcDvcEnTJa3YE3fItlqUQuYMT0vF33XYdfywRtoRwoHBOVZ1KyhE5Jl89z1OdGxox+2KvGbcVctT2zeTwoVnnyQv+tRj19bOgrv17fAy5YhfkSXH\/zK+3vayFNp1m5Ivz2hAR7G2yd3\/Y7\/6o8bHm1b8qsTZOxIMx0NNOLls3dsjUygcDrGbefx6Ca7fzrOXOlcPdR0twT0cLn5anOaf9oGN1Mm284uSODjGuSs38HefJMk5F6TIet6M8TlQeItCfYlJ48EYGkd1nQ3VSd2bu7m9V1rcDp4FbfF88iX4LpYlfEmF1PH+X7956hjg3lr2tepRGaJvP1lzM4eNiwtG3iirdMJnyvGI3GFyfKILt\/M9G2nmP0592dUJ8zm6lsZjJbDXF3\/Zd5CMC78xL73Ygo3PFikZORbjXpRxrhbpr9tjkbOl42gEOfLtW57FQoGJpujG84140qatRV3pxBqOuFyBCoUFU15Mv7e7DZ7S54wWkfORHZY9sJfkqX1aNdtnE788neRrqXGCjbWPU5pd7Gio\/mw2enusDdfTc1ts2wi3XO2+10eO751jY\/4yqBvzDqKw4kov7MZWit8ndTq980vPfeLPK0yEkrcS3Q3XXdB7YLgJB6\/VOnVJkjxjcaHI\/SAXEoZ0BL9gA5b8TLh6huQjgQj52NSnNGp4LyZyDDpRzEoU+0n0+aM7W3ClAheC0ZJSMh\/qMbRUJqqEHH\/i6wO4kTzluKDmdhvR2fR72y+88GVhAWPHMt6PbNwT0y4Qukbje9PF6UZ3+pARn+\/RFzSAVo00ga2iNESUvlz9ZsWCi5SvQkE4Gz\/PSghJXqXxsmYwfDE1gOvzdv285cRCZSGTp+IgyQe3GezYpRzEmv80eMTDhZVXpL4tyW21Aq6cvPU0pr9NWqRxgsbGPxmJkvFcVN49t+vFc5KPRScyp8XS0OKfiO\/oJevyo4h3fgKNEbe2iCDyN6xnXls5P9GXuY5PJ2ppWOU4n\/BL\/bsvb1D4XZ5e7P6yovYg4Yvj4s4bVFNoJN9+5sjUIbwTG6k7crkcG6P\/XDL63QDl2avql4z9u\/53B7mdj71ZAsW4b4VNdvWwOVcoZUDq\/F1buLa4NYVCjsLV4yUUqhtVXFv4ST19L3kmGUjDd8VgeD2pryblB9JFqYQL5t7xDvEh539TZ8WqSKJHr3fEgsyL79nNrQYKNEy3hp65ZE6jvmdzqEISF1ce3WWvzaaxtdlAKZCc\/5zhO5yX2wehdtyZMo4hfjHftc7jF4Xt2Q+OjxGuXp5zqcOD5DG+Y8cp\/2eknpceTfvYxEGVm7yKtT3J96fU2PdJTtggcNOKZ\/i\/+5rB2iTq4McSbB\/gie18WI\/LB72na3O5GOqqnvW9ioWPLUf3zvtG6md1ack+VxoPLZe93sgm+eX6rS3q\/QPw\/1p49ro0DbUC1rqhRBbUo6oP+7Wy0XIla0zNmYanZK3jq8YBiMbJPxo9xYLeXgT56dLQhqzo2YABfDvrF39+Iwu5NUuV23fTEIo41r9vkI0v6kvOR9Rx8HSjTLcAqevrWrkL7tg0QH2ryGEb\/w5Itb5MPbWeQk0w35NG1zZ0G+stGOIwMOOKU7m0JeEbu1rXd8a1+D53bY1MWys8vn2P6Sf5Kzt8eEv7tXosaJHJ9fvSjtV5nTb1JHfv2sQTZJvWhXNWz9xpugeqUnzM7P+P793ZOzjYfKpohYzeTP\/qcAaOVQ4YXTQhnNAvNzfrZR0yFnovlxRsxwwHpV5e4o8unxvDv7ypQ1SYtNwckXZwjceu7STjqyz0b179wkHQUde12\/YxceJwwtRyywoYr7NjLjlDYc8nl6XpNAtJr8rtI0n+X\/3pdfL8XA7ex3+K6t7AxNTj3bP6D1WgVHjDyq\/DXEyI7Dm0UXQQvtE6Q8pS1dj7fFGtPclfAsl\/Nk8EM7BIW03zrE0Zvq7v842yo\/BMNujKhyoKwrmhXsfHKTguaXF\/UMWB17tNNtO8udBwGXGWfEfy6F5fs3ur+5Fqayu\/WnIQzrf0lwTLkP4c8fUw6GPhz2+dBTL8HJSLFMca3KKxjWfdOvbOQfSlbBM+9J6Fdp9lUZeN\/ne+LPdo3l6dbg76o6TCU2uYWDilMs6isAKflkReU+ThoOVb6Hqvui447mm8MKOpFL\/eREvulOViwfIVW5+O9cJRn976KLESy3kPSq9cRMEynaF358MgVFTMzD+aVyO\/6tcX32oa5qN3+qwTia7zTFNuIDm4RaL9inYl8cP7fTvcie+8SVwUXsfbA97uid+BZPxMIM88eZJDZ0W\/cSiV6UEEjvFFEh24uXbhLxbJA2K+yXJGU1sRs2AsrJfoi2ixZd7f3xcmPtpn1JrAgsX3TElNPRobVkQWuhAd\/xTNOCfkwMVd\/pl5h8spPLf34TEmfvKzfR1H7Cipn5fv+VvCaNgJCRR1kBxc\/0FhcqYYG092N0vwkD5eoTiwXjqU+HTS3nhN0f+ev5ZGrY+S1CmHaEXaw67+BiTbfmF5kdz4q+1Tku1HGv0xEjqnH9C4W6CVo6HYitm85xQXlNO4lT+ytv3v\/oRWk2qO4v\/eN6l0+y\/XoTuEJ63q7MwYFEwHVzg\/q6GweHRHO4guP\/Cf+nquOI3LLkM6OiZ\/nw9EnTZ3p1BydtcUxR6S571757hUUPA3CQ9tJ\/4zu8Py2N7tRNfPBw\/uK6Ch37nHQ1mc9KsM37mCz1xcFTNf\/zKdRj6f3q2SEhoel9Kes4lfHb9WfLt\/PgPvsn313YjPpp3WP8ckvpz6omH4tk0nhtvU3ozHV6N+Zaqf07wWePw8uz2O8CrdFuu6bHod2Ks4AY9vtWF5jNbD39IUYq6ulOFbzYZNoOHC3b8bccIzb+eH1iLM7vyWav6Yhbf62ovuh1TgdqQsMt4VQPyo+9VtT1mYN7zs5NmRClQfNF4Vl1MAv4vpL\/3l2BAqt9s8urEJA5fFukwGi9CQ+v6DQCjJ+XOVFqbIVqJjnfUWn88F8Dk4\/5n2CjZULwad2VXbiO+zzCu1qotQz6\/6bmo1C8e\/zZOTITq\/UqBfcj+pD\/PIjdOi2lh45X1ts+0fNt59rBexdaOxeNp+7e+budAKPv20u53U31TkfiZ+7LF0Z0twHwfTl2jMeBrGRT1TtWV9MvErudL5di0c\/FDvO90XwMUJkbzPAkn\/Pf+e237inZdhNTaN8MZ6ZDcj9vu6NysJDz8p\/nRyM1lnbU8Hr6nzaJyeYL0ONiScPPihYMc+CuM29+yOpVFgP+akaGwi69Z81S+O\/G398fD7uZPEb3rCalbFcLHmcarL4+UUuHHzH94mOSw0cuRJGsn7MzaOpFWHcLHyUFxweWY\/9mSbV0\/zrcKimT4WVUJV2Pty5ICcVRMu76zd3UX4WdXfejxJugIapp3bBQwbMVC3vtN94t\/XdfVguelu9WqcundTc+nLZjB+KhrfmUEhy3IsvOJnK5TuqHXrJzNQHL75c5cpheQZbaEDUs3g33myP+JyFxa5XXpvt5vUfeWTh1y7NjyI0eZV6GUgxC3kndcJClcPLHIcmNEIC91XNzYs6sT7Q83THyhReLjebM5IKBvrnjIPf1zQgRZ+EWMHzxLw\/i4vlJ7LgevCRVZFogykZKw5cpe\/DHK3jQOe+lFYE+aTJMyi8O5YqUfXB8In4c8572Zywb7w5tmJbC72BMtrvUgjfi1bMbqoiYs3MunxCmYU8k8e1NxK+iplncWOoGjy\/7U65mz+Sfj7cfnk+GMKHzZnDly8Q0OpKlBnhHDOsK9VZFwxB+7Je\/addqfxzL4\/Rz6chpuJioR9MAfP\/Pp2XGBxkJsyLh\/7nIuaP2GvfEm9BZpd\/ZbGGIA1N\/Bo9XkWND+KWT48QGN8I0MhXYyChxLD5o03hdUR1WeC\/GhcuGk45tbOhtgelamqpSSXzA6fPviERu9OebGtH1kwLB7b6z3AxmU1xaTSm\/+9bns5reVNwSVYHPFYIuRGPW6M0+4phDO3NATYtQeUIHHOFvPbhEfu7Y\/ge0XGb\/X4tYv2tEK3s1sx7DUDi4+qCUuSdTeen3DlW2wvzP+MLhDl9uPG9Neb\/Eiuzv4w8YRh0AHlwLnJnfHdeKRo3vTkMoWpHL0Dvy8yoTooZZg+1ocu9ceMbx0URrzsLP6kM7H3hWbaToV+vLWyLDra+7\/7nlh70Sv\/5RwWdnoYHW85WYcs\/nkup74X4sd3TeecUZKLXz+y\/jZQh\/NqU4T1JIsw1arb2rqe6IxHcKPq9FqMXP+psje8EDwZDh+3Eq7UGa07OEJ8b\/Z9Prq2igvjHINKdZI7OVaBdw+SvL8lybX5fiQbd8KfT090+7t\/5gnrSuJrF4+cZZiMceARbO7L60ljudIfvwZSP1Gxy4X4bnJgfupHnwnhdbMvyv16JI\/41R\/KLG5mQfiHyNBzUi+mH5M+eBJf3rx2tPf2dZJvpBY5PK7govv0S5egIxQCPk8L1Cum0bP6GUwaaHA3ZD1\/Q3QwZLz\/9KNpfSg8VXDixho2fjvyL+sUbYJdXtclM0bR\/+zzzwxDg9BkrxqErPX76jSlFXmrkreNihDfv6yScGse0ZO6yPTD15rxvfG34wkBCks7n3or0TXwE5LPELZtBUeVL6xY\/L+v+xHZt82Hf7PAyFHcLXmuHme6Sg23bymCHsd4vpEQjaUl9XuWKXORe+XuC\/eqerAlophyvDRa9gwsPjid+Ma3\/WInTtSD93ae1fezLLycdbvmeBQb17LniH4iefNGw9DsdVEtOKQrWTC0iIHIORa7v+tTGA4\/F\/DpTwfEw899PTvSjfMfZz\/CdQonlS8z1Xa3o5wngjFVoxvR3JVpw7YUukel5CQWd+FH3bwl4ld6YHLmwboawgd+tzTvb7jZhMcHjg\/oK3aBhxV+wWbH\/8fngf7XMh96VSF047Yj6\/ua0N4\/Z54ZH9Fni2TtEMKHhzdbuLsQPtwedMole7IHj7yXLpsgurgtIUZqoy0N10B11vLOFkQetpCOIPm2v9VzdzTxI4Wofepv6lpwS+Zm2r4LNA42BOUVX6Ow6JtwJ09WE0QyVfrLAtmYXfIxaJY\/B9EmDGmRRyRP51SdbqfLkaG1hTmk1oja4ebqrv\/j+blGZa+qiubUIDg3dsM65xYUnl0SazWXgiy\/6l75v\/tJCjd1nZ7WgGHBS8dtv3Lx5FBBGudVB+6qXj6TX9mN8eWHnUscKESkK906ad8FbW+ZyrSMHtQ1Fwpb+BC\/DbXqvfysHbenp0\/ynuzGsLiDw5FzFFRMLk5s7WhBE0dwa7QyA2cWDD8rNKCwI+ZYh65eAwpmiwmtdenArMnHAUmKJAcrWkofHe6E0labnfsNeyCTUCLWQLgwjPdw5EshBmymvDFXVGFi40EJg4anFGKvbC3+xezGB\/FnTrapvTAxXz6ZkkvhvXHOFNUPLBhRKyt+RVZDWGbO+3ta\/34e96TCun34RV7\/h5Dn1XEmrnWP3T3xlrx+2pzWGjkG7CTmm2scYOJRHFvqx9\/njFxcf3eM5FT7W12Wb6Np7FzLN9qsyYapUZi4L8n56f0eX5pIXnKTiVyj82YQ1k95MpUIJwuv\/XNBjHDnSx6ZCf+WASzvGQ6+WEXDXSOlgjeexosFA6tk3Xr+c33+yEw8EBJXjmNyjHciCxoRYtM9Y2CMC9qs71U98eG1tyUdphL9qw6+avSS9NmLqfLZ+mQ8KL3\/ETeCxt6ZH3ed6u9CcPud5nyS47u4mZ14TeGYZ\/TSjGXN2Dcifs2bQ+H7\/O9jL9fRcFRX1NtKcqvx9ITAPn8am\/xehXNf0HBemNk2v4WNyXnr3o0vILxV73BJ8xCNudqrZV7XcbHjm21cvSoNvqdHBvlJX2imP3DNIPw4c063r+RpGo0S4y67SI6QjubjZupyURRr3O7kTOFglW5OeSvp2+UbrTQ6KeSm\/9n44GQPVgcvfDa+sA+xVfJ5ucWE\/5nzPGcF9SK6VcX4fVs\/umKk314j3DFjx\/j6DTx92GZ0Luyi4gCW5LwPWc1P8pll\/5g8yf8NW6vK73j3IXPULzKmjoLYDeneLy59aCl506L3aADND\/o3FYjQUK3n3p0AE7Hh6lELK\/sQ+fkRe1rrv\/UkdMEd00w+Nqwmc3NyOuox92vaJd\/DRRBUep03XsSCk+S993LaNbicNb4l4XwhTs3s3nn2Bwt7HbQ45ur10BlL3LtAvghhtSdNSxgszDwcNS81vxbaR12X51UUwtpMu2i\/dxuMjWa\/MxxmwGha\/oXblhTK1vBdFT3RAqEXUqu7eRiQtR+bqDlEwTreeuLP5Q78eTGX3y27G4+lrpvXXvnf3afz2GE7\/c3icqy9Hn7Wo6oBhyIe8bG+ER+\/3J7BiC\/DnNP35+4IbIBI7DZKd5SLREuhhyL5\/UjaKsFz+eEgFhwc9dqwkfjqo5OTLWc56FqtscrufTeSJNZUnEQ5bu6Y\/d0ji8K1\/nSLIzMIXzIy+fuILt36qJ7vdY\/wpNiv9GqSg4PeNXU1vyJ6aXTWcI0TBaVbq34GNlG43asv4ttHQSLM7qg4yWcPclZMZz2isOvKLt2zf\/edvnD7ktsHLmYUcPo\/7aWwgmNeXkxyoIdOTlCCMxtN62tW1RCeeKvF0cn\/e194rmEAexETTDq3VSulD9cWN30+Q95nXoKFv8yifnhWTcwXnDuI2ET5xb7LSM7Puj8jIp+JdFZGK0ulH6dSzJ+kkPPZ7VcYOeTUDdP2n8a3THvx3vVkxu50CtTB5XfpE53IETxQJrGwB463nvCsd6EgQqcOfy5koy5YS+BxeCdONXS6mc0rxY\/7pjXam9i4Ws+92pXZhAmn3cY5M4uRtsH9hmsI8ZHx0N8hszvgeNL9VuSdEsjdE+Q3kGZD7+BnLwGjRmR6qb2tTipCkXDUZpVXbHxpeKP9w64DK82lH555XYJbolPjLzoOwiucCnzYy0K1U6nRY1PS\/\/rpTOOlbNi1vHPetJmDNMpryhjh+KlKaumexPd5bYPXTCO+r7NHLzWd+D5fvax7E4MN10MWXgkVHJzdVjCqR3L26MDyegWSw2WVVvqlLqZRKjDHqnNzC7ZWOb6tjyecW2BRsYFio1tdUbunpQYHx9ry135i4rfL+aYtyv04mbTbz5jMZ5wASyHciYGKhkyj0z5MHGMw\/sx\/QWF0jXxS2HGir4UNyzLF+\/Cm53OtINGNuS909oTOZaLvCnuyKboPM3oPqSg3UjjRphup8mQQSjOTL8pPsrBi8+6iVgsa99yvNAdfZyHZZ9Py6e\/YaHsjdnoV4ce1GUFvq9dycHSXwksHkpM818Q\/cyLXA6fK2MnKQaw+sdxvjHCifcw800OnaPw+aBzHcuTgu5q2xordXMQHj2Rlvyb8+n6DcQDhXPNg9mq1UA5C16au3Bvw1\/dnlnqa9eL2iFLlqqR+lDTvLBP8TiGlcWOkdk4rpmccVal+zID9+6iYFmMK\/FnPW2R9OxGt8Hm94LoeqK2NTKNcKew0in6apNoG0\/l6Fn4VDKQ1nkxmmFOQjj886qNHcmb3rsiOsB5YvEtz6\/SiYGn+cfinbxtanfVaXEYY0M2V2\/\/k\/9iX8l\/jNottDmmnliDZcGHKA6967CkJk1vI5WJBmZbzZbsBJIZ9jy0QZ6EwWeWK2E4alxkfLHIT2JBV\/LnoPenn5U6v470CiT5g9q3hPhbS7i7aFcHPQevTtBcnSf8u1XKdcqdsEBEKX35tX8VGcf3Lm+PWNE5Wf8tRus8GvWnGpUoPDraV3tk49pD4cLfe\/jSeAfhrxGrW5g3io11OhZoKjeL+qaoWZF5rrrM3T2ymkbFvcVUw4e2EmwayciRv1Pqvzv1EfH+NhcvcW+psHKAvph72pNAaKbAoikmhdnLlBsVSCloe1j8v\/\/2d5eqKE36ED73HXt5M6SQ6N3+rWgHxTTVHR3QR3\/zlqTG4vo2Nkqv8Z7\/8fY7u62NCnPkk17gu6tDUoxApmTzzwDxyPQoXdCsFG\/H52bOmR+FF2F+zkhqoYuNB26b3kYSb6qxyJ5lKpRgPfOgUHMrCoa\/dimNbK5GyxOlzSv5\/\/974ud+xpk9zWbiiWZa0IqMadLemfdm+QvCeVyp1I3nf0El6wiZ2APaDCZsSvlZBxerXpREnGlWHVhrPD6Yhc6cjiLGRi\/yHYjIvCGfc+DNcERJDo1lez\/nSdxY2RFyZkU36Lz1dIPiNGI3IjFvL5Un+tXSo7hkYpDCRzmv2Zi0N+QNbQlJWkbodrVU4TNYzWWQVnwPJeWFvlOLmGfx7H5LXQnOYm9JZ4AuQ5RdRrsYUDy+RF3KF+GLluSW3gIWgZfusx1fUIEbOI2HNqUIUnZNcEsXThA3M+7sKRjtx40Zi4IXt\/67z4YDbwfNnk7ynNKia9KcTzSvmTK0gxw98Fz46as1GmsZ7kZovrTBuT\/esKSsG63z5fNkGDp67jSx\/FsJE0PEPK7vDKvBivuOsRIsa2Ci5rTlE8sD7r79\/fBSm0HbISq78ZhXu721i5Dc14fiwMj8vyR1pUcwshagaNCSzN2pKtWKxSQJPvCiF0pWMgVfXa8BYt+V8CN2Cd+zE7S6kbplXr\/aejKlBmuAVs4TFrTB9\/fhtGTlerOHQ0x7JekT7DPs32LXjKHOubPxKCrMXbbrtIsHFaZeGdNWYXiC0t3jkQiWsTK6PXPzMBfeakPSA4QDY47AuqajClzcWqcdPcTGkw5lXNdgHfXHp8CeqVci6drN87AsHjX0ahu77mTDMFAq9YVUB47RflPb9bmgJunoXnOmFxXxHwYcZhKunNDWpbO\/BlkvcxW2\/e2F42utidgEFrzy9XcWGLMzaKz3j7SM2Qt9\/CXx5mYaPWbHdmflsvPT2Fupcx8GcAddZm4nvDLQsflNLeHzxUhHPhIMcvA+rvafuRXzcbA9TL4wDL7EVohMnuThieXHR\/jc0vk7+Co3x4uLDB0m7Lcso3F0keOTrJxrM8xPlhiv+fg4sPnfImYuTTeL7wy81wNXpY4gu6d9p8RWr7nCJzqYfW6P5qRl3V1FTkwj\/60nYKvX\/5f+iEztnxA7id5P2QuVKogNh7m87cmgIGi076THcj\/HE34aqJD8W1wu8T35P422NSqp8dT9s5+sIlpLjlRXFHoaR81skGtdipNrzn\/tX6GqKDQ+LBflIRucfzToM6yu\/UKYK8VPNPrOxloV5PRnT9tI1OH\/fcqn+k0IEaptdM7nGRVKVm7rc5n4o\/IlsUjCqgnbHfWmHB1ysmXZHjLrRD62fhrcPXq1CcHX+bVkOB7cKO8LuTDLRu7TY\/tBABbxWX1LKfEf8L3rJlSihAfzOyo3dlVQF6YX2WgpCXNw5Ite1wa8XSl46X58bVyLOtaE5Z9YAZgpW7LhQPEhyG++yIyQnnKPrPHZTfZBNdE2PHhxAWvO00WJp4pvO5a2iBd1omn7x1KHQXsye3zVX6z3JlV9PL\/25nom2zG06eZ\/78P7Puz52M9HPuOshdlu4mEXvLW8hfavxWnDulGwag4yB7012FJbO9yllEt1dyd\/owTdOYZah+seHs2lEa\/TH7NxNIzj9XfUR9r91xjg8QOFBIhtia2x8c8o64GYiys8oKfnn8byz\/yy+tIeDC4LXVGIWdsPRvtpgS3EZbiekjrx4QPggzebXy3vt6K44tVhAvwSrFJJHP74qhofptiMWv+sgV96lsGOQi4NtOxoeZBeDL+pnvK5APUKElMa9yXjWhVB38w8cDLgunO5xk4uUxLeFxxNorJ\/j4FFCrnee13aBFnK9tQr+3xeS600RHrMwJePj8UlmnmS8buKxQB0ZX6Ky\/dUVSQqH\/wjrZvhSuPeZbTBE+kj1k7dgHsl3MhXym+aTfLejJIJfoP6\/7wcVppjSUvqAQpFGbq5qP\/G9xNPOevkU8ra6XC7w4OJmTJggezEFKeeXDTGkHyUXCj1ZPEpBMez26b2baOi4Xwk6LUHh5toAB9swCm95CnlNyb9PuuxhukZTiFozK+9DIxfdAbbj3cRX4LxRYgPJvbPedAutSabBVipI30n69POR0MtOnwch+bDCQJD4ivTMkfUt4STntvyOtHfmoMT24ngumb+Ol5FxreTvlCClgT8\/ByH8WI8er6FR7vvA6kzy3\/t7mxpOBjARPdTSVkr6XCxYrVw9lcZdq0YUyZDX\/+Azcb6Whu3GVt7TRCemXH\/2lKeQiW+UFONeFY11r7\/oK8YTv7vl6aN0vweXhspbJcjru47HNrqT81y2ZEv9rk1MKPIWNhihG7ewueXrul7YRoYxYpOIDq34pdRizoTjeP+7cqLDP7Yb3A5tJ3y7OHmq1Q0WSvh76BjCq7Nma\/eoOv7dTzor+dUV8t\/u+bNOEw7d7dG5kMfvf\/fcUr0pendzRWoR7+Wz+YxPK+Y8fRBVRtZL2XY8QS6wGrPZnrrHfzfjhsuEHC1IQe\/GIUltg1bYeufFbT7DwJP7Af7+RoTDFZbZc3164TcislK+sR9H7meNfflB4YWwgLUF4QfN7Yz3toQfdNXvdn0h6xxn\/vPcC8LrA0r663z86qG1XtZFTKMI0yd9I\/WU2XC4OOtd4EATjGNkk80kirE3oVi8IpxwJ3O\/8suwShx7Oto2WV2A5a8EDe8mkDyeZTuLnVeFTquc+xvmFKIzSVOlNpqFD7l0XuheooM\/u5Uyvv6br3bcOJpNb2Pj9c3aKd3byfUmxRp3yRVj5\/Eyt7wnLORcurTLk1mBVbGyx6qyCsAcLhX69oqFG3l3vHapVWHVrsM7rLgF6L2QOlIazsULo\/MP\/Yv70bO8yPZsYBUCKkuFLZ17cY31YKsTGed4JNpMm6Bg+HPJCXVFMo+pxeHNekwE9K8\/qv+MgkKx+M2fEyx43+RvLRfn4HFky7nNd2gIvbp\/8x0ZD9v+rdmfjP90mWK2jozfj3ORmevOBmNJtfO+exxIZI7IxRJ+3uZnZvJ2zQD8+Fc1C3YNQu6TgZeKGg2LLJ0DwblMGMz60b2J+MhAn1TOApLL6k7fzc\/9PADLOCsfm6Ms1L69WhqgQ6OuWTViSKcPtuoSx8LODOC6\/zmTVKK\/qxXfhu+p6IMrD5JiqgYwJ6z69ROiO4U\/qsS7grvhvqmYFebQC0f\/IYn0TFInlcEPdQkHvHGQumz7nIHLfaKrIuz+vT\/n97BHLo6+HMQ\/910deqwH9lKvq7lJ5VD9M1Vvx20ONtlIsFbL9MD8eVKA3P1ynDga6DRLiYuI9Lx1h1b2IeeG+UWXhkp8DR0TMz7DQaXzyrMv0rpRON0711q1HOJfr6kJ7ucggZGg\/nNtN2qOdFsr15dhQmDT+0depO86pbp+3WiHmU+Pz\/UDJQhSUYjz1OQgQ2TeRBVPN771z+i6kVqGUbXUgo22zTj6VkZ1QVAXuEHXV\/buoZAIweiQuA5sPeA97011N6bZBMVPOFDoNfbtLtrTimqF+plbrRmYoh9dvon00V3R\/S\/LjRgoUBGwC7zMxMpTIbnBEUR\/d0hFlq1sQ0PqxgPD+QzYBmfZgOTBuwUnROMekRzmlNS1\/SXJ8\/5HXCzK2dgZuUwmvpjG6UiJzIAsGs5CU3U1dQdgUHuD0evZioD1a+dPujFwoakqDccpNFReuOHZ04Cdq2Ye\/P6rA+fvyojqb6bQ8nFLs4VMPQZvN0yWOLajnbmqX5Bw\/tXgCyfmER02mWP5uJPosJngXPOnNzhomT+TW1pHo319mLt8Lo3dUSlbZgT1I4w5S9nVhUZ2wk1RsXjiD0Mxy1coNmOq3re5PlMpHO88EStmMAhXu7n3v22uRtlKDT15Ky6kmjfslmX0IaWie4akchVUv71vmkM4dufbpybhA31Y+eI+JU049scK9YBYkncCvxq9mRk3gM27ehu+krzz\/PlS9RlEt2\/oJ4bJvCW6\/SwwsuxwD+J89d8HfKGxoeiO1guS2x+7mNd9Y7cBX85pZxXR2LhlU6XbM5JX06cYH1Lpgram\/p\/v5LqqSrSM49NpjEacfahxrhdJiZeC\/zTR2Pn4WItOHsmJbbR4u0w\/PvCovHV7TPq7V7nJLZwNv9Ypki9IjjHWFRAV7ueC5\/yk1TLmANaVietJC1TjWepF75oZFPzUVWjuuUHEuJ32FVSvxkZ1raccS6KHD44lbQtqhXScwzLlj8Vovzl\/ysI4NnQel1kYhXRgiYLK4ayMEixjfDuXNZODiK9777ZOduGx7iq6c6wUUwbnf39lw4bzoOJJdkcruKP7dfRri3HnYhGvNLsG\/s9vBn462YpfFY7ZceIURFLzeGMOtODeFFP7gYku+HsnFmw7RMHMeaVd4qU6iI5OVj\/rasPXRapD9kspsD\/drxBb3Y6mHMdyk03dkDWflpFhQ\/x8ZGuL\/XADVpxRzeya0Qn17x\/flW3+332eeTpeyT3YvgLJ2frsqFuN0KwM2ff+BxfrN1lrfuOtwBh3RuiP3Y3wkgq1WTnBBf8CuZrfz8ux\/7rHgmnijVBSv\/bnyxgXLpMnrwrFUFihEV924BcF\/YL8MsdAUpcfz5a7E906adzy+LEAjXyh9YefOFH4sn5hrnBWF3xfz3rQP9yDsHvJQdMC\/n1dqcMBnGHCE3FGUsJmJ2iAKR1xurIFNjbhykOlNEQ4gT8tSP8eXGSUsOkxA5uiRqSc8mmw4tbkeAXR0Px1WGxVfDs+PUrhJDv24n5D0KWq\/H4Mf43v8SYcePi1S22JziCOh9xOcfhM8sSsTC+1Y6ROn7Zk7lg4CJEQg37vZyw0FmqqnjL49\/e7liaxXbJLWdA48ssp1L4GcYYBRjuuFaJ1qVHrA1I3hkoM9devGEi7f2D5sAmF4LMq2n8imrC\/1ynCCl3Q+Rq47Y4mhZmuXI3JgBbwfaKe05IMZHh47LXXp5C9bI+QTyONvJqMJ1tInnLnxMasde\/DEalwv\/QGGj\/vqVSeI9yPqt7yCbk+jM\/Pf7iC5KDoqd47HzNrcFj8fubroEKou8cqn73AQk1PxP4GbjEKRtb5uS0swJlfv1ddO8\/CLfvG4c9VxYgq55h2zyvAyOS41tX7RI8sqN0XImgckz+RO2LFgU3IprvCHjS2ZPX32BMdk2mYnx7mzUFowbzDr99ScDBf+ylnksL69AcmSd4UlK7ZXnYknJswqhv+05e8nqOsrdOWVsRc+uVtzkvWSfTFZx4BLjKFtqn9tKzHdfk19\/7cYmN\/hkfpTIV2MBf\/YtVvKIHMkNAVTyk2+vS8E8+rNcLaYe6xobgiGGkm7XWZwoatvfa8T8\/qURFi+dp0ZxFisjMfKtmzEfVrn2zfxTZI8ptFDI8VI+ngqS1X1NiY8XqaVJ9WMzaY73\/bKV+MdWkDBz\/v4iKYT8Um7GQf3FYcc\/Dkq0J+3qlXauocaJhsvd40zICBbFLp9dgyuPE76b7fwcH1KUumrv\/DAC\/1qqAmqQzN+1TXN8hx4RN\/6GwdyftFOt2Wz1MrgY6C45t\/cXFfYdP+UeVBpFdmT5ORrYbPXt314k0UOlyfuBs6cfD6d2KmqVQdeOwPu0feJrratIGPP4fCBzHRRs2Dzf+z7zn0rXl60prMg\/WUF7K8ZB6Ux5oYr8g87BD59EjNtQZT\/MLF7UZbILFa\/12EyP\/xvK0AXcRq1yHD+nqPUXYbsr8LzBBbQmH76p4cxpYBJArde8JhDwLrBl3eb6fhEpm3hLuG8E3visldHiR3z53SkvyVwu\/T4bONlzMIh\/nO37CHidRH\/AmWof\/9\/n7t0buGBSwWurS2q9UcqEO41r3RNUP\/vk8a9cLeYUEFC46mH\/bPfVyDNT+O7D5y+9\/H\/2t87umAmsXPaVjeuW5aGUOj5WzoEguKhec3jkXFE78z\/6jT\/Jz4u9+GAKFOnn60f5l+0pz47NRz03k6iM+2KmQcaHbqwXQ3gbUjdmy86qVSstEGg40B6fbsYrzf92TfW2k2WqRlPQ1MG\/FZaWqpTEoRNqyQvXHzAhsdbwQrHI+0oXecj2s8VIyG\/Cn1r3TY8L2mGOGo2AL5N4+vitgUgzYb6BwhuV51R5DS6aoOlOnwS20tK8GJMzLjH6fQ0FfDLi9eLpIW6glbH6lHBnXx1+kPXEQLDmZO7BjAPsX2Y8kFVTgqPm3GoqsULEKkdbVJX45vcnQ+RFVji+G0Um\/CBbNst3JXSXVjsd7oijvWFEb8bezC7Lqhne\/x+qBBL9KyJq5bplGoataKDJZmYFQx6nKKJhNT5fdYtIZQeLP8ZcaWa514tvx64P0VPbA5avtKypXk4V+1h+qcuqG+b4nfadNeCGo\/st2VTrjxEjv3yJR2mM+7kb16eTdaRsRS5E9RmHPvAdNrJxPMid7ympo+GJwznHOilUL+ommSF0160d1v5XEnsR\/Pu1n7G75RKNQVEdj1kIFtlnrLnj0nudTp4aPvL0ke06l7FPK5GyZtExIHn\/ZCI8Noj9h7Clv9A5d8fMXFEeZrg9W9\/ZgxEfo5LKLqf9anpYcu+OwNYUF7ScqzNtFK3HvglpGaV4CqkRlGxwJZOMd58FrbpAJJ07+lfI8pwI1f6SaXpnJBJ8mcTSPXZ5v+9WvUxkowV92bNFPmotft7O5HxCfyv27b8KWlEm376v5EN7Fwc9Euka0\/2Qi0H0mY7kYjQObakDHxEX4jbhDvGBvX5o5euOdKY8eYt6\/ABi401vPF5bVwEWM2vcaS8PLCskPrfq7mYOWIl4rNdC7O7njQL0X6QdBw557ejRz0Vy2VWyjExU2RFzYrI2mE1yo++Eh8vDrr7bRfL2jMXSYp8\/UWAyXPbXZNZzQiT0Bh1r2mTpyW7\/G1VqNgkDk6pvapDqYHhd5FL2+Hu4Rf+IgMhdOtPXWvZjfiVsJN\/wtLO2Eno+MXq0Ry9OxiXu8SGuXzuyVt\/j6f8dTq6o+E77JqPTsqCCdovC+X1XxMo9+544\/oWDtaL0gynG7SkFCgVoXHEt\/6kcBct7oZWo0vt8+pptFWu7btUAKNO0eG1L587oHhwTM9uwj3nmuwbfEIpbF1v5V73fSuf66jQKqPzvLPNErNKWVfkjMznZcxXie14oLJ61NNpO4KJqdwstuJv\/ZELnnGW4+tuz+YrCW8nbBFQOALySv5T1kCmx+1oc9spcMUoiNhi2pUtEmObQ\/KFr4n3QpGD8\/egTji7ynLnj5oZGNX+XKBzzdosPO1gmYOkPnP2tCSR3I2c43KIoNkGsuWOxwLkusHV5IT8WD+INJEF+3sk6Hx4bRfVaM5C1J7Nw68C2FDzTp9xdMr\/\/377eeDnNtvtBKuOMbprzpZiyRpp\/yQtELcOv5R6TN5\/2bHhABTUxrvBA8PbihogX3QjO1GRA9PjrWmVRA9bNmxR73yag+U515V+Ps7macHdPtoMxrf5Oy0KotbUCV8PyCerOOR7tgFfwjvrVrZJxTe2o45gSuNpWppeMzTmZ5K3keuaFXZ9BdMMAqzHv0gubx9vKkrmuSn6lOyMSHRjSilv3c+KyC6vOsE9TuYhtjseO8F0R34XR24zuzv\/reiQrtVZdgQChPFFWsac\/5czvkpMQgxVQFXuycsPHpY5991mJx3rv9upQnCl29LDBWyBvGzjZ9zcgsNT+4LjTRnzt99QHPGZ\/QgcPGshmiHcoTtnbXyQXwVlj+U4v02sxlChz2ETKf9H5z\/hJG\/YGM5\/DSMKz+0NGDTjdlNit\/\/++eTpcKfK5Sfs1CnMRYlXlIJ\/7UrbGwbC2DinyqUReaBYbZLVfUJjU9f2BqiuR3Ia+HxdCbjAX\/cP2WQ+Tk5t\/npU68OvMw9uC1VmvR3xG6ljSe5SJeqrzi8pQH7PBgeVWQdrz043lEeT4PT\/fWGe0wP5D85jM15QyPaVD\/LYiepy2cR+47cb\/nneabUnpwzg\/hRRMflpL+\/c0+6cvmVOi+F1mDB1sOkH63yhVM+EB5uP\/Bk19XKfqTfCl3zR7QK52OGo27ZNOEnX9WlsSmEK\/aGGQXOZeGLwPSqF8fZYISZFESfo2G95kRJRFEvFsYnRKrzDSCv7MO2u+T9jtKxPrMqejFsMP7lhsAA+gwe+szl+Xf97w9iumjPpjFefvZV6VoulixtCE7PqMeBP8njMs1cxO5cOsp+M4DdYwGKKUNV+L550fSWL8SX8mhPhy0c4Myi4JG7tRj1u2niY9eDu5vU3s1b0YeOSMnLf5+v5t5c+UP7Yi9mfdryky+vH7ucysKqxigEPXsq\/HxtFxZ5SaSJuvagPbJbqseDgpTtS22JIQbUeAQkTtFMxG4dDHF7Q2GbeM+T8dtcrNgUd1JiIYXbZm88NhEuX67xeFHbxCAU\/bUM4\/ayceXyh+vOZ2i4HZ1p6URywSGe\/feMo9nQ\/6JxavIq4YN4h4dh09ngcNfNh2ADOs7v83plVoTWjtd\/ZlawwS74cu0J0W0TNYGj+vKl6JGeeXXP3+9HMudNcbLuQPvFruP7okogaXb5kizx4fqPwdZvl9JYvHhTbow6yUe+BaXygaTemzsmKtZQ2OTtk9JEdFOi\/NjcJfYU1lw58tiwlsK982tlHYdJPjpfrG48yUXKyj75XGcKPC5vbucQvTh8sbQm4vnf+zLvbtRX9eNI+oUh0+AqnOYJXjCkw8Ul3ZBwMTfCA7vfsSWEqhC8ePftS9lclCwejFVSHsC8\/o9ruR+roLoms0qZwcbHDysfmGp2QWXWRjf9c6UQOf7WV7yyHNFGt1LS1zbioQHvUdtxwv1HyzNLxRnoPvdIy0yNiUg+cfnthGfWy8VO1l5gYMnRiWwtdyYESucX2ERSmLovcuHKk73YHLyi+2Mq4cKwwQtu3ykI8qgO3x\/oRWjdUhUF6QGEbuv2TZ5Kcu\/y6KXmV3qQTA38fC7bh5K1490ipRQE6K73++dw4Bl379myYQ6O7nvt5hdG+mbpzA+ePFxM+11wTjyFi3Pz5yV8Tv3vel7jkPP8bQjJQQm1r2f692DJhoX+b1rLYf5QY835KVyUxy7qyTvUi16HlKdf11TinY9Q5pwODpad3Hnoci4TpbpZ5qqZFWhuE+lTvMbFeKfXrWub+nFlkZ3UwNEqOFTMiX9VSPjgPv+vgFMDcN2gsti3\/n\/HUTWRAZYXiO7dMg3TZlRVQn9p27IdTQXoN229UBnAwp2zv1qf6FRgvqHoi+5ooodrVEevE96ZOpww5SDxd1F325sHBLlQvVDhI9ZOgftaYOmG+xyUHP4xsGFHHTpvv93zMoGC1i6lPPZXNlm\/aL\/VjBrEMe207UQpXE1bMzwtYBBOvumdbgeqobMswEhamUJJ4I6LLktZKEhsukR5VKMj5NkT14sU4Zwh3V8CbLReGtjJ7CPHX5CMqS+jMfLB48neVzS+Kh7WMxhnIHnZ\/C1iRJ8DHTpdGgnPUA5pT2Zt6AB+PXq9Io9G1LWV21aQvC6j91T47MpWCFrxeO0IIL60y9h7wSiFlDsdV89XN2P9789MC9JnzESP7yL+NGYVn9WY0d8KdT393aGEN2SrptQY3KNxu7PkrfqyVtwK9rE3qKHxa3l62uwkGpXTR7d36zKxcvR358eTlThfaW05yNOEEyyJfoU\/XCTouCa6lrCwtGPO8BDNhlh6k2S8Cw2p0Xu84zUs+B1\/JZX0nY2Q3bZVN8i8Gwhnnc1Zx8WFA28fLW7iYu+pw7qihDMpWudq3rsB2A3e3mu0lwWGV2lA8V7i24e\/lV\/uYWO3iqH2eCUHttvu7772lEZ37ZE2YQ0ynxYaF8a0yfFr8iJHgqvRdaYypleQwo83EaGrrg7CSPY1TmhWI2twpO8Bh4sNayOkuiYGwG5efO6rUDWSLY\/YORO9ykq8UFp3h4N5Ckhs3FyH9y4CJl8+kNexKZEbkuEQTjy09K1hLUovMw+oEA4p3F0j+Y1wyI+eO32fE5io+e4xV59w1o4GG4MVDlz0XzgvO27ZAGul0thgwjPqG35vrSQ8s6vNo+1XUTtirfnO5ClxYNLEO\/CxkAFHn8y8yvv\/\/vz\/X+P2RkZzEm+x8Exq3XWbxWXIrH7OcjhRABZ\/yqsv6lxsqj3IrTrYB5ENiT6T45UQXpkJYx7C0Z5bNC10BuFva3Tx3IZqWH6Is\/Cy46DMeNRtfn43jsZ2j0\/fVY6bjZeD1vzdz+2tnJ4O6ZeU7KrjwWOd6E3ziphVSPh+VWI1i3CFcWH06O5pnQg7uEvLvILMy4rwF0EkLyeqaIQtjOiGHk\/u8N\/nQXt+bUz7+zzoV9+Ov1OsYaC\/94fYHjKfEZYfaiSIvl\/tDT7mmMZEvJWzbz4ZN7D8JbyU6NqNOe6iVmwm1pv0Lud6kXyameCYe5GNgD5dydPCNVClejIX8FF4f\/aL0Y4jgzg6QfU1KlVDf1Xk+jHC4dqanwpliG552IYefTC1HnpP577iDafg6P0zuzqDjcmklYe+mtUgR\/tTVdV8Gl8kH8wWOUL01YGelFjQgNGXNfT+eRT2bTxw7Wj0IPhDNr82OlINIaa+g\/xnCjutdfuqN3AgYDRUN+RYiy2S1SYD1VycCGOPbvcbgEE2r6tQXxVunxkoZQ1Q6PvFrl+cxMFpcZMM2bA6vOmszRWw7ccBE1MD7z2D6NnxazG\/LI0FR1QcRT+SfKBX4f5JoBupL68mrbGisM7d\/ivfqhZssbiQojvQhetng3WHDlAYX2a\/ydK9DcVbZL4U0AxI8lYo6FtS2DPJv\/1DHYVlV7oCRMg6x3wKFj\/LU4eSgRlhdqo0nqkq9krmc3GX16fCTbIRDwKPXV8iTMP+2eWWTypcNJ27\/SWgoR43xHNmRRC+8B7MNbrsR0P7p2XDxh2taKSyBmNtKKSNHevXLqPgf37M4xov4U6lF\/tC91P4vlVRUCqDgv7rXufdijQEVPnWLZhPQab7IT3kR0FZpPDGGk8aKkOC4mJXKaidmHt8TwOFWWu2iBayKVRqy416biT6Nb1tPNCShpNC+RyROC52Nt5k57FIn84+dWO\/PMkdknc5Wisp6Bz119N2HcCEmNB4sgwLM5c9NGzdRV7\/Q7ewe00vshfOPP9LcAA65eF1boQDlxypHbp4dwAbriyzyyF99uxjjJCZFo0NUtmPFmezscXDr6ZwbSeSck9ek6dK4L\/ozuXDRJfOzr3k8E2nC0++7Jw0u1yKKWK30g1CORh5Nc6cFtiDlJGbQe3t5RAMkFZqVeuDa78UT73ZAH6v2mm1aRaN1zOXVVed60H0j4mKm8v7gDeiHtcIH85u1x+22clEAXfELq2mD5s4c3TNiE5FruM\/0DjOROd44nWuRT947ly3qSTzUztL6afxtj6MLFE7FWs6gMTZp3TmkNd\/bhtwVPMAjfc+ohs0HWmccVvDv\/zG3+df3L9RZE5hy+m7fqcKKNzcZrmpdu6\/76dftNzPCpYawHdPc\/5Z9YPY\/FV\/T81WGrGSx5y2nu9HlLxE70ndQRifP671UvbfHGKz33y\/z2sW9C5fSmwyqILm1lnld0YKYLhk8v1GsVqc3Tt5fti3Fc7Mmu2NEuS6jj1pd8muwavRn3zpG1ox91xx9EExCqODE9I\/yik0X7FLxxEOVOsUlrSU1eI3d2vogTQa\/qkmO8dIrusP\/Vk02dwC9Unp+BlEl\/Ty151tf03jDa\/X8X3Xu9EdM\/jH1J7osjSXWexGYeabJe+XljRh1cUhdssdNnaKrlAeQjs+Pt\/2W1ClBJaz9U8JCrNxmX3nkExoAxwKf7\/Nu12EO1MaB5ZP7YfTOo8Lo8RfpMUYhzsW05gm\/SJDLpsF4Wod7QxSLzPL+zKVb9IItv51YlcvCxEjcfP3TuNA7MmL1K23aDgenm0cvpWFxU99VgneZKNP1fGqIDm\/9WEH\/lxoaESUnu\/9Y5WduKCZoySkRjjj09SXGhOtmN2cLamSxEBNyIVvpaYUFg7InFrA24IodXXWoaYu3JUIUP6iS0HXul7uwO1GqKUO7jNy74Sq1waF06oUfFWeqfuk05jntHqxLMkJcg8f3o7racG8ptXLrz+kMVyaVZtF+uyxv\/LypuxmTD4MOvOT9MfLIYnz52gujt1xFuFzaoRnIcOlo55Cg2bX146LHDxR+5EtN7MOz40Z+4+2cBCUHzGjPoCL184eCfyEL6blzWXv52OjTmn2gHZTPbRNZ3SO6P37+Zv\/q3HTgJ17+NaxMcbQlrln1ITzZfOPZA0X4c+HOeHVn1mY6i0W9IzFxgnT2p6ZhGcyrqc7n5nNxvOn3ID9KzjYePKIoBDhpoutW++Fv+vHepc4wx23BpGsvlN7x3oaDZcLmHYLCBcsTNkfmdiHNAtxQ+EmCt7Bax0y6X5ENByh8pMGMc9LttFemcY3zqNv\/Uf7oS8lzxzZNojicOGQ06uJLi8J2\/O4oB\/jNbPevvAfxDfP83uNiA7KDNXNuebNAvPhqO6SM+XQfaXpWupVAB\/O3gYPKTY0pXNXWas14lkBc4KKK0JnjEzIQ8LDPPnWyWt3VeDKg5aib68KMCNdqSpCl40Ljtentuq2QHvo3qOX54uxeWb61G1knFG70P7v\/o1TK1qdltkV4+D297emvGfhZIGF+xq\/avzOL6LrNQrBFF28d38ijbwJgYUS5O8JuSvdTcODiBj4KKr1jnD2fMPfN8j4FROTuvfdg9CoiUzvtKGh\/Gkz19iL5E99xbLig1z80PickVlO5vVG9nf1HBqW+qd+byE6rWpfm\/GM+A0m\/b\/8jCT555Sk9\/dJNpzYvMm7trQiIi77RpQpA4+TA8ajjv77\/kKLve77FX+Ivo9dcIt0qoe1oaSj6dYixGhkyM+tI3zjJuvxgfDGQh2jkXcze3HG\/py6O9HJoMyng0pEJ4946z3XECJcfnlH694qCj4fPK0fEl5YvfFKlLA+hViTBafmXOXgx8tLLpv7u5EWknZ+gWk5nEsvjsR0cbCrT1dwbykTQnwbT3A\/VqBXdxa9YwcHkRtDjk77xcCUcVkD1XdlmHt1sZhISw2+Sj9qb9JrRdjxna4K4hTsVnZH3lWsxTbIe6a9bcXaU7vjoyQplK+PYS\/d04CEhui7Kg4dkE27+uGUIoUMM7nNFaUDMDq9LTfZlIU\/Tl+Pn9hP8sCI\/2kfOeJTswMZV2ZwYdZtV3TsOfHV6MAyVzMO7MoDBstcu3HFQJxZK1IOr0t1q1NyOHhKj7+bspqcP++2rf17SO77vXloOsmnV8U6SlvmMKDWJTylj7cM6\/4fbWf+T8Ubv38qopI2SwtJSmWJtKeuhJKlhTaKskTSTraQkJRSKrJkKVlDSSgSkn3f930924yEqOR79wf0eTzen8fn+9N5NOc0Z859v17X9bzGzD2U3\/HGPjaKAq50Vnb3wvjdfMetNeUY6n7O8HnGxgY5rotHb\/ZAlN9TmV1WhuuxxxWsHGkwb4XHXAugMVhxYVBYiYP8vGdsbZJrpMLMym+9olGo1omBLyy8fFmqXU10PKBYZ\/OfeBoHqp9sqbrEhPC2KlblawppGTPWG\/6hsL6i8Ggl4YuIrnOGSjw0UifOd\/Cq0JihH6TnNsHB2h9nml5+pRF46qhNDvmeD9MDDo7+aMUUg9qQvosNnaPCayZYXZi\/qS3wUmQpeKWePUu6wAJvZeirOWKtOHxY3aC8uwhzbqXfHNVh4VeHtJWvWjMep147vehiEUaCssbs6\/qgUhFtvH\/uIFquZY2XEt6gEn7wtdvVoJHz\/knyeAtOaf\/6nEB4KK8rQW3\/nXo8vJaxQjChHeMSa+NNNlA4scNzntnselRZpGlkqbTj3Z21clfkCQdS39i5I83oM7Jeb6nShZmrwo1vHqNQp+lYVpPGxie2kMBBBw7kleWbMxJpuEglP+G5QMH8vbJWUTmFoKM3ZpX9pnD1qbUV1y02XDg2ZYOiPbguJPLxpVsZ0k2ca81y2Ijb0RujvbMXlyV5U3z0yyGuGH4mXKwD388M24xMdePDzrtBtk4Uju1iXHzV2APfj3Prtt7ox5DQw8s91RRC7Xh4977pxswRn99ld\/vA5Dg6OWZQ8Lh7djKE8KLlzmLzWF3yPX+GDuz\/UoPn9WU09ZlGrvB3UQEPGtELsjsnl7VA4uTtNd9I7tIf63o4YUT0YFl517OCZhwaUR0+ZEs+d7AlSfQhBe40y\/jCwUbMUqDeeRA9kQnDZHY0jfZdObI5e7oR7ni4srGGgt29R7O3LqNh12qrJ0A41XF229qhQNLvmeaNM79RyHG+92whyf8Hj156aUr0\/jln0fKcUBopIcr81rFsmLtd\/L2+pBRjnzKVJF\/VI7Q8QzR15H9Yn0TZjGvd1xIo8U4XHFxcj6epSjY\/hjgQGpJ7M3tzKXqfY1fO0Xq4dhV6+A\/\/3z2Pw1GqcdZf\/ukyGZ3bSvpGw0l7iIfwT8zM4RRGBY1Ireo1naSPCovUP5ru64HYqdAnNwdYGNonNqPndCdUF\/78uN+tBLN2bTtU9ZYNgSLbhpnDPeh7rbxih2Q5+N\/8Obd3JxvM09rfz\/R1YXBeZKJfeCk0poS6rBaxoX1+\/8YOmS4sdwhQ3S5aimtqUY+7LYmefBvZ+Y3UxW9W\/CfHTWVwT\/vzzowc5zlniyXhJD+a9Gpt\/fOiGzU5PKsPvqHRMGHWcYLw7Oi+TL7AiGasD30s2FFC5te6c9UOog9e+iV2Tg+7EJFefDwzj8LTc856tjvYSEvYktV0vwYGlxRzbq6k4HBzGf0ugPRBaaTkIzvis\/d9XPRIXm6wLFda3c9Bza4FldkZNMo3FRtxRFlIEM\/0dpRnI3z1ad61d2hExHsdsyB58EqFrs8Foi+hLupbT9wj+eTqi+dS38sQrqXEjEMD+vrsvrL\/h\/udrwkGPHIXKIe\/gGKOp04DitqSu7SJLmns3Pb0rDuN5jD7Yx4hJDezenxmtbDRn3xI5TXJ3fxrj5dnfSTvlzbsCLg8iNMz7U5ZE39dOcu8eRV5XXdDd8h4iAGdG1ZGAlVkXAw1pV5kktyWqvtHuHYAPhL2pqGVNGT9Lj03IbqQdLPPdNPTHoSbhVmGk3nRi+yo\/prYjbO2fxghG8uwW6fZ9e5FwmmRUVXT17Ui3GmbMX9\/ETj2S6K6ZVhY0rZn+ZetjUgIWHjkEbMQkTxWsdmGjVDtWduwV7ITBwVcqk6rUJCWFkt7Y1qDqU+e15x7WjC2xSfibw7Mv\/1j7lRpA2qvG0G2oAPi3d\/kcpX\/F9cJHH38aeNuFk5ZRMquutqE9vjSi+Zbi6AUdn2yQ4mFN1qX+p8mN+L0xNzKdfxFeH\/n6UuaxcKHb37P+G06cWRk0HuxbwmO8PZvmYpnY8HJ22rxVzig7J6aJyfQ2POmTKGJj4mAP83dZ44RvQ\/Yzfl1gYbjkFfoOi425DP217T2szHn6PuDW8i8TY2JzzFfxMDZGGs\/y2dMnIgyCQs9QmPT+37Fc89YqJ715t6RJ2y8OhZ4YtsTwk\/+LtfyPvfjlPi8oHtfB\/FIhjtbgPBFqcvc3Bz\/Hths3J6aod6PueaqL5JJ\/lmyzMw\/6mYfQvybRnaWDEBnrrMMJihMM1qXZSXNACXiUKsexUSwgNik+zEa4wFDqjObmMjfenLVNNQgUUFltUJCASLlQ236j7MwwFP8waytGfWus\/zXPCn65zjfcX5eHShBI1nw8i7boyTHlrYmSJRwkHZG4OdN0geLn2Vp2oST\/hE9wqV3lg2Fg715q0heEYhZ3FpD\/Hllxuanq7RpfP0hVaJ6oA6mu6S96ZA2KAkUR1uu+R\/+Xta83Vjoej30VtqPa4a0o9a4d1O54r8\/HyQulm2d0gD\/1F3vCt514PTuodXTSV2pzFjJ2Ly5HoZSotn15u1Q54+6Vraegs73OuWwKgpz3Zn63qZsfNFLEZdl1OC9zC3PZsIPd6S2NmYs5MD9acvEpEsdZIV1Mr3qKVQ7KyuJ2bDxcfWqy8cEa9Gx03Tae+Jb44H0nfAsCkU3HiQ+OtEEu6MKPcHrWbAf3y7Fda0RL2cqhNaMFyLIga1WsJj00bol3BaSDeBdMPf7xsj\/vi6Hd4pTfJJROex+WVgq2DfgZ4jhF5ufHIwoPviRy2mBlGSKBBK6IDQ+beclkhNPLOtQ5+1ohcOnR7XpQt2IXas+KmZO4ePC9XtCng3i+42LC6hNTNwOk4yT1yD8HnPdOOlOD5iNHhzXbf1gIHSWB\/Fv4wMnN8+d8Xfd\/PTFrwXI8X2w9OC5WgfnW9FLWnIJTwse2SpM6vsma\/P+pQdaEbl2KvBrNY0jgry2v0gO7I0cTZBy6YVtk8eW\/WeroGLi2clb0oTsP8Pij2f9e35DRi2fZZyuQ025RvG8hDY43P61fJzUD5N\/vsSsmHJQ8ip8n0IbsNJ3apHrLw4Eft7yaTAsR+rygsJMuwawX5pFXyXj01dpWjNcwYJb1oOMAUYHdrg8ePJGqQSSOgeuHJvNxoyiSVbYtC68c9OMHJwogbqm\/6aTeYQD1u8u1PKncUM5FOlP23DsFUd53fkaaHGoGG1mC8TPb2rbT\/RN55nbl\/z0Lthv2fL0YG4vVNnBC3bEEN9YsEmJkUvq8n7JYhvVHjiczFWY5k7qSV1WKNihBdzFQbVDjl3I0X9Wl25A4V3gomUvw1sxc7PQ25SfXZBf+lBkhRnZPvjwPGa2Yh3PbHWNDyRHvPddsOs0helXZ3ct8OjEnAzV2\/MLeuDO22ue9\/C\/62rbyrS7jvqEn\/bxLq6WI\/W8eGJVOl8jMkYZpxUJj4cOzHv460IH+rU28+fzlGBh9SblM99Y0NtjOi\/zficq988NV4kowQmtT+vnhpFcXSZu2yXXjsolJytdHhWjOf+8O\/MkG243BxTcr3SjSHgF1cxLcofKxqdNK4mufBu2ulrBwbqkmy78xPdeJDjOrtWmMNvb9t3tNAoF5Z9tg0juHnMx7J8fz4HdLTpWkPR5rkVS5Mx8wguSFruCSF+Pu6\/y8l5Co4yhy246ROEis9do1nwauvm6Zi37abi+rg+z6+NAvExySQgZb7v3XrFlOYQj+HLeqpH\/Z5w83WmEawBypwJe7BofhPtJOEQtp2HLPTvuYVoXnkQdN0jO7oX7ngd7f0ZTOC3hy88f1wVlM0\/lDym90BM6\/oYRReHtR41dAk00DMLa5C9k06j9wXtOZN0A9l1R\/ZpHdFN5JSURR\/jntLuW\/6YRJhwGw0MPfqAx5Kk2cZbwr8G8qmCxSwzEc6kOva+nIeAgpniO8Iqgzhu6ZV0\/uESUTB\/lEF9Xl7q9LY0GzZP952vtIIINHFhMMaJjWvI6g2YcXJj1mzG6rR4zh\/leLyF9Onz7YqijL9l\/+6Hj9nEtiIi5uG4r0Tevle3ck+T\/7egtV+bfT+H3lJQPNDlQWDD2RJDiwCZ4pnAyyeunT3IdjyVcQZ0c4HP8e51A1vzTbQE9uCQpUhB7n8aST2Pmjs0UPrUbnLb0b8KNX+2\/Y4coiJZOBqmUssH7htfoZHMtgo948AiR\/vJ5bBiT4kfj9k0P5dn6bThyJ9dmFtGNeaq5pfwkH3DRUYnvcwegnJorb36sBcqXmL5JVl2I7R15E6xPdKlq37vrul1g3AvYGHapF3d3+mXPCKcQOHDKnOargv2h+bWjlk2wNOUfGppJQSbrTfquVxTMVDiJaeMk72\/fpfAihMJh13nNl4P\/Xs\/bNLVqmMLP7\/5L78VTWOD+46OiN4Uvw0c7+fopeDIz0vkKKezablx5e08XSg6JTSQa9yJGNtY3N5TCZdfggVSRLmiuvMJP7erFdL6hBjOy3xhlduWuz2X4YRmk3r6yAaozQ8ZlCDdq\/nKa1h5ajroVDB5mYAPcVlREGf36t\/7nBf7c52FUhvm+fgcffqsHu919fsUYBxlLCtSPhXGwUNXTc5D45bataZmVJPeeCfcfMSOcf1\/2ufSyGjYupC+40hxEoyQ3Yv\/NYAYkJcTqv3OxEC3yOEfIhPSHtIgTLcfE29uh\/frWLAQFJ21PvEKjoG2S8YL0e\/27Tfx7CafqKRhcrA3+9\/nk5kPHh9PP1uOLnUv4n4ftCDAVnTxEjuv6Npf03tdMFJ0NS5C+Wwm3PsNAHa4CCAnazHUkxzEW1\/v8akgdtp1JC9JU+787T+h0i9\/N2IqJXab9dtW6RVjYnhimyJ+POvPWJfJjTPza+9pGeqoWGrW\/G5qWFWJGaUiC0t91gpdzTq\/+WYMZd8zVq1oK\/r8\/V3HrJ6+9ml7laFrB9p\/j04BKX2PDOaQeztvN+1Dgz8DNO84OapNMPDoYfjbEmAZjrViu\/jgLxfSFsy862UgkI27\/nIZn\/fnuhSlM+F8pdmttZyH1y+Phl84kB2UVu248VQFfvcqy85MNiDNzyJj3h4NzPdM7Ls2oByJ\/u37Y0Y5vRnEXt8hTsB6ntk0VVcJo+lNGuXQTbvkUSa\/mpXBfWCZniFWB\/nwf8xGNRohn\/AhaxkXm9\/ThR62iVWAPRa1PdmzCxOM1fGf5\/u3vEZbWxlfqWegeNwm8sKATXC90T+jvL\/nnPN5wfyfcwinGscmqln2xdVi7UcCQyfn3eLppWAhf+DKARefDxo0fMoC3ImxqA42foS1HQlt6MU\/Wev9irQGY+G\/M7xskeW9rzUrlBKKvqUduN6QOomlyp\/YBEaJTn66t11nAgFhPp3y+HxPa1r+WWf59TvqzmF8teT14pH9NfMKqH589kvvOER+yjAxy679D4er8Eu6nPRR4WxcvfE54\/l7tnbeKfhRWP0oVceFQcJGSNV5K\/O2h9thnu6UcrLHzMvtSyIGsb1C1MvEDqaN2vDu\/czAna07pexsKb0S32KsU0XilkLRKpI7o+6mSBXmnKGxwn1T9RrZr31g\/980wE1EnjcYtimqhxSN99bpgISosk2wFZ7Dgfm1EoEGMjQFZXTeZ2zTm+gWHrCI8N\/95svjxTA4U59RLdaTSeB47sC\/6Exvuz5cqrHHmoHXxjSRFks9dlfRWys5hYm2ecPTECRbiD37JPHSRxqGX\/In611mIy7V6Kfv3\/s14+a8TD2mcer\/wzx9SX8HDcuF\/10\/66n7E2CCF+LHlh\/kniG+L8mWGnQugsbp9Qfpnq3YctzWMOrSUhrP3jCqJUxxEatxC5qp6lPg7q38gn79wfY7Z5kAaTM\/E3PuZ7fh5JFDjD\/G1KXFJO2PCn1oWGy\/wXGjFMcr\/9lGif98NpASXPSU5pCpk2cbUVrjlNZzMmShDS1XJLSnVBjzcxNc+g+Rx6blytwN8K9HPTmV6shvRt24Fr\/f\/4jm2Ms\/f6wjnMkEtWLY\/hVOFG6I1DCn9AixW29N7meTH8djZyRJVnZjXa\/7Ks+7fdf6v7Uul+jesbugHVRzB9msYRLvlgrwbZLwa1Ta79X3rwbNcX4ePD\/vxlP5h2ln7v1hfriRdzvcFBa5PgeYfxijs+eoXufYlhaFgyQJZ4ptido+14ohvHph36EkW8U2VfJsmmvDEznuhz+5E0Nj35\/LAAibrn8dfPqvhWVQGC4fuxkz4KnZgJveI+BD97\/vTlx2W\/+VxkY0lXRrTrmWT\/PL6w5rnKmT+qlcqWpPcS\/mbT3fYVImVhQbF1qx8lF19cTn4BROcEwalc+qJPv1ayjvQmI\/Tj7Q2x21mYRMf13379kYosaweNy8swlCkyvrGCCYGKwQUrQQqUXVhsMu+Kx+\/7yl3+0Sz0R61de9vwtWZiyb09aaX43LNmd9bnnAg2pvk8P7ZAOxMNZPkb1XC7NuX8hcZHOwUFd1MbRmEUeyH+C1fKmE8nr2pbRoF\/fu7bx3XZYCj\/2aocWMV\/NTGjXzKKVSaFlco6bOR+fs5l0FVDS58qJO9fZPCD6u5lQ93s2DJ3CBrPVmFuIDJ4w3ER4WlDeLN87txZntpd5ctBZPnVZfuONH46ORaIEDmp2vlVum5i5ug0Lqmk9eOQlb9wys94izsylmoUEhXYUag3g\/eaxR8zlvwzp\/NQvKHwzc\/DVRBclg71zWVQu3B0ex5fGycO\/ow1U64BqmVK+kz+hx4ps+3Nn3Xjy5xU+clUpXQzFSY\/YLRh20NIQ584oNYGpOxr2L63\/UEF+53CyS5M3WqL4Vwn\/G0nf5lbyhI3d+qFu9KQz9a5pcp8ae4uqxaeT4OtPSruExI3z6l58RKvKLxmd\/\/5rJqFkSjPm2VWFSDe44PWW0PW+BTeedtvTCpO6WX9\/QqyjDBt3hfo2wDJlIHt50nHFUWsez3H7EKeCRfvfKxlfja2ugpuUkO\/E9HXrmsykbzuW8d+tzd+FBCH1mVUgohhWIv+ets1J99P6bc0403+oo71p8sw+uKh4vzhtlIuGC88+nSPoQWeYmNTZYTX54rlCFBOPWqy5yHR2ms3S5hPFhMcotBkJemC4UjV9YYvt3BAm+vUr39rypsdk79kV7LgRfXydrLwYMQzJo6HsyshP0PllDVZzY+fFjCDFDshZr0SMLIofL\/M374JN21931aCb4kN+acXFiPJruAWcVDHPA+5LTCuQRT8zJuRIzU4atj2uQIzYF51Yb73CQPpXrrUGMtg4jSMjYvnVGFmrM5b5JMKQzIdT3YWc2EsY\/Vh9eVVdgqPLCvs6IHwwrXqCU2\/ejhjfm6oZrwdMKWB2d\/t8JE5+1Oa8lunBxt8RCwoOB25168x80O3Jrf++etNMkJgo08h10peNQJ6QZ7VqDoXZlB8sJGVHQJ7X1NfGLmT8+DzPpKqOdJtZtsasLqdzd0PQhvaFjvsxhuroL4RQvpd3ubIRMZWcoSoMAtl+fJG12FwBsW95fPa8b2h+90r84hOXBW2ceY\/hpEtK8NtjVvhcSSj0kjy0jOE73XuTWOxi1fJZfHCTQ2fgmKCzrOhI6j7+7fKjT2f96w5tQlGh\/EX5SFPOYgk27ieU3Gga9V3NCHcH9944q532aR\/HTqQfPr5i5ITqQbbWzrhflwU0tmHMkPmzVF0NuCwyPrCpbHdkH22adACSMKHKEDJn9kusC39W2q2cFe8FuuuTv59z6pdu11Aloc6J0t\/+Hn0I+xl3VSc4gOfdw\/dBIkd54IFGm2JpzB31q+2qqMg8O1T1ImiT\/P597uvceScEDesJ1GRzNmrVt\/J4psP54423bZORqaKrZLIlqb8btvgWFUFQ0dXdHtz97SeC0ldvXqjF74zdWMNrGm4affWrDpNoV4L1P56dWN6Hm8h7+9jMZ6xccLXGNo3J029fPTuW40vqkt78qjMBr69ci3HWz0p3ybN\/qgBorKYuGLXWh8SZGwN4gl+nE1kF91VRMSFNw94i9QeG64N7phlInDh+2WLu+owsMb7ZbLOwi\/nngw15T4YcrSlX6Rt2i8txL+3vKJcMuaEMcfD6qgqO7Vu1\/l3\/dzvT9cWNAXx8TTTffNGh0qsSTDdrbz73+veyDXYiQt1cPE1omEcvvmGiQ7REWwawqwfnnLtyKSQ\/3rj7zc+oxGpVfrr57hNiwr6K7RINsDtHfYSfmT45u8Vyx6uw3N59U2mExrQJFf9exEkQ4UFy+MPbCZwsFTCfo6JB\/bqcRQsjdo9Ex7YXifrwWzQhPGblDNSBNWrXq7qwu2MtOltY8RPz1lWXiY5NzpU2KdPO9oLH\/6\/LSeTi8KD\/QN3E4nfjq9aNWh9zS4hXoLbPYzUPva9cejQhpvKzaVipP3lw+vOPzxzCBMpeekvb7IwFotzizpNibaWy\/aehj+\/Tu9PifHeAAVRtJC7aoMiHCX2mivpbHuzEIn4RcMmF391XeYh4VChrfFK5O\/18ne3sj4yMSak0yxtG4W6LLWMVEyr5nDyb3iD0uwJNu7fOafOmx5ayCxeejf9y+ECjV8E5lkwyFv9U43tT7QbAtRheUVKFxqE8JK5MDbi++CF88gDK\/O7vySUInPhr+1n\/hQSFFnSO52YkElI8AyQagav7NEb5SdpzDhHHnpAsXE0bUzti5rrcKlj6X7xIRplFo6l\/hpcsAXljHt6GQdJj7p6KmBQvKdmqAqFSasNhxlzPGvwnmnhnWDPjQ25TBq9r6kIW6UNLZ\/GRuFZ5oqzxC\/EbmrVSf9mvT7vnl7bT4wEeow2XOWcObD0XN7tn2kcaWuxDDGYxDLZ8W5zWyiEWuTzzqdTePR5djz0dIDWOztun6ijgbfUZvgevL5\/fO2redr6cPw21EeR8KfiwXLV5wn\/HnpThzvrrpW1NxNTm57yYSclOH045XEf\/WSVPtJvbTm\/3COfcDCxtITRx96s+EbKWOu9ZjGgwXTFPlOcCDwwX6LAOFU4wSvqOmf\/\/t14Kk9B9Mq65l4uWBj9O9lNahlafOnvirAt17TChbpz5tNJw7J\/qrF+WTTwZal\/z4vLX1sxzIHXwrZXEti05gUbF\/OabLIpLBdYpOaLD8HOpdKGTLpHFjQyUtdiB59e\/xYUojoZvr7+KGrC2lUGEwd\/HHm\/27db5Pf2\/buTGTCS9K7ZAupp0c3PlH7+QuQHrGLP+sNEw+dd8wz+VqJ1AsWPoKCBTipMbVMNpqJS2zZoie7K3HzzBqxrVQ+lAo8jNemskmeyWBqzerFd+PbevM3luOAfb45cx+pF2ub0SShbrCav91b\/LUUKZtarh5\/zYZlVojGuqYetB98LjYiWI6zj5W4RGexIJF9skBDsR6LbjQ0Slj++zyG\/sJ+txCiM6mPP5\/tJ3lvlYOBzAvfQUzOaki8ebYcLGOf3twbDWiocnj44CcHK2I8vtyWrcbeOyndl583Q2SA+8queRTm1p39VkJynA7iVmV49sGk7IXR8JEKlPnpfppazcGrwyyDKGYfNEVLLghGVUB0WY76tRYWlos0Gq1d2wnlqASGoEEJWMcNTRw8SJ4oZZuOhRC9WGaZvb6IjSj1ZWKdcRxsDhXmvjk6AOc1V27ujq4Ez9bxT7O8OJjhzX5qZjWAR7Nm7dxwuRJP9rWH3TGkYPDDZF4Z0ZXvp\/y2Z+dX\/WeeMa5yV2+sq8ej5nD1Jd\/a0dFy1bxnI4XJ6Gh53UYOFJ57b4qPHYRm0n5\/k7\/r\/v3pluBOI7yTa2zgt2oQDTvTd+SlV+J1yuB9dUk25le2qOWe70Kyf\/Urm72lUAg6+5sRz0GGSabA08kBTHknHvaKq0RaS6TG5woOwgtENsbdGUSO6NLGp92VGDgtdDSmg+QR1\/dO8wM5UF\/Fd86L6Df\/\/VXPOqcN4v3PxZqfchjwbfx69+Q2ou8XBOYpEF9QdGs6zUVyb6fErj3tcgzcm6t0fYroxX3BvPuif5\/H1PWFWkPyQenEHp6zxBcuBXXwrCf7VQlete\/W0V6oJ79Lbi2l8Vtwmm9fBg3zewta7yweRLBG3pwzhLM\/b7QoclGkofxNpvkL4Zw500yn3fvCgXLSmZ0\/dQj3DHfslyX+garWU31rmVCwv8a\/4QoLJ3efWrPvCuFyxgx9ZSUOCvcXCae2cPDHzkruVvq\/z+9J5Z1O3k36oNPq8w7n8HpoWR+vfj7CwSFVv2eZAmV4s1GIe1lBPW7fKoqNGf3vHKs3SPX5e5fD1VDWrvBhA+5JFZqK\/uLg0uFpG19Nr8KJbrVLZ82aoPbEWr94JgXluuT6NMEyWOndEVhdWI+VSwfb35DvtTlwYsW9IxS2+Nz8oU50auCjdPN9KeL3cULasTSFq1PXnccUCGfNu7pxXIyCVvPpJpXSGqw0kD4XcLAVqQrTTomR8Tyf2j0Rmt4AdffycpW0DrDDth+UU6ZQamB8dXlsDYaObmmzl23FkIxk8aKlFMKellesWM3GV4Z6pCQPBwkmMsfqw2kYvmtTcBBgwsBdoH5Sn4XQ1XX01Ys0blrNRk49C5LJ\/E8b8thQiPGXUgukIWEok16iwEacyJhFBOlvvvMDac0vaChJSrufesiBzy4FW5lVFNanjkZr5tJIShzsOVTABLffHGsLDguTi+dpnLlJ4+xQNjuQzM9R5xvcH69TsJwW3TFMfK7ywOz1s1bWQJO1uuFeWAteXd5moSryf6fPV4qX5yYFMzFfzjdHRaIC15StZql8yUfBwrXyb98yscExTaqtuhKJt68qv15QAIM\/W3WMk0je6OKe5tpWCaG3qYmHhQogPc\/sVR7h1\/s+MRIahIeVzmqljCU2Q9781wWnFxTmJ55ix4xR4D+WmK\/9ksLp3RofXNxptJsOZ\/gQHRMS\/zxo2cTG5I1fEjaRFL6i+VLoBIXeP69s\/IJJHlZhueTkUIiJmzMjfS4NbQfboXgrCucqdMejz3Lwy6Z6L3M6hcGIs4cPZREOU32HAWGiT1KKceJ5HITFVhqVpZH+k7641UmF6GHi17QYvX40T747feBXBRp2iHvFN7KxUoepPi26F51SWmZ7osuRwNB0iyon3PxdVPm2Phsh8qHeQtU1CBZ3cqol\/rLawWK+SUsPWDoX7Pzml0NAO8SO+YDCr0dPvr50IPwW9CktZFE1NnuWtdm8bEAGd3+K3ssOHNSfue3cjn\/P44OKMqM1W0n9ZPwueUn6zUCd79QE6few1K8VvCEUblSbuR39TsGkeOWOJsL1pxW33340n0KGnU+prjf5fuW0PpYfjcd191\/6zKThamZSXLiHxqfS8lW3Sd\/NyTnUr\/KOQsHyrZPrptOYucRqNoPkDFu1gPRkTxpb\/Bft6g6l4TYkF6f6io3gM2vStYIIZ18KcPodRSP4le8z79Ms3FsxsZqHQWHVxFHPabI00vqOL928loL8nEO+r8j8Cks9Nwn9+9wW7svxY\/Vs+MlFKkbcJb7jnhvV0Uth+hnt46+LKYTc7PK7Hs1BUId38feBAcR\/sl+X86ISJ1wzvh1IZ6FAaVDMeFUH+lYPL7\/OKkb6\/djC89s5OMAXNvBySz+4XJ+l+vRWoK9NNvKtPAur82KKO0wbsbvS3fvAaCHO8Cg9rI9nolDI\/VDCs0o83pEzyJpeAL8ytysqO+vgctmQZ+PDNiw+7MBpl6aQtkL99aU99Vjr59pidbUdBz4XiyoqUFj8nY\/bOasRbRdDbgdpdyJm+5MRJ7X\/u34Mn1LzfXOLiZrDrd5BXKVI\/SFp+8IoH08N7e+YejEhGVy6KKm8FKr9v\/YT9sG67Itzlrsy4WZ6Q9O1sgQh6l0HI07kw7v3oKefahUer10RHhTdhKOma2ye81MQTajcdmxfKTZtGLnTYFSPhebb7tUNc7Cs03J1LdHFH+c7rQ+nMCDr7HyPx7AKOzVcVsu6cvDgsp+lovYA+NwH1bxMKrHL64FW60oOlMo2\/trY3oct01x8RoMrQJXM\/2bi244\/qmdUZhZ0I\/66yPVvthRehDnkH7jcCqO12kv1+7rw+v3FYh8TCnsHSx09I\/sQeE7AtnZwAIEHGh\/xTFJoP633henYiTqbY9dfZvVAyUG5bc5DCpJ9N+rvebHBX2LfFaTHQan2YvVtcSQ3zFvZd4Xop+5Ev0UQ0c81knf1thbQKPyy03FuDY2WaRYOgck0dsvOC3sQ0ouA3If6EyU0TpVy7t\/5u86Pn2g81gxC6\/OW1VuqOHDfULgoUZ+CyNaOyMdFNDbHGrte76Hglfrua6s0jRqqfyJsA4WulhqTQykszFW0NZYjerCDOzVwIcmjHoltertJPlKJ795jV0Z0bP+yvaVTpE83CR7\/NMmBSeyPSS8nCrEclrcT0SV5G+vBYUE29gior3kk0oUbWyTeafOXgvlMzU0hgg3HF1\/\/rHrfg9d++Q8+j5ThRETmCRmib9u+a87kRPfhFOtTf+\/lCqQprF2id5nsX2NxyFn+AURpWrtZ7SO85\/\/jPvcK0t8zzo3V+1N4OZ59rZDkmmBtn+qPSjTUlNfGfzSlUbZZd2ZO3L\/z4z1\/17ErvSx8Zfnqc+t2ol1neaCQ\/b\/Pk\/fq5aVcInnTf\/pc5Wb1Pgw6GOnvIz7TfTJsQ3QJGxELK427rXpxlS87vfRGOZiOvgWHjwxgUf\/Ec6NtDDxqnfdklIz31bNNl6obWWC0PrnrXMDG3KBpobbEf+\/+GmYHVDGhZp2yNmiUBcvscr2Trv99XcrQvsHjhjqluPv7j9M0k3rMbbzkxiJ9kR4j5fGD7G\/rau3F7s9J3uN9n3VwOgeJ8vfbiohv75uZd5KXbBfSHu2qJ\/PhOTf1rnlSDWSmGtfJbmqFuInwisOkr1QrXfodrKvx877X\/ekDzdDk7olUXUDh2vs1KUVE11Xirq+\/QDhzs6\/4ivnqDLy7wXpeeovkjjz1rS1k\/xuFZ6z3GGXD5\/uM84Ykh\/TH+if8XUc0TMVrautFBuIXUtEjfhyMr5Yw93k5gFp\/y13+tyvBvXN6\/HExDuKlVK4Zfu1D0p3TS355VmB0\/+4R+5McPHow59nb9H74+c9a5CBdCS7n2U3Xatm4yrYIrH7SC9FXn+euCSz\/P9O3HJ6WxKAnTDy7s7rdQ7ocGV7K46oR+dB6n3\/C\/ykTsilPr39WL8cy5uNvM6Pzwffx1XLFZ0zcDcqfXuNXjjWssR\/cSf99ffK39N4q+UYmzKSEP0zbUINmG67532MLcL2kKjmNVQ67W0tldb40oFw8LMv297\/rRHzHid3jBh04++nw9BbRHjhuifzU6fL3voOL6Snr63G2f9x6o3E7diYcPxuwnsLuHS70tMFOBKSZVSiJ9gLuE\/YRz4hf7ng0T+59I6748hq+39eJUx5rkiSIj+xSTd9+MpOGuvU5YSeSR2ob6zRdlzDQg+LsPOKnmhopS+OJn1afM31fSebpwJ1KvsBwwgdCNVFZpQNYGMN7NdW\/Em\/nLmXuf8iGjnHhi0L9HmxdzH9M910ZRG1Eeoxd2JAPmLFghkAPbkj9edPrUIZnmjKu3m\/ZsLkZUV881IMf69PEdFeUY\/\/jI5v+rh9iq6f86u\/6IUcDH98vse3ByhbJhHtVNL7eTeU+RbhPWamh+fX4v59Ho7vu6\/ziYjZ6K7Zojln0Ik\/2xmumfTnEnESTqhlsLB\/\/NtY50ouGjxFWNztJXfz2yKkv5ODWHktvzQuDOOX9xMa+oRLGa9fczh0jvnPDaoORJAPJb3j+nF5RhQEe4zelRM8Pcwk1LnxFY4fdMeP4O11QkCjlYlnQOGN2V+qOEYWjtaf3M+0b4fYi3tqa8LXFFl3FiAAaxxle\/jPd2xETe\/e8Nem3io\/bSzMEaTTnup5ZOL8ZJ2LubjPXpjDWpH+++zoT14Vi+Ne\/rkKP5JI9nx5zEJf4mS7yG4D1mI+fhWslDu6ZVRG3jcKJTCOFUBkmXDptZ856UAWWpcrZUWMKQ93hwqdKmOBICmd1lv333P3P68zr3nNscmqxq9jv4cTKNjgMt2\/hrKTQ3yCXx01+7zUlyxZBkmsXOcaFrvQexMhvmdnlWYSXZl36pHW8A\/MDJgPKJothqyH0ypZweHObw4FwwuGjzFkbfQmHX+87avSZ8LxK5LUlzYTne+jvq9vIv89oRz+Q4yM8+eHBa10PMk5bzrtURBL92jI8LTyxFdvPm7K+cnVjbXHapidmhPd8Z6SFn6Zhctl33aM9FJirYwZdtzbC7nxf1STpGyWezNkzSE7Yrroy8rwJDZEjB+UHD1Iwn9fsVPWRwtKUfgMzwpvWLpnSF2PYGG\/20Jx5kdTF1welqqROTapF17iNs5HskrCjO56D7asopQGir6GMk2tTMtkQk7qR+FC2F6fDa3lVdMpRujhYQNaNDXMNBaNt4j0Iurig4p5nGfKsGNd\/r2Gjbf2+K7vvduFOQlVj26lSnDkYzNNO8sojnvxLF+N74RoZyLvrdTkWn80eWptHY1vWa\/Nuwt++gVMz6s63QSPiov\/IgWpM0xCuDc9uxkmpwUvb5v93bmx9\/TDTP4eJ6qOWVfH1VfgzUzHVQq8AmdPXMsNILsvd3n1\/T1cleg\/M9FARLkAGeJSCd7IR8EBztKu\/C9e7yxLfvijF+aJmr2ulbMiYsN84X+5F1GrBc9Yu\/13n10su\/jDrHROdXWJX4wcq0bAwNbRZpAAuc2JMjEh+flxuXNVqTLh\/7IzngQekzzK0JMtUB7Dtac5aO1kGZCTUlhxa\/T\/c99q2+0TPfSaqvlmkVH5mIXjb\/NAyBxrfSgKYhSlsvMqPFEu04yC2PfDn3USSYzxPzHZOYiHMlnKUIHWxf0+4QiqZh5o2ycxXrn14ZnHKdQbRycMZR11PkLqeSHY\/GnyyH1Yp4\/kL7AZxUrXjpgzpexGDn2GXcxmYq+e\/TlqChaN5j6rnmdNYJT8ymDNvAGlyJcP+MxjYViT4ZtsKGrwv58aoFtLIMRiq+UP6Sx5B99PPDuLx3nm6f3mEE8HrtofoyqXh24cuCHBwRkTkxQbCfcJG1suH3tEImOSLeOTKwIiRTJj9kTJ4SnhU72PXw2HWE5s4oncI0WnrflUFPkYeq0OgGedcHqUbz6GwUW\/2yLv7nXhZ4yi5oLwHPb4F260fUVidLJZ8\/ycH3X3pr88oMvDZYMsrO+kq\/I58ZKfSTviwsShOKWcQW4OrnemJSpSnRd\/dk89B5YPaqXkmg+ATPsSlW1OJpjOfFnz5w0auufq7pVp9cE7W9\/eWqvj\/fp3VQU62jF4FCwoXdzGZWWwovI\/84EN0ut069kq+NBtVhvNmX+P9u05im82fcBrO5bIX2gg\/OJd6c8vlsaAhdNvskSONvNUqy+XfcqCmfibhGEiu8Dk27QLRwZ6iJtm\/1\/fNat+11MSeQqZJyM\/BbBqq075dzzr2936DW6IzyfsOoVlavcSP\/7wqvy9Pckmr3vSe2TtIzs0Y2Cg0k8KHbWNu2UvZ2LIi5sEanS5oLLLoS1Ig+nBVbMuSmWy8kLROM6M7ccC7sS6PVYIhG4XRzVpsbGzT6I2X6obT19fnl1WUYuD7NEfNZjZuP7Lu10\/sxWR16fSY+H\/3o4\/6b2Vu4kPcjiUpaY7FkP05P2Wu\/H\/nIq+HPB2qWzngjdzxYcn6fjgeSwx60VaB\/RPjZVryHLQtUg1\/OrMfX65JlHhnVsCyd3NkyhAH17Z\/vm44i4GUdRdaX4hUIdVv1aXXpf0QmJwtYV4xCN2NpmeuLKGx5U2xxOSCavCVhdoH3mqG6s3Kgx6CxEfKK2duH6xG51eL9o\/GLfB+kfnWX4hC6Ir69Huba6H+TeZ09OtWLK1lbHVdTuE3HaV+uqAP8lWOturTB5HJ+alwlotG57BfBLdZP772hj1\/6TyInHTjau55RAeWRyg91+xE9ER7+vmAHjicqtKFN4U\/duOLfLMYsNLIPLFCjIV1AvKiiWdpnExbnft3HYyfSscbHnym0dCe9Z3vzQBihEI2ZL+hEZTxNvfvev4vBeSkfv1iYPGi++tzH9EIdPTbMzuChusRnsS7kywkba+aVptFY3Wt9pdbqTQiSt7Y3v02iHqDU8ujTnbilu1sGlE9uH86I8X\/PoU84fN8XLZMLGtRenQ4sBhTKm7x7Yr\/nkd27hu0OzFh\/GOV8o0LJWBEiRnIaedj7flAWfrveYAnl9VvMkowdc7JI\/tkPrJDMsLNU8rx4YppSE5kA26xPhS8\/UX00uHEBalzlQgcEKVGshuxx2RD86npFPjM4\/2fOlRhPLXg3snOJpwPWTV39WzSH191NokdZKN+S3aq8eZuHOe12yvRWoqf3LLWVs8qUUE7\/YwcbsRYhYRjygwKW5546Er01cNYMCjp2J92KF08xH\/mf7HecrX253CxQzRKN1hO9tnT+DwReuedIwerU5xLTYnPXolf5VVO8tCxhZ4hhn6DaI+6f9ezjMxfRzPrazSNC4\/S1e6qduPw2S3uSYsofDZykot5QHL77VLecDJ\/J2JrDhzoo7Dz27jJzrU0RmpMIm4S\/lhmH75egejyZv33pW2Eb\/OzFGb51zAg0T+\/rKqagyzfRZ6jBhRsZv6o\/FhEdL3EfOkGXcJ1zMv2nhmE+49+9\/JYQ+PdJ41u9FAoXVBa8J7k2LV5QZ9+bqBwrve6+YY6kutVIJf+iAOL0cBfXkk06kVEhyP2MBEj6PTxuTsL1LzM+A\/XaBhZjkxmED+9Wj7vurQJG2NcPDbHiZ++nrbFIe8uB53m27twbQCjATdSfl6tBNxq5oZrcvA0rcqsz64fK8cVH52aUwnx0Bn1kr9ZuHZQbF5gZicy1kVFyRSUwGBR2KuqaqKjItwnRUiuXNURte6tey8cgyeCb2XQcLv3ZccHwk8X9+hYrCW5vG+Lq9jZOhqG2fr9gWT8m+sZrxY+70PqkF68QyPJBWsjvBVIH\/CceXlAn9UPL+3ywJAgCoG7yxXvfqPgKcQzjUog\/hvukizpS+HXqPMWOyYFqZE3Yj8zKbya7v9TiZvC8q6mSfGbFNb7X+MOTfrvf1cd9X1izU\/y46+oJlVB33LIhIpPO\/82H2oWf2LUiV90LeJ6K6BcjjDdx13Vkfk4JsbhfCR9bmS6TLaJvK6In+Ix\/c3AAe6juUrk93YukTquQH5vQE7wqMidPhRVnhBmkO2i7V7WEX\/Xj3wkfuqJ+wAusJdMXSb5yCDqx5AkqR+ndeJsPU4PLp52u2Eqy0LioWNxLrsbsaRZqdKZXQj3tb6jNeFM2BUXZoh8rsDEh4vDzDqSi483VAspssAIvbD0nVcjbCyk1W78KYTbuY0fljt2QV6L8a7apxe6d7aLSUVQuPKjTipuXhv27hG63LquG0cEZn4ptaCQI5fst\/hIG3I3JAgo7+3GI5dD+2zOE77WyBpYtbQTanOsHndf7cGBqS\/lbncodGdntjTu7sTO2+5Rzo96oLlz8JHjPQo1MrlSnbmDOD5m3XjrBBMbj13nCdCmoRHz5rFoJQMbdXl5Zq9j4YO7X5MeyV19XFscxZL7YC9Xt+\/a9wGkzm87fOYPBcWR0b60fjai+zb+KejvxYaiggjJ+nK0+PdKT73nQOLqtbAwsUHESDUvv5dWiR0m9eabQzjYx92ZqZc1gLjf2ZWqvpU4OaKiu5nowMLqwo8ZZF6orutaBwMG\/7POdIiume5BXtdduSAtdJbC12LeGrqY5Au9FZ8vn6KQvTIocW0uBUaTVLG8CNGVPS3ShocpKOyoixpIp7DV5D43h+iHQrgY83gxCw3mM+5xpXXgknLU3p8SJbCGWP7GXBYGfdborLftwNbkuXXS\/CX\/PJ4ki802yhurEVEheN77VTPaxQ3jbOf997yQ5jB4f4knE2pyAvaXvUoRV3vJ78Hlf\/vLvsDh98fsmJA\/PeOow5dizBQY3T21Of8\/j+fXLqe5oXwVmJ88tNO5qgH9uLqo8\/e\/zyt+3F9eek+YhaKYhDnRQ\/VwX573pCKgEB+OjX+6EsTEwvmnXyRPlMNLw9PUOvO\/H8\/1L+s\/UlplMLPbOa9koB5T1qFHvQlXW5QnBT93oTGQ319wN5hYc0uky\/F1HMyw9Ja4saYXmgFaPfyf+kEdH7gq20T0vmOtkaBnD7gecx7Jbe2H0wxtSdNSCuNtIrXJ23qxPuvXfJ7iftTsCnS\/00zhvRPXjfVRLBx7Kb5DLIyNZ0+5lV4+JXV6ZRq3cBUTlhLT8hRHWfCdNrPhAMkJ0QdylixIZGDfaMdRW0EWuqnJ17QpjRDDRSEJS4neqxYbFx+mof3Gqvt6zd\/nNbl0bthGIWOvGd0VQ\/S0d01urS6N6uz52t51pF9nzxJyEqNxYHpfi5wmBZaijG5SDPEZoQrFmdtovHfc+VLhSvN\/fz5jhOnmi2KlOLZcRrRKox4G5SuKlYc5ePy7X077WCmS5GZovTevh0D03vlzvv973i\/29Hx9J0CDX275fsN9NGzk9tLLWeR3yXU\/TiC6MnEzNPKoLeGuhad2eLhysP9su4cryVs82r+1JI\/R+KgUIRNUxIH18nX+xZvYMBZQlQybz4HlU9t3R17S+PBl8YvlpG8uWyMRRL+apl87eorkiIZQ700BaWys07fyWu7AQeKZuTKpJD\/u+9Gu+WcjGwvvZ03mZXVhk1OI0TePUjTZKOxLJ\/Ontpy39uKrHlx5q+anwChDfhPfteEVFMK9RMPuPaOQlr80QcHxv\/vUhnyeg9XRTHzi+vHGR7MSC5QjU94P5UMw+NeHmtF+fGKsWvOAHsQ2sxV374mTvBmjrepZN4j4erXLWuZM2DadOWFwgMZvyVvjKvE0it7l5wuoE36h2p\/0eDfjhXGJkd7zfqydMGl+ETuIFN2UxlChv8+z1\/pcFkrDgedjchOpi5o7+T71i1h4K9ye9yeHxvbMmnUWJKe+jHYOCysbhFB98ab2SgrXvg9pTS0m8\/N6zhZRwj1Z73\/MuvCRA7kvWRtS9hKft94er1NA43HEB7nZohRU4xqqpUkuFanM2jpyj3DWig69dfPZOBVr9eX8CBuz3Z4a15Pj6PdjyDzdR0HttcaV4GQKR7daazpvpzHeONAre46DY3bet9k8JHe519c+IH77ISxwU2AHGztt317kCeQgat3XMU\/CbddyUuznp3RDxGzGYTefPpTuK1ajCZd11q0clZxO6mhFw8eTKRzU6y1LY6aQ3z2ndOuCTibmdJnFSXGzcUKVkfnpFtGFoi32P5JYWFOuudgthg0v9eG2HD8aOtLRPk61NIbfHLkRQzh\/9dRyKaVtfShTXex06SsZd8cS68Okz1Otnuy4VNKKHefmfblYQuNgHW+5BskLw9vl1x463QUVlcMGV+NY8Mz\/qer2ko0rwhOrZ5H9J3R+z5E8ycSd4eP9Us9YsMg+Xjz3Oo274RsWShxhwWPWb5dEQzYu97i6lN\/\/9\/mTqTyvztFPhHPdJ2V1ye90zrAYE1zBgKDUm+H3uTSOmMoYLiO+eUUmnKOSNAh2FbM46ywLysIq2ZrvWpBhcjB2Y2ER3lw+Z61TVgsd+x45Zfk2HEhVrdORovC06WGp12IOmgsdzNVS+jD1eu6Nj44VWCy2SDAli4OgpDoDYY1ByMrzeeYXkryx4AuWLGfDI\/7rsdOnuvBQozS3c0cplj7nfnuijYnufCf78T8sHNBs3eRIxl+Cz+Cj4K6\/\/f118Hgv4W4lT\/e7hEfXO57\/Hi\/ORn++76zLBl0oONQ2ar29FJe2rUqgbJhQMOib5mxfDOXCwOACOeJ3YXaJxmksnFXdcLEmntRbSJHQXn\/y+3OCvm3pZUKn\/+du6xlsGJa6T5N0o\/GlTWv228eDSLqtXLZoA5mHIePRt0SfHg8+9Xl+sRuWzgydm0f6cDLnh\/zBVAptHstfbF9FuPfE1RmPnTkYuDdi+vVaPfgNrl0aeNwO+e+Z318VdOPqji9ZXHaEI3YlNZ7urkVlSbCX0+42WG7d9G6CjKfznEXP9hH+Xlwjdfzw3+fBHt387GYOAz9t+sazn9D4pvaB2veKfE+PZ8hYCQu6JwQZm61p5PEOblhI3pfYc6BYAxzceyFa+J3U2Yw70Z9\/xtGI9QzZ7Z7FhOrTKB5BUp8sgcjnKmTelfg71118PQibpbV63ws4uIT6Zk3Sz7OMe63eFtK4cSs3Y\/Z2FoSPW4x1a5B+de18d5j074fRPadHSpiIE0g6tOQbCwu2WnpX3aTR6ndUvuF4L9wXJmU6df99bopwX38rhZnHK\/ex+XvgZCHUcbamD2ey1hiFfKGQKrLGeWldF8rs47jfNvbCznNPuk4cBZdzhudjvDsxY9GBrG1lPTj4ShZGRD+216jfunm0F2vmh\/f5dfbDUSH2TRrZf8OsLu13hMMDXsRO7vpIozxZM7f3E5mfL2HW\/iE0Bn89nThB9M2EecVucg0Lpou6b24m\/TB4+M6UGNGL78\/2xl5\/wYDDso2Fc9JptGcfEBQnecfEIUBM+zADibud5\/0QY2JmJfWnw5yF7Jf1GcKXaVz+dXOPTBkbySqxtnr3ONDmUhz7+ncdkNVfT5iW\/F0PZdvdDWQermqNfO8mdbrojIpdNBn\/JU44UkL0YUvrvYPdv1pRSq1sMCTH1957MICzhUZxlhVPzMVmiBnNaP82i42D55fubuDqQhD3yI+A8RIE+J6Sq9jBBst4aMnH9i40rghQSwouxd4trfqn3rNhJdnmJD6tF4c\/r78\/V74cA737Fgk2suCQxBVVsLgTSotLbuQcKEF84\/qWZ3cIP684sOlMEYWr53ZM57nchA4+R\/UBot8SCRKOnwkXHRluX7YxqwMWyh6But8pjM1YZr+N5Ff\/\/aO20+lavJtfeOUmyamnzz0+tsWN+K3es2qxkkZ0XCx5eP7v849v2Yx+2EjmZ+RCvbp5Mw4yeL\/6fWShX+KyZYV4B9YNTZ87m\/Hv+4z+tV3FWu+3zm82Pmt33jVW6YPbj7MiUcsqUCIXklf3hoOfN6Lz1\/APQsOWK2nHm0rc65sMOkDyt1PZ6e+X5zIx5mTXpXirCr+SNghODnBQeW4JV\/HAIDoC5BYF8lfhSZKETf3mAegGpvgdk2Rg1a9mPR7S59fKl7J5s\/rwxTL1TvbvASz64b3n0RQFRyGlCu5MJj4cURRf38fCwRMaj8wIXwqYOul9O9GEZ69Fngg+7ISh7om7Z\/ZT0IoT8BV51YkEm5FRwa4eDLAb4zUfU+BKdOh7nN4F5mJdh1W5veCzMpvcTPhumfJmv\/6ZLLzSCJJ5LFiPgg3RpulnCvFp\/rEWz40saPIsWB6U2Yhwx\/KfsbOLYP\/64LBFcA1cewUE54q34sGUWdnbJRQuNQx\/3l1Yj0\/bj9w40teOHE11b5uNFAYUJcsc+yls6OQb6Y9lw2XPMfft3rVIl7r3fnyAjYDhqmR7di9OvnA9e7i5HCIvbx3+QnPwtqIzK4CXAS7nxP1LhKtwr1T5u0MyB5ctDz4IEBmE5pn2EpGUSlRxr7mmIsOB8HnnJM9ffYjiC4\/6klwB5rbwP\/1\/OEiWe+H4cg8Dd0U3V9nLV8F1lYbhbBY5jpP9ny787MW8xDHeJ73l+MQULNBmM9Hx+ICVmkUt8FbhJveP\/37\/76EojXvOmSXgzlXZZC5cD3FJwxUdQyRnlt9sy3GksHN2VnSCHAsv1J25ikarwDD5cr3CicKXjlDbqk0slPnoVApPVGHMwOz1tlIal26bfv9N9Fnc+EnstFTSr1HMBpGr9USfC9fVB7bjqo9iXIIiyYvWhQmV4nWI2VygW2\/TBg9Lg+j+1RR+yWalWphVIzYgQV+2oRnDS34V1c0nfjE17LRqVxOGLPdn27h3wkhv\/e\/bGmQev1\/s5ymuxdHUeK6zMm345NkkpER8JDrW8NE++Xpkm+Rr\/zjdDu7YnvT764m\/3AjI7ymjYaabaKBLuCB95O1sV75BxFp9c9\/697nj\/bUeAuR1IuDyOsURBh4EmkrxnafwcWn5HCMWE4VpQ1HtzVVYEBF2PUyGQh2dWUN\/Z0BlwmrbFdsqrDZw8eEbo7Cx+ZC+UTsbBr0uWDijDk8WbdN5\/vf6tAVqTuX3GYi\/m\/zniXYVHgv6Wg3Zk3EeXaprv5qFr8tNf7cMV2HcV+tJqxoFnY6oqanjTAgKGuUIhFUhM+x9wq27hDdyz4sqXR3Am2T55w+uViKxZG8LfYmD23lqK1tnDkCn+mZpyd5K\/JGWFoi4XYYPq9pN\/x9r5\/3P1fv\/8TSkokShhKIUqYRExaMUJREyEkV2aUgZLWkYlTZCUojsMlNWA9l7Z2+vcY6ZJPW9+gP63m7v2+3zk5vjeL2uc13P5+PxuL+ccxHlbED4J9uooxNs0KWDO1slW\/Epg8eoXb4LKSbPL8TbU7AcPMDhKtcNK73QooNjvXDaqu5Qnk\/h\/lZ54SLJLvic3GrxZ3kvGFzrKzLfUnj1yVijoaEbIoY6ex9f6oPMW07NmmqSi5S9HqY1t2JRT6x4x5UudLOy33w8+29+n\/wyq8CY+MK15ws7VhJfWD6xU100owW7vjqfoD5QYL93qZohyILi5cmsdqUa\/LTROiddQCEwSu1w3w4W8p\/120s9rIG5xGITnRslOMSbWqA1UYf8p5kOc4f+Xf+1ul2jeqaVWNrs0HgppRH9hUzLPzMpVE\/dWjvTvATJJfo\/cnrqsOqwW74X6fNCL9\/XmqfZqN6kA32OfqQoC5qv3lMJwdN3Ge4z2fiq9UiNbdKLaoWdG5\/IViBDq3Rs1kGiZ6tcE3Z5MBDYyFdm\/aYKaXajnnZCZL2SQm8Vve3FTbscJwHXClyp2zzJQbFh48+t+PrPACQidhbv46+C7kWehthTJPcLhcyoGmdAZ8TUfkX7v\/9uHr9MciBVrhJd00I9xT6NcAj1N2rgoDB6+WHQmpJyuBlt2LEpqQEJbUnzZvw\/93vML5qXp2BWjsg\/GsmdLg04upgzyeHnv8\/\/5+f2dHqIVkMHhK9GxITN74HT3LgA\/QBSb+oKHYFJbeCr3eG6vLYLe1UOcimSfhC4r\/NVUbIHD02FsuQ+9MFGfvrT70YKMe9WyV32GED5B+n0bxIMlCmF23eo\/\/f7nV47W1vyrCxH3bBu3R7jBlyeqHR6OEn6gsP50FV9khO4x7S23mnGws8lP8+4\/3sfKleTI5\/8SE7k6oq4s5nkrKtvl6aZSXVAbcX4iEw9Dc3tP\/XVSZ7yfWuqP3+493\/290EzYYuLxpps2Kqviyt36sOxvHPFWvMroTn\/svPvOOI7Ulf3UJP9WPxS\/QBPTCU4PqRve0X0qnXdeNZMomvBy537XIle\/eu6ljXnu80LYcB5Td\/5YukKLBycnPHoSwEqDgzPrUtkYED\/dKZBeiWmtrcqPVjwFQ+eC0XeONeAWykBMZRrOySCx2Y1KVMwyC6\/nX2kAYouXoVbrNsxtP2qthg5LrN0U7rxVCMSo4ttvWw7EJCqtcqGcPPx39fSP3ytxzG9EKuOnjZUHBHUcCS+vCxWw7u1qQ51Dd\/zmwTacNfvtGqLDIUbGz1Vntd1oKnh\/J4983qgPqSeJkvqirfYJkTSsQXV08f90ns7UbuvJNbfkoIPX9Re4YttaHYI2yCT3YXV0TKlv5wpOEu+GdtFfGtDijmfcByNEwMqqec\/MP5zHgubG3Xz2msG2gKW9fmrV0J4dvFjV7oAmz+sUVsbykCYpaBgi0MFOBI598SXFOCrh3HrjiAGNvD41ryvLcfJrUXCjRkFuFnU9ogvnIJbnnef0AQFPbGFL3TCKOjkOzX3bGJjnWLP0IImNlpeW\/htIvX1w9dAmucqhcpZY7FXvhGdlRC2mWynEPw5rzLrfhf8n9eMW53txYGGsq+MDAolVpYvze8w4TPnTfZCp1bsONa13lWrGHcGveYUaTWhKza90ex2B27HaymPE5\/9acm1v\/A4Cyffe9pJ3u3CmTxfu7PLy\/45D9f5uuZKvyJ692qznSFfJTIDhi2TuwqgVMjvlU503iewrMOL8FfusR3b\/V8OIEd56DQIb3Tx8NS+I9wnl35354WkQXR+a7cvId\/f7N61MpX48paD+6RXNA\/+z\/qI01OMaadZg9B5SsJtX7\/BPK1zsakQBc3rr04bkfyjnZ3m49JEgRGoa\/eoh4Lsxs7ymGoWLGuLOdLus7GeP0hUi4zvmlWXd70jhYiKTbUWxP96Qj\/+iByjYJPrYFe+hcLuy5nbjkRR4Obd3\/L4MI2xJ6veyBE+WikXY7OF8Hz7137+FVsGMP7nROypBhr0jhPSwySftCT1e0y69SHo7Urz5loaO\/RWrz73jobfKdldAsd7UZh7eIKfi8IPnsPHZtkNYtNa954dKv\/2hXf2x2pVN9RiXffjOcERLTjaZmirIEZ85Y1VgPRkMx6s3i2it7sT2x5nakQY\/fvvlWIfJFNrNGthElLobZrVglyP5TdFVv7b3z9cuHHtlXUTii3001b6dWB9oPD3XJL\/B\/Lm1jCymzEUaWwULdUJS\/HceR8NKCQkDSjXBxOd+DJ5KmWY8MqsvrX3Eygk+w+NNCuxcWpWiezmDjbs7C9ZzyfzZ1VXOy4qR2Potu9Ob0saQmubb7glsPEsW6w9kOTNGFmvZ4oRFGZXezQkm9M4VTV\/tjbRw87ksSu3QimoneDVMj1JIz+gcpONYic2Kchfqyccv35SR6riOYXmeN19lUv7YCAV2Oe7cwD2tnkJilw0tlkrDqvI9yBm3sixgrw+mC+x053TTPKimnmdqk0DShoDRQ6ebgd3\/PWpC0T3eN1Dfuctr8WbvXkaQU9aIHvWL+25KNFJJ6tPD5WaUJubM2P+9Q7caDJ3PUz6Tur5jW8btjPh9SrhQLEmC1euTx07fYcGVbK5W+cTA2dTnAWeD\/z9v8at\/mWEs17q0ZwPIvpx7cyBYHXXQXy5utzh2ybC06Fb7JKuDeDMjJrFqsQ3b2p\/0ir9f3xzqbSD96FANvJVPjiNxfXDn97cbHu7Eq1\/FtvfcqKwyTbzyEweJk6ffW3mNVAFabiatX4hfX16C7fwExrT5a9ecOq2YNkKyZpt\/jRahaJ4LYiOJZZt8PzR2ITQt4Iz5Sto9Ly7b2FC9DbG6ENC2mQX8kp\/+K8SbYCmumRk+qZ2GHm+\/iG7leSBV+4vNcSa0BHtoiTg0oEC3SUKd\/YSHhxUOnOa\/DyX\/zKdJc6Aee05\/bO3qyCbNjPlPZlvS8GHyk3rGcj73Dq96l4Vgvw02ueNsjGXmz4QxD+IlSV6RseFq+DVLe8fKsCGplJJX1pML14dLykyPleBs9tyBsUs6xHdv2t1u28blmoU+8mTemJwm4Rd1q3FwrFSS7HPLci4bl96iNS\/5e3+ScMDtSiwelXnndOCb7NvTG5e+e8+Sgpbdi51CRPF5x6+WrGeBc+gYtYnLxqLjrzJkg1hYjjy8PjqpyxMdbWuTiTzukRhn9mVPsKTQ69v3j3PwNOqKbEFujS8Dsj4J87ogkRonSLvrx4URWX3Zib89\/sNkr8lxikvKIbeks+tG+TqMFARbfaWwYbE\/KcPLa7TCGHOupMYQkMlfnf1jV8sGA8dSC\/lodFrqBHuuJeG8b5lc8bI+XdVbU+F27LB4zLmMdzXB2uLzPNnlSshMZmZGJLBRlqIxNzx9QMweeHpZZpdiQ0+9+LjFrIh9faRtNydXqx2OOb02bgCYp5mS+46McF1vNNg0qUF6spfDRUni2AU45nyPZWJyyw384axNjQ9zjUObSpGj0iYTwg5LqNw6uar4TaUvp1jfa6xGGVPZm5aosiE5LN7G1zqGvExearv2eIiVI6N9ZYTX\/nGyk3VIl\/rXr+jLjAGEcsbGddD9Jb1ynK9N9Hb+\/llyq42vVg56DuS9ZFGfee9pV3pNEYm7i537hrAXJXsNclEl\/Y08kXzEl3aHq7gwUl0KYqrgFGcy8QcyzemPiksPLly1oX\/KQ3X7ZC5601j9JyP4fYXhJv7T8vrBbBwgeEzPbW6AiW3tUNtOhrAzcfjtneajcszsk7Wz6hC6E72tNPxJnRfUxxMm0vh5OvZT5NrqqD489YTfjTjklLLWDoP4d9dS12PvuuCTphwgvnDXrjxf70vkkU4yrcgeKKKgsbI3LNp1iy8koxIbmbWIONZYo3GZhqN+Uezt0Sxwb3rraN5ZT22t8VbdJI+ir6td9tFhoFtLxc2Hid9lJahFGDkyILSk5Io1bIuGHxeGzNbqwyX+Qw3dhF\/byxwowKJv+cg792n5wO4miqquO8RjT5zTnW1CFIvMaHL2GNMaIk2jqY20ujY7WP0JpeGM01duze7H8I3z26SP9IJzzietv4LPQjlnp\/z8iWFbF3J947X2\/CytEv2\/scuTNsLFui6EB04nhE1wN2E1cI5g6vOdEA27q7tGMmT59P9vCKIDxe2j\/yJaWLhtnPSTpXJWrxyjbLZSnj0xLiDDOsPAzurnH0Uu\/939yGb3B+ok\/GqRPu5o0OeHY1wX7S5YOtsCjRvJEeFApmfI4Y2PtY0qt4L1jKj2ZAWc1xX2cCAgm6k9yGZGnR0n7rsE\/0Vx7\/WSZjfZCC\/+MajswqluDZ74QMBmwKcFDt7wKS9EkNzG5btVG2C6qPtpZ\/+7kNScme02L4SBwRkv0d8aoRHokDg8VkU9DXiorJVWVj8\/MTEJ8KdHTG+SpvIOiy+KthQOo+JX7ULkk+KszDIrIt+50nj90obmXkf2ZA7oNZgpTmADzEXurSLSP8uazsZ58hGyq8raR8W9uNxL3eQv2YlrEUe8X7\/THTsl1H5+Pl2jHRKeRtxlWDG7dKMKyZstFuYhlYl9yHkwpwte1dXouVcVdCqFWR9ZhxVVXhC4cuOpj6uWzTefvqaOs+8HxqZN2Vzdg3C3V6Fd64UDY2omfMer+3H2CWnAycEBmG7oz3\/mgSNAeUIacYsBlbZ5sp7EW57xX1ovvspGnzq\/JtC\/vTjRG1758bcQXRx7JPhUqbhWGC6ON6Pgdz3bZpH9pXD5WrzatPXBVhRlv40aS0TxvHHpfR\/NMAvqUzgRnMhnmbweSnHdOLH50t5i9J6iI\/uNmkiOW527r1Ptas6kb9ZM3D13h5IS3a+lw2hkNKZJON6sQO7UnmLL+R0I0okKIS+T3LLIWfTebod2Kx+8EZ1SDdSe2oS4+9SYJZObfb3\/QaPtoJP6252oizCP8TQlOQdIQ7F5Y3dcKstDy281Ic9gjPvN5JcGbP0A5cfbxdyHOx\/TnD1Qsn7nNqvRAr9TupNEtWd2LKjQ2tvfQ9UheexF8dSuL19o0VpNxN3Uy\/8WXqwA9Ihl3YNOZdAqvuKaZfNILQPcVUtJnVXknO7MNuMBr+x8LCdMhuPrVMTX8r3YZZqTph2ZwVyVMWfsDrZaCq9y8ipGMDxUrvc+j+VUG+9H766j4VzYpw663t6EJZzX3Qr4ZjR4dnJNm8In9bOP3Nq7gCm56w29E6sxMV598ObeNnYKBGlVf+4F8O8z1QKjv37ftoRqbvaYfYNcEh+\/kzFsR3bP7oFPFT+t6\/9xEEPH0YLXhbezUtf3gUj38bqy7YUUiXmrOP61oDw+d72BjXtuHHI4fUWFQqcTuePwYJwyIzvxq\/3UFCP2P5UT6URGgGarzfsIrnvQcRLG03CgRwXzFYG\/Xd9WMVh3zo8TqH4u+q6qC1E56o\/6xnyUxA8vexI8gEmvmrsy5Da3Izds2oCVO2L\/vPra0TWTSmTut1TesahU5mFFQFnNnj50FivXpSo0sJAtKRThcBvJnY0BGw1v\/7vvBdwqEtR6BUFaX+P8eAfhHuW6ll2kdz7UyevdSHhyOuaj7z8VtPQ97Pk599GocVGgVuDcGZnycWpT6sIl8Wc4rq8k\/TxG07fgiQ2Iu4JHw4h33c5LJx4XEB+b9EwQ6frG9Y1N\/bui+4E3xtWMe8xCr8dUuan5H3DrMBLqi7POsGeXqYtdpT42pumdbk8LbAs9y0RyuyEsbzEkvPmFO6uObVQW6IFnAqrnM\/kdSI8zKxD3IL0ReaPSjFBNvw\/Du5Jj+tFQWfK+wmnCvQ+\/\/G7gPjZXC+xYPT2477YoS3RLytBKels9Rn6BoMH6s3nEjvhIOZVdouMxz102XiCZwtYQR\/t5tGduC4QuEvdioJvzi2L6rAm+Dq4XHyR2AEjqZXDyVoUNgw5N9p0NkNkWHpijnInrkzsd+g0pBD+vGiB94dG7Db94XNhfwcaf2W5G5D6evKC8eLBjkZULc361cffgQc+asJ6ZJ7clz08Vu1CI0U7Z\/ALycs3V114voH0YULski9Lr7HhGDg\/uXNvP3or5msUWlRCi45UMJjDxgO+W8XrSC6ZzavkmaRcAblYqUPmL5iI5vfU\/yzbhpwo4bB7j4rhsoE3VwFEX79b3NIk+qhh4Cyn\/5SNgcKb\/MK+JI8ole4XDSPruHlodvp+FpI6d5\/8THgiWUnlZNAzGg033tA9a9n4I\/pJdE0BhfQ7hrNm8BF+3ZlGq1pTCNXV2Wbd043i4Krkz7f6cKTfXamyhvCdb1\/x6Zkt+HkicbZceicCw\/jzBcg6ZqoU7Gu99g2uQmtTo6524nWXUif7CAWdLy+W2fZ\/wwH7KfWrsZ2oico+uI2si\/Xw2y8vGEz0Gh+7vIT4u4TC9I0M3xLcDTkdJOLPxp115vnKL\/px4aWY9I5blXC43WuYFMyGKk3tMUrrR0NLeM6We5WIJlnnwgOiuzW+U5nXmPCuX3BCULAaMU3qpiadLMQylnvalvdAJ4gE6bxyFF25ddrldQ12KDiv+SDdgilxzrdcwkRv8w5tlB6uhZrxBO8B7VZsyvxwyGkNhe+SPK\/UEpgI2PpwfldiG1RuG8gP5BYj6VTKFL2bBb+Hmx+EzepCeG\/user0Uhxcv74sv4ToQ3T6msqDLHxbsPnZ+8warNm5hvfmAQr86lSugQsDTReFnI7GVaEj0OMoRXxjicvSh\/59RK9KPp8oIusxFDjdlnyWhYnrsc9LwMYivftRza9p3J0\/q\/+0LIVS89kRxuEUVpttYMYfp1G5+aaAyzgLe56qbrsQywZffGBpSCqNsgMGI1PhTJxf\/vnTgxAWWlvnchn40Tgepzbo8JzwLoeE5d5owneSo24565nQ1CuUcKisg1\/seoG4hW3Y20lvfiBDgc+2eanYmyackK+dOJ7agQ4+gZNi5HoC0tIZGuJM2Nw5MsEd2YDdyoYPPucXQklwgaztthZcYahqni3vRImGxJ520te+m\/N+vartQNlnl\/eXuHoQPiAtLRLw3+8DNO87fyywh4HY8K011UM18D+VYe7e9BXBOwPX+TAoBGqOyD9+x4JDmLhVemwtRI340txJvpiz1\/xhhisbL\/cH7tOyqf+3Pk\/kBk+Q9e17eF46j6zv4SVfyplkff3DXxgE9DTi7RutJ3FmRDemFW\/HqVNYfLTIz6OwBnuseMqND7TAK78l8zepq1eBNne1vzdA4fCU4SijHcIfRviXqP53jkt8PyjlkFCCnu9zJ0d56lH\/IP7eqyE2rPmLtoz93T9N00XSJIvGLq64N2eJPwtEew6ua6Lxkk\/u6GvCN7fe5v9u3tIPv\/XGNpU+pG64NRzVeih0qBVL85YSjl8X8266ko1ZGWaaHiaEN+y9198romH46K3h50bCwZ9\/9nWK0XgqXxiXRXTvZpl3\/nAdyUHHBq8XitDoarhi46FJYWResPbUFRo+EQ2\/TINpNCfw7P24kQ3GgGrKiauDuFaieOD8IOF6S3VxAXMaef4ix6QWMHFOjTfYQ4KFoVaO\/kaSV4VZgb8j\/HohkkGnRHzrR8XPmGyjKQprjr6fOqLVhS6B73lvlHqxT\/1qRUgKhb2Rc3lGuwlnjtcFBy4bQO1BYTPVWTRifeST+sj47SKvz54m4y\/MfLryGhn\/KZu2ei7Ca+kXBB3nEF6TWiwk\/SmUhT9rl0nzxlbBQ0GuV5e\/GQXmSq7e3P9er3sdTxUu5pSBRfOP\/5JowGDnqTKZH2z4ZmxW2U\/8Wdfynk4k4Wt2hVTV2DQL\/PYbLJYRTpjZaqVTRt7\/RdqW\/rbDbEhyV+h351I4oH\/AxpDwd6LcDrP6MxSe23dy8oe2Y+WTyt1CCt3Yeq2Ydes6BckLy2RPX6UxS2RG6ZLXFFS+aOyeu7IJ9zOMywsIr63lqjZbSHwn41Fooo9AKzxjV0fyEe49usmrtyuZhmzA9eTwG4Moe6Mkfvs9DcbM+ND+FBqc+6PbqkwG\/3M\/ap2QuxL0hOjaupR5FmvL0SsSchwRBUjo9TAc3064xKK6XaWYcNSHZd5HyTwt65yoZfxmo1h+f1KS2iAixuf\/dt9YBVupK8c3EX+umnuBVqpk4HH8e87miio81ln6pkmT1NW9JXuXT7KRLTKbU\/tBA6ITDLMSSB4Z+rb8m1gQqfO8VWpPU9tQLqke+MCGxk7ZM6lPjCjI62\/gCrZtxL31ob6qduR6jcxO7jKjYG+RZJl4vhE\/f8VNGHLTmHqv4RMkRXwmoVzRNKkOXBttL66uJblbJKdrwSkW9p7SPvrpV81\/np\/vrcaKaxyZ+NPHd3qFfgvuXY+Y5BwqQtEBDxWT6Epsfrpy8bnZTRBr6u+QnfPvetvazXXb\/F45nO1Mz2U8bMBVpkCP6BQbUz0b6Sw9Giru3u+FL\/19fmSH1yjRuf3qQr71vDQ8dSeyU8n81X5ZbFLRy4ap1y0\/\/Zskx8koXL5CfKD1\/lIH9RYWYn5FK8t4U9g6cYF\/XjcFM5UF9g3lFDxrjhx9rcmChD5PkPMqNhYb8b9VfkVj33kjLR\/CSU3Za9dOjJDfm61j\/YZwyrdlcwR97tPwfjkgJBZOoyZnxdYbhEfD+SaPZD1gYTx51r5K027calilU5lSBq32mHnD0oQ7OPefW\/WY5IphvRfWVqVQm3hMX1lLYZB3q\/jd7kEYtFqWFp6tgqJc6gOjZpJ3eOlLcUkDuHPY91HYaCV2D9sd3FFIxiHolN5J9Hvz9u97VV\/W4M\/X2UJdK9ho\/VOuefdzLwS+v0\/w8KxA6OvFh5JvspDZ+f7amjXdMJVOOhl2twx99mczh9pY2Kr7\/LHLlx5s8L72QSarHFcrPe1CD1OQ2DgSbBDFwOYvIjxNOVW4cm77HL5AFkqj7n+Kvt6NwhUf68IqynDEw8dWiPRjW3zcoaAnNL4sfPxp240WPGV2zp8qp9EfvDy+M5bGpIShFKOzCz+\/cOn0fiG8e6h8ngw5\/72VdfNXI5K3lH6kTZ2mwPWmrhCVFD4d2bDo8t\/nmIXsBU3sCMfxl4TvJnXjFLQ67GLuf79f92rFx49nHRhQ46AcfQyKoBq5RNZ+XgEafjBtGpcOIHjlUOK9ykH0BMz3BOnnhanrDGv9CV+H6dzke8zC7wbNGj4y3sDjOyxibBgY0xm4eZvk1nUqW8oXkRysX9i6v6mVwpyNFpEJxIe9G64sF9tBoW7WlrKdJMfcE9M5vn2CQk8ew2xGGAWjaic\/5yUUxBntly7fIz83Wn5pziMaxbXPr7FITj8q9WJmUzqFhR\/0TojL\/z\/7ht1Kb9lnWwa14bvmr8broXlP5zjz+3\/\/\/OfLk8kf689XYUPVI8kXTU1YxJpjPDGfwrzzU89CDWrw890Jy9c1JP8meVXECxGeGpdq3ulMIbhjWXUc8Uke3p4wGTbJ1YtqFZZco\/Bs\/+28Py0UVp1RKblDvnayljKsiL89mbm\/Pk2Zhod\/2H0R8vrY9lJ\/XWAvTBMqFli19cP37LpLb8l5um5ZXvTUIFzmtF\/cT7hT8cCYU7ID0f1Cz53rwYDxq3fLGz2YGKnlGbRyIsfn+F+wd+3DjPrp98W+A3Bmi7QNLaah\/EVzolxzADgv8nHN5CASkxRsTu8kdeoftSnLlIljViOtuVYsnBf30vG5R+NBst6jhUFMyP7a\/9ZuohXvqguPX7xSDKnjjRtNVQeg5GjsID80iGeHcjdqEj75dWf4m0pYL3q3NuVfJrzmcrJqd+AvCsqnnG9Y7+tC\/Ydgjn2KvZCeXbDsOPHxNIkVKR17GKgo3X\/KxpOJRa++a9Nk\/FpZqelmAwzINaos\/TSXBelX7Zu8bxA\/f9Rh\/3vnIFJlZojv\/MDAc5mMa7wmNMZy774NrG7Gz3myP0PkOpF3\/XOyPeG4x\/PbQ7WI\/90U+bN68C2Na9XNFhVVgxiV055vTHLM2yvcbuOWbLB284y4bamH+MpbeqVnGZDu7Y8Kfc1EnICK7lxXUv\/u7382qDPwRbsjUNqLCanNzG7O83+f5+uQuSQ4CP2dVzWqghgQFJ61gW1AQ2fsaultMQo\/zh9y58wj41V89Xnasgp8+asKfNoozI6\/n7KM6KKt\/41ud+1anDS2UVtoT+Hw2yN8tYQndjmdT7tJ8syi\/XLvhblo2D4JmSW3m8bV42b6AWNs\/L6eHlG5ho2rhqd8Z1ax8VPk18W\/+4musThafuURhWGh5VUl3kzccLUQObq8GmxV4d1Tw6R+JV4eTKlkgVsioOVpTy3KdgmIvPvIwuieiOat23oQWDXQs9+4HFM\/kkO6w1jolfG2Uk3shoHN4Dm7oTLofEzYUMzHQlBGtqfL6k6IxTcuL+QrReoIt6UsBxvnhu6O5Bj0Ipuj8coxmQpk7Qj4wVtHQ+H6TVYvySOFlmaLtd16YfZHKL2rlvi148ufN8jxso3uU2HWvQhoOdt\/p5TkkkTO1NhIGvPqP9zxbezEQqejv2PJ8WXybCOaHD\/aO7p\/c18n3thaf77fwAbtt\/ZUZNQAQtycl6+jK\/9nnwOnruV726JUBpuZ4rb5rfU4kTCvVp3oif6Ki6+VtpTiPMcSY33DevBav7r5ZISNGdbrVu2zKMWoWZjXqEM9bJd\/vyA7ysYb0YHnW24x4HdldvVmnVI4zPEUPGBfgMA9TadtehnY+fC8rMR0DZZ46Nc\/aPmKdIWFcr+uMaB7wzZNt7QEZ8r9KkQOF+BNbVabYCQLN1qXThdndUNlef\/WZVNlKKSHYvVPEP1LyZYKHu7Diuxqji8qlagXGc\/zEGPj2MxlWlRpL2w\/2KrS9yoQOWdu9ho+NuJ6H0z+fNqLH0fni4xaVuCMu0nhjldsCG2Y\/X4DyeHyGZnNj0IqUXXjBRzLWdjIbNng49aDuW1XE4Q8yzGplyQY+4yBBA6rEUOxChx7lBgj8bkAB\/yeNU6NMlCIJKZVay04AnZKOy4pRM7ZkdJZCgzM39+busyNic4wKRPNc\/\/W87b2Rycls1kw+rzlxlzpHswr4gqw1irHx1PqCVeaWFiUZHIiJbYHqd4LRCdjyvFF4ZyLYCgboy6+XJWf+\/Hb\/urvhMeV6FPQXThyhQlOyTCDFT9a0CCoGRQpWkz4VTLmhRkT4VoCbzgkv6Hod4HBzsgieI9qiXGmE95fkFcZN68H+m\/fvXomX47PicreUudI\/68T3Z5zvAXS8TKCrNF\/f+6X4eax6bndNzR41q+SPN+JZ\/EJguuOUNi9Yg8VR3LCZTWuzlrC5wsOtagl\/mnBiZaRrfq2pC92mPk636bx2FByxgpDNq590+RdsZZG5sXzLN0jNJm3n9IrPrJxKkElkNef5JZxJ96nRwnnfkma5xBHOCh3TsPv4wOI7k\/uns\/NAOf9lXfr1Wh80wgX3blwAPfFTUpDiwex+rpj5t\/nU+ptxp2uBnWCw+BQoGZ0D5T7z6qGRBJOH89Wb+ZtQPOCGAPF1e149T0pLu\/vftTxC7Zfz+iA\/M0+q\/DhbvjZzljU94TCUNOF8+0KJCe4fVrM+twIC6cGg2nuIjSuX3iM7utDSf1VBqOb5Le9e+4vJPorcN3qNXYNQk1m1fK\/9+uwd7jNECR6Pm76cJmAJAO8aRfWKp1mYtr122jvWRofpUz2b\/3MhFLDIKdrGgt7JOzDdZ7ScKu\/rF43k4GAeR+6E\/SYiAlZe87yFA1NgYiF1ySJvj1X\/nNqDhs6\/tPb2l\/SOJbdbM8jzCB9tehKkDUThVbDJ0rP0LDbXjGsM85E9c1KrcDQDnB5+r87\/rYEikvBupTPhP5VBeH6O+3Y5hPRlsP7733DOCdiP6keZaDt1dClmkAm9mzI11Jz\/u\/3uXn5i0UYZjLx+axLfvLGdmSYCjM6qWL4e1xNexrBRPD55Nalxm1YZsDzMuJFMb5tu\/rkdTXxT1OmRTbxvcd3F58rO9eDQdX3y3ZkklzQsF\/uCfEz2f3H9HbN+Ibzxm9FD5bQ2Lq4QX1uBI1n82UtNfU7Ee5QYeutQ3Llc5ZzFxfxUZeT9VEpDXh5MWDLkizCz+JK38ZSadyOdm+J2zQIuQ4BzlHiP3eq3Oz5yXHWXPE\/3\/UHcaN2uVxcFY2mqJ32XdkkF6enWLcX9SP2Za6fiwYNx+96Aimk\/9\/uEjw27+5\/1+dFIsJjj8j445TWKgeQ8bupR1WmnOlEgEbm8AkuFhy1vm80Ge+Ays4UG8mhEvS+OpJi3sRElHyX9EexDniXSnOuOVQC8WjXw4N3mWBxa+tyerTip+kpzSDdYjyriFZTjGXi+Ktn03JP2pDOmeGVmVYM2v\/HqLgnjdlaa\/IFPlHI4lkVT5k24Ub2kiPpboRPRRZ82\/CUgvtx3WDbqUbkKKuMC2\/pRGN\/uWKJUQ+ueGiopj2nEFCppfKQ6PBjK+2tYUG9KAerS9O6AnoMe753hNeoEwd1tbIoROdKXOjWbYLaM30xlacMqHxsZe1+Wo73vNnsTUkFELlkvuHkQwZyywwKL+SXwdZh6SnupwX48DIl6DV3HZRt3byEbVpR7LTztr4khczZKjkn3BvweVVbhPDNdsz6tmGn2rZ\/c+jGBIOcC90MdEqpPmuYxcKjki3Wi0ge4zgjvvwjiE5v\/RP\/lnCmsofop2RSZ4Nl+uZpxNeOPOe0iZjDwsFJbmuNG3+fd3Rh5Aiy0NEnxhE7ycKF1XMXub6g0XF7ZMUuURYMi9L9m3+zUBx4Ymop6dMvp+0tmSRffby25J1UMAMHckOdf5B8lfdprkdgai\/C+HZbBI\/145Nnt5DXbwoNOY8uv7\/bDU1WYl3Bjj6YMOv215VSGPjdGqZOcgavgtTUBOmLFXqCaYbXBrFm+QrNNJIrnBcfPzIniowvL\/rGI0YnRJdZNDwmuWWvEVfqVMbf\/W9EIm+96UVg5DHJDs8qmKmvrN3LbkKK76zEawsozBpK2cu8WYlrTko9km2N8J+\/1mDt7H\/Pp86qsAV+SeUIPJNmlBvRgFN9\/E3hhOs\/SujOXEre79DvwCztv\/vj3V47NHBuEIeXhXraTn6D3bPXvJrJnfD5oipedoyCvHkDZz2ZhwwdhmMxmQdzrcJtvmQe6ncP6+cNdGOdFtcCXZ8+XL241HZdLYVlxQlDfsRPn4ZJmk+v78FP\/m2X6w6Uw+9WgN8zXxac+bZJhmh3o3TTqQfmMWVoGEsw\/Ux4ubCyTPsM4eUt3q+oesLLH305n30wZkNWOHVhU1wf\/He3fHNaVYmX6\/VGKvXYiN91vN\/Orw\/Z8hMctGAljuas2FZ2iYZ8gkdBZiANGXenMUc5NuSZ4UIv8kg+6eM+GHGQQusZb3HzQhoBr0UvbFw3iIaBD3Qr4e46g802T41IfzuuSHV0H0CMs+Xt3eIMuJt1GcSr05jxPN17d3ofmIl75XqzB8CVPhqvIERyeGlXw8cTA7jHX3VsOR8D4ZbHroaQHJ3m3nWw4eEAyROj1yJkST85HWi4vpeMT\/7GHQvtfhy0eqg0Ij+I6dPBZ\/cQ37015Ls5yLQf9a6+hxZiEC\/6jmi\/WUdD1d50iWsajUuRq1KVSF1pdNrY7X0+CB+Pdp+iGqJLNbyPpcjPg2NORCxl90A1as\/uE6TeFF\/o1aaRPil5pvtrxqoB7JBVFL31hsLx3OkgMQ4aycuMf\/reoTD\/zIsAETJfiUN+iUtJfUr63LRJuMnEvasutt8JZzsmDRa2\/d2ni7P0xZAS8X\/estB6oodXLRSEpF6R8+1W5ffe7cTLZK299\/JpbLnH1ZEeQF7vt99b7dxWSGYnrVEhOWTrjCdvDEjdfW3i+uQYPYC3QjyNf\/dVjxpYsWeGeRX8XcNWBGz5im61G6NCLxm4sqJmbvjrCvC4OoSJ1vz7eXxPvZVWrcspJLTni15LGoTGT01HN9MqtH98wzmeRnRzlo+VMicL+xjfZm7jq0HkWzfpF32EX2aFhh6PZaHRxILH0Lf2P\/sCx8iWN8IPGvBV2Prmo0ftuDP56mQx0bczNNNStLcBXlVPORa3tGPy1BaWtwqZ99cS5rUZbSgyCZg7v6ELQuZrBt3d\/vvn9js\/+X\/l3F4CvaqcZfVVdZjY9v7lLJro4recWIsbJTiqsNfOcKIO7QIeiX+fa1CRHhwovFkCqWWjGXw\/6pCQeqmC+\/953uFfx2sezxB99LwKF5acdN\/I2Yx2QR4LGW5yvYEB8W\/3UqiuWlmhaMXArUVGM59F\/O\/uk1lb4au\/IbccYsVyLT2xDTh6XedELdEx59d2Im8FmZC7cmb1npkN6I25JCj\/vBDjnzzsKkk+O3ZX+nfttWY87X4R2nj53\/nZXb0070MZjYuWj212kdyxp+5oxNoFA2SebjaIEn0+mRnwdBap24p+RpWcey+W1o103Y8m+Vk+27ArnsZAcs2ZjecZ2PJD\/MVlkkO+lduUb39LfLU3X1V9pBuFRoI8FQ+LIbzuWvxxtzqcfM+14ynr\/9k3vjFZP6WwDFwK51vMpBpgoZ7Er\/+DjekNjw+LvC+Czhf27Llz6\/BTLl\/Qc\/Dfr7P5oAu1cAmN5SE1WlG72ZAzN7lkyq7DdGiyjUkBuR47hosD6fvFS8aq20+1IZdHRNSY9L\/igZ3VgptpnPv5MXvwaDNe6Gt9Ch7qxNfq\/NKZdA8Gcu26XOMpfOzu17Rb3IXH08OXI+b14p7rYDc30Ze9wZunzj9sxFUXn2\/blTpwZuC04bQahSWJB0TXVHdi7fPcQ\/vqezDnygtOvlgKXxznGbIuNEF8w96kDc86sM9yXe6e\/RRCefu\/7vFowuzTGrcFX5LjG3\/uDSPHeUQHdjgot6My6MftHQu6oaZ0OPr+VQr2pcek\/Ww7sdEtOGDMvQdqbrpbg8MotDxLP7yx9xt0pj5ae8d04ugnEeV1xNfKZhbOl\/JtwvzsHrZKZAfCDoqoz9SiwMc5S2Ex8Qe3y4rSQiFkPS3iV7d0taPRRaXR7GUrKr1m\/JK16YLxvfHcC6cpvHazHvoe2IFwqfl6cxu7wZeU4XDyEYU96pJR4jE9eB62Y0uMRD+c2x7EtHZTYDeePjlh2olCbamZxi496M0YM857SUHl04sNN6614WF+zLn83C50x+boqLiQXGyruEeqi4W1nCufClT3IPKRTQGroBzZq44H3djPxq8B9yBH1z58EFmzbgN3JRb\/mqdtQY4LyJmHDrj04Xey\/ffxBZWw\/qy5bDqxAl739Tax1jVC6b7KBdU\/JP9XeNhK7CqBvWyuKXddHSLFdfqX0f9+Tud\/1dcdGy3UbkaUYdUEd17V0gYY+rbeLp5gw76p03l0cQVm5C4cta5vAMNXZNnM6b\/3o116FD2vHHUZNxZ6aDVAeIV1rerkv8f5z\/+jNDZVv\/UQE2nmRb4n\/ZtBvZewU75eBGUDKu5AIwszN0f\/1onsQeKiB44zo8rR8\/veeQvtdhjOabpsxN+N1uW\/vxi7UxC2G\/S6a18Lg7k2X7\/Xt2D4YiW30CoKnPUq+6e2dMDJOt4pzpvko+2qT1\/cJvWwOCT2zMVOnJS4N652vweZK7k2CET87\/ZF\/9ofZ3d1jImRYeuajuAOZKw6ZBSVUIKCX192bKhkYo3DSvmfzHZsqrC77aRQgltjrF\/dko0w8Jw8d2t+BzpSLpq9BIXr5snqlGM9dG5wSiUHtWF6hYRx\/GYK+XLBHj+1e\/Bgc4Pg5eY+yO8KWL2yhZyf5Ta9h6cXVWmKo13n+lFgafu6kU3BLmaPKpc70WfP2OSfHK2QiYpYriFejO0bR+atL2RCob5kjuIHFvYv8P3RTvi6TZsrwOkxGw5F7HNhaynIhT2dFfCFxu4GQzUNGRbeJ464cc1nQzfhpN6pMBpCkfe7XpM+HtGtsq3Ko9CVE8t3mp\/ki9QWax7St4KDl8+mv6bReW7m+bNqTBxUk1ux\/RONXxPOuwRITte+9kNtf\/MAUtzdZ5Xl0kjNutP69\/\/9UJt8T08PD+AikiT7Y2jM77qU7JhA46PIJ\/5eMwb2lVu1WZUTXVCm9L2JX3w8Xqq4ZcYANhkaLmKpU6hT5pIwTyb8E3RdXkuFxpUT88Z9TFgoOy9gLbaRjZ4V71yzI2mMHd\/yvKiBxvq5fJPvCLcuFXc86v6yD5aSh+xvPCa8mhkul0d486P024UBHUwsUfp80\/IZyYnnPuefJdeVI+Vvdk2bSfTFQHor8SOdNJNFOcSP3NWXy7e4MSD+oNjuORfhm8zFmY9JHuWPLi37MMpGJv+E\/t\/7mUtnTLj+vZ9ZXOKjkztjEHefDviVNzKRs9Jq6waRDsgFy8Xs1CvBhbvnZvflskHtO+\/cuG8A4wkHDy4tqoSlt9+jrzIkd1TZ2T7i6MMbu81qsRkVeFt+bd8fCxZeDywO51Ngg4dLNOE88ZWMnRerH1JsjPXzPGjlGMS8\/J1xG5dUYdXV41hwiY2nusY7euX7kRFmfSvucCVMvJtTfIpohO4f0ft7\/\/OxyDctSx51oN8mNGn163ZML72bWLC1G39mHDvYcZ2sf1zLnu6Mb5D7deT94YBODEYtnsgxo+BbExa8e6wVu6INkuHdhcQ1Tps\/O1IQuDfre8v9Lvh+S17ofrYXisMRB9kZFD7IFK8XdGTii5fT4z16LRB2XbC5ii5C9HSE4\/a1TNC\/vlUqDzfAu0LjVnZjIfTOi0z3ejNBsVON\/ExbgTeRexV2F2N0Vvu767v6Ed\/3a0+89CAubBu9t1SSxo7AyAKuqT5w3jviGzo6gJfH+20XidGoc58ThR3dGOu+vn7Xr14EF\/5++qSAQpL2k3ur47uwxJ9fb7d3LwpWqlhvz6TgOuEXZvSDAWH5eHX3JYSXf7pq8tyiYS1ySOPtSnLdbxoPBwdQWN73g1P\/Cg2ri\/KHM2MJj7y5fqx1DwMz8pa7COwn+V5tpuHD2n54XRUTvE+44qvLpqpsBRqHhxV5VvD0YV3MM9mPygN4nMUKODyXxvB3tS93uyioiRdNhoWw8DBjrULsqVqUbj1ZmlTTjZZ+RS8F4kfqm6ozrlVTUIiUuzK\/mEb5fedBXcLbvMtu9aoVdvzPfKRx96zsp+FF2BbiNnPzVC2yDWs55EkuappyZWlEFqGkM2NN8K9aOA+eLN5BjvO8rfJ3XfYNb72fb9HR64R7Ge\/7WGPC15\/OXn5KfN1X6KnXL+1enL5bfT+B8IOuoHjrz8+N+HlAN0xEpwMCg\/SZoD0UHFz9v9afZ2IieNmtnjstWMR9plPmdxHW1J9P\/H2SiVKTB5XUzBasjP3teqClCPVhDtsf1FfhWrhs2FK1ZnQ1W1WV8FAwagvzCdaswrZzHfpUQhOkXikYFs6jsHjYZO8lsn5ioYxHfs+Y8FdQ7LIWr8algxtfj9iQfBb4RGPjbbLen0Pzsg3ZaF+lZsLnScNUQzxySyiN+DfyWftyWSg2DDQXUWWj6s26Ki2NPpTuOqzjPFSBatUw551lLNjmXclZfZ7kkPisDPHr5SiqW\/l1w2oKCyx3nD1VP4gT0bw3nU9WIUme+Yd+y0ao9bx33jwD+OLj38qRVImOHygcWkR8oOlP9grCk6ciFMPjSK6MlRhJ9qynkVXYrNhD9PVJ5p\/esxf70bVkeFlxNeHzpdXcJjk0HkZMvDjwrh8LhBOWCxLdZ5Rn2E10DqLzliB79dkqBE1W2CWYNIDzijH\/fqt2ZIl8DxP4f+7v5RnaI5pxjka01r308Uc0mutYnyp3kePZuneekfprXpcdG0h03eyPsNXwdwbeuuaMBN0jurrueWgW8RXzPXQ9azMLs00qVT6soqFl8+ywthGN6VQxF6Uiwgv9F80\/POnB3YU3Jmm+fpxs8nXM7CR+tdjvpgLR8crwHv5ThMdbFm8b4BAZhM32hNAXhAsaHlwv8yF6mxnsePoJRw\/yqGe\/Tb\/SOJ0YMvfFexphb48Uvb8wgOnrhhEF6dUQfXRywccN37B4fJvyxiUkr54PqPm4oA7K8j8jDlm3osKfe5OWJJnvuyPZhT0UxkJ\/5jeto2Eyf1bmcVmSh92vZlQfoHG5mXVm1SwKnoeapm2iGvD+zQ6x2SEMpPk++NRRzETlhwgOXKbxZ8\/s2M9n2RAesmeKLehH88uD88X2VWLv7XSpjtcsGFasOHy6qBv9UwsiLGf\/e9\/dmTFFQlbXGeAulrV1mChBRu1+3ytH\/70fndev1StcEsvgSL39+Fi4AZtEzpwbITlQnr+\/b\/peJQx4vmzKHmjEQ42ij46zKfAGWh1\/v7sMzGsZ2Ze668FV13Dy9HfiqzUFIgUunRias915uW8PpAs+BHWEEx6p3LSrnujkwGwZ3T9r69AxM0Rw7tpCjNL31g6sozD3YLrM+sFB3Al4rLPYqQohfodHFMl6aN9ZHZ6fQgNxDUwJ80HEGjsyhj\/ScIhg\/JogOWHPy+X75rYPQDS23e1EJQUvTi9HF3MWTuaPmua31\/zzerOFg9dmk\/zxRW+FvRR5\/c2NjoOBroM4a2gafD+Vxgmhh48ak0gesbNdbRA\/CLUeOY+\/+6xe6Z9D\/d1nNcu3v\/phzSD2awpfPE6+Nzny7oIo+fpJdrX1neFByLsb\/bq2g4nXX2tXyyg1Yf2eXQYK0kUQ2S\/RdiCbicRd2zt8d7YjQ6zw7rnxYoS3LPdU5mXBXUK8uFKoExr1ty2U5pfiUcrm+ym\/mMjI2CYv\/bEDB+Q0EhcW\/Xs\/xv96PHyJXqTFylo0yLK\/XAhswS+nKqcSUQrcB\/hay0tolMynPIRe0djSnuEe5NMJQ54be5dUkpwTxiWxjfTZInN+nq09\/aj7dXAsi\/D7V66RA2okj10y\/HJyFuF3dzfdS5tJvrq4NPiREzm+Pt50T4V5H+xmqIxGkbz5sHn7ix6Sw3YvHLttepcJScO4Co\/nNOSXxnHqkjwVJ1+73Fqaifs++bHuSxn48WLGXDULJuZ5v32meoaGb\/zlcs2VNO5ZC17sP8XGzNfdm48fqIe2xpHnbwlfb5tzc5ZkEA3dOY2T89614TVn77nFpN+5jJLFxsnxDvfL7y3mtUP6mrpcWwaNB6rDRk\/P0pizayKuld38P+OCSK9Rbu6bDMhQMqwL0qUoXzWxv9GqAEanBHLFs1jYuu6x\/ak1PfA5NdLFsa8cKyIrYy+RXH7r1cMvfSI9EIjf5HhJrRz8hhc2aWUUI6cnpGrVvTrk2iqsWctm44P4Tzs1Uj8DgyUSk6R+joyazzMi9WMseM6Bs40N46c2DzU\/DuDwEbg9nKyEqPb1XuHTTCy4kNd4RqIFDx89vmPTU4RpCReeBevYMCi5saGY6oVR5ZlCh5gK6Or97PhTyEJ16YDZDG82XFzs15qTev+yLTvsIIMJjw\/aodGnOpByJ4Qn4W4JKp58l7CKZ8L6W4HuWFQbZgxoK\/\/OKsaO68GVHjeY0EuNkfKXboUXFWMkt7kYe0Kdo23YTJhFnxqOu9SB7aZCrEn\/\/17nXdYdoZ5k3bnf5\/MUE\/8TediYculxGw6zg+bEkXoW6PJqKCF5\/ofzSRMzwoEnrEOuPCA+5LMtOmRsO42R5Ru+Ui7NWMs8d0yU5OXF25KXdMSROvq1QyfkGQMNy\/c7lvASX7+zyDlek0ZfU7dkV++\/+Xf9xXfjR8l4rGJklZ3JeHaf2T3\/k2MbPDxkzGcTPziiUGh40YOCxrumgbuJ5P1lzgpyqvejKao90mHDIPT+PNU6K\/nf7\/sqLt0frMhkIHuOHN9Do1r0nb442TDyFee0n\/\/i2koj96bp6fD3xEchICwyXY+kTaLHfUg+DNnTsukY8d\/MtMepRdMdqFr\/4\/qJuzSadtAttcS3hb4vL1YwYv3n8Wj2LPL9lcyA8e7cyM2tpM8Vf3SdvUpDOuJNhsDvAWwrVmue8mQg5eDPYzb65Hq1d\/T5CzXhZM2Wy7LnO2C27Xf4ob0UflVwCGzP6MF7jkTxC5v6saTlUN2xXgrNn76On+bpgdy5+Pf8UX3YJLlNfUEDBZOS2numJb3If1Jy05JzADXjMl3FM2i8+Xr+mS8fjVmWquIPSC47kmLdFdZZB5nXQ\/sXEc5sTle0+LyX+MvY6mbRx824EPnt9ptLNMrSZvyoe06h7eCB9Mz5TXg6Ltq7x5KFmvbaLWb3uiDLwa+9aEUZJD7INQcVs+CgMX5Y2K4HdbkWWZpu5di5VOvJWR4WTi8UpiW5O2EFIafBGaVwF\/v6iec+EysO5H249KQV+0v63uUaF+NMSO27rFMsuFgqxfRkdWGmXFH2H9UyhJ+2XsiuZSAu4\/vLXT+YiPqRHhzvQePooFv+PI5+9H79qHbwB+HnObaB0YRrEl16x1ijpN9\/vFu5vJWFOi03B27C50qKUysjbAaRlzbzVEc9Ax19Wy+\/M6Px+\/wGybWZDOSH+gdlna\/C0EvF\/I\/bvuKA60xLfVLPIxWiLn\/3J1Ufr2wfsG3DF+V3jv21RE9lZwvdI74alVGa8sq2F697PoReI+c\/wwqlbHK+yYZ35y3utWHfUh+DeYTfo5wexbcQnfeembpnzeUu5Du2ROiT41azpi9eJH0pM5ESqBvchffdazgTST58brJRY6CVguKYidXB0CackW07+MmyDXx5MR7LUruwc8Hcx8LOJI9tmfeDw48NUTN2XzvJFyEvvISzvpBxPPg29Cqb5NbGqDkxC2jcNemPCHeiEPWH2TcgSOG7V4jawocU7ovKqW4kde+cLV8jK8rGzq8llh++9sKnS2Nm+u0KvNu07p044VdnBnPVo1lM8Hxmbk3q+e+fty+977sy\/Mvfv3OKHQl5THKi4srl0SItSFK1+8pJ1o3Xan1NpD0bdZkm1k\/U6jF5KWLuE6JHv44OROeqkf7xtDji59WMuNpt6V+KKNxb92zGfE0WyhdN6YvF15DcsDp7QT6F\/VPlymLKLFzL8q519v7v9zn\/6\/hqPwmT\/BgGNvxUMPOyr4Tu4qfbZX4UQPNztkcuFwvTfncepLJZkOdY1cxFeKhopFrjSzQThTVhhuvDWEjO81\/V6Uf05jC76mQjG1HbnsqcMqfAVfbumhrRI9dDnWHdD9noaPc0sCI5W5oS\/36WzNcGY798n2w2tri8fP5Lk8J2YSxNJr7+a\/HQ8qNL6lBxAB2FDq0I7MCJR+T31KvXXr2eR96\/PnrZJfJ+Cbvt5Z5+a8Gzjp+lnTXk9yzFLx4lvCB\/kdFoO9GDablXtvWknufOmIq0J\/XMHGDz2Zr\/932BrF+YZa+RInow55Dizbp6XGl8co+b5OTRO1V9Kw41QW+ekupt3w5whS+aliXX4azZc9k1jg2LiTkSDRP9uJA1S1AhuhLWzap+w4UUkp+1yqhrsPB7xvz4nMga3EjlHi0jXFLrl7zJLWgQj7QLit\/pVaHpj9fjir91HjJ65t1KMs9XdsjhYA38eLorq0YYeP2Ew9i9pBZ7jb4G\/Fz07\/8r\/WeWy\/NkJyb2S2gJm1xswdOFb\/LLJougIaUaeTuLATV\/922ct6ugO+4RvnAn0YeVP29EhzPgUZr04ej3CowWySaxWwqgFTY8N6O9CbSxcu3pog4Ue8z5GqdNcuau1pYbAZ3YumSHe1tkD46\/q99iEUnhGWNL64zudrzf8liYX7cbzbyHr22\/RXwy8YGHn0QHgva8np3p1o15rzyzZXwojOf1NBzZ1ITLV9ObuK92QHWh+GGefRQeC97cW\/CWhcoa4ey64W4oUfLaAuLlcIvvWJSTwIJ1zC+RxT3dUI7P85wQ\/DdPiTZYtTnpsLAjckjFTL4L9b8\/ZvY3lf7zfMWvdA\/jcS+e7U5YodXcj0nptwXSUxQEWrr4pI6wIFS82PqOfRf0ItbX\/55RhgfOMwS5QllwC+rb+yGkG7zKtdbe3WUQETHSTlnDwvuojbTBpU5kjpvo9umV4tS5S93cYmT8\/vzx4maEFyro9anbS6F+NHHsRQoT+zom3yUOtGFHSISZZF0x3C0NXJVOE90UbF2fWEHhc37u\/fyf\/\/1z7+CM\/aYBJxh4GJ92M0G4CL5JDt36MwtQr8ZZemcfC0\/0\/mjcEerC3l+\/e2QLSjH8ZMbkmDITQXdd5JcsboKVqv8bl5X\/\/flZTn2\/PyFVTLRsvsnFOdmOh5XzZ6kql2Di1tIteZ+YoH7NXLviRDtmja+KM5ldAgsPm5Un6hg4IHz0g\/XcGhw5mRVj8OIrotaanmgnfT1qWMG8TPra8ad\/9TarXrwbuGjjQriGw3M8zZJwDYNh9KeltR8xmdKiQqU0yl\/2b0ojHPTB7Ux+zutOcGyTdn9CsbBzn6+My\/xe7A+RzDIbKoeuucNwmwsbAkvmZ+iu7Uf\/zXt6Dw9VYu2o1P+x9uXvVH3\/2yKKEIk0SRMyhTSodEelSCkNJAkpY0jGkIomlWRKKipSUSqV0iBK5nmeOccxnWFvSSnEs\/oDfK7r\/Vzfn87Vctp77bXu1z2ss\/faqmmgEPizYaPXJuIjd7VveBsz8b5eFfn3nYLXMPBnodTrsAMspCtMavxDfMfm\/oZQh2O1UBexHm9Ib8XmRZsj1JcRvfK+eeRpQAt+t7I5izgMNK\/cUjrybx+tk9NTbi\/mosXB8X2NOwPbXumHsI1K8NejZMHqPVzU8S9YPMmQCcP13MiKvhLoL\/lhJavMxVH\/rtuGYQz8DlDzvGFdAm+7rIM279iIGp4qNd+wEi+CJUcXauT\/Z\/y8aV8VcXJXN\/ZPtqs96NqLqH1yreLiNNKPDCWtOUtDaGX\/lHjiS5TlO+xlx7mQTxdaNRrSjKlBna5tQQxIFqx4OOvgv\/3BBJvPNTbD48OsGL8kBj7\/GhcpPDTxepTbssCe2GQKdjsrC3wJ7l3ejLY8vEXhppHBatasbsj9OntSVb8XRfOd0p2n0jj9Y7HMemUWqrjhh70\/daM9s6vQpJHC50WLQ9e9IZ8djZOPCNKYZuVe2E78+5i+2ItH5hzYBH1bvN2GC6M9B2frEr+yKdKrSO5yA1r8c1jiKzsQOH34Qo4+heIrm6elnGajudZs9FViMfzW5F4T35MHC1mzKvZvFr7\/knw\/atODS+5WFpUcCodaDv7JPcTFvNRVt3m+TPQaOV0WESuF3FMRhyrCJ3eqvIyuODOxuP\/6ZG2BUnTKSkkbE3y699qyNYW7kKFod8SVLsM1MYuB2Etcos\/jJ46t60Su0rmh0dulqM\/elx1A\/Hi75tftho8oBC\/btvyMfCMMrtixNLe1QLB4V75DDQO6V5kFJjYUKizOZC2I7MCfKq2ThtWdkHZ6mjFIfFPppqN2Pb7N8P1exZ9I+Opgs9C8NxbEL198tmbTujb8ZZTFSCYxURh+NP7ayYnn67\/iarOMUpspPxcd94QKXjZ2wGFKZmpV88T3bV7r4m6cTHSte+mB1A7XFvBWpndpDhFemiYwllDfgbzTV5S7RVhICF2x7kAMhcnDkyBs1QIJ\/s6Nba2kvgrXcieR+mpi1XE+OjLQMKipev4sC3vDrZmN9ylYGrjrnT5Kw26Wr0\/9JRpyvS4l5\/ZPfF0n7ji+WvKP59rfKxbaUVCozfnQTfxPfkt68adMCobu\/i2fCS5zRp9Tun4UduuIhRyVJTgadtZyJuMe4tez42AojZ+GMSL5YxRag4Yur19P8jn720ebyRQEDjlsYU+tAntzFY\/fpwnj13wYa6dTuCrpXaGpSOFlsf4OG2YfOIV5vSZuleDERgvJfqWw3isg8rIWFxodp7DdtxryMvtDDffxUGHaxFB+0I3OnsA\/IfMr8DtpdZ\/KKA9GPc4NZav74Bb7tFJKuRIiDrbiTaRe1L+nO7YJcuE6LOzjIFmN9g9\/ako8eEi\/cEpWbVYPfqn27xDYUQF+TWNbM0UG4vMPl93dzoJt9L28hDsU\/g49Dnkd2IWYw\/Yt7wp7kPOk94LYHwoUs1CmQ6oSc8Y\/X\/TyasTjPw7PN06lgIK0H4HE5+06dHNmDOHtsK7aD+8\/cyC\/2SrdsJH4R6mHAbxsGtoOW+2KN\/Ug3lSxLofk\/eqokmeLn9IYDnDQmXKDjZe+tfFbiV7Ea1jqrc6gEbB3o\/HLRV0I1ck+3DtQh\/GjRcEGIu1Y0bDZvWIlBfYUu08prxqx16abfSCjAzpCvQGbjSlsfbPr8o4dbdgefXSzXSoTD+1O2G\/yJH4uPmz3LfNmGORqnXzowgDbmnPv2YH\/fj+SkkW9jY5bGQTqJpt0nKmH8pL0SS+HeTgnrhQvlU6DG3x0tPIFDUEV00C32j4M5ZycN72WhpjsvAEG0UHFXuH753y6YFGdtM2ffC\/FcM7CZeQzeblCUhvdh7q4F5qbGmjYmmkIfsyiMX274q3lNd2IzUxJNH5Ao3fmu6\/bU0iecsqq6GliI3uX+R0rKR7KHTL37vjCQ9GlMmkfcp7DD9pWpL9mIzIOCWFtHFirHL9\/i\/DOw4rIuYGX\/uEsn7q+h4dR4Yafq8nxRHqG92T6M\/CTv3T9gnCS7++oWm5OnHh8pu9bJd1DfPL32zUh\/+67KXs1yI0keaJnLLuuexENpeqRi2pmJAecaLu3Lp+H4dEdOeEk52mJ587qukdj9c4vB1OILprZfL+\/kOiRzJbG4CiiR3X6Nt+i+XjIuWv4ZvNcLtrCpO1+GREe6A14NnN5yX+er1dnqxZMInV9gNlQf0aCi\/3uZjN7lk28Xj3hcwfxGY8TxHno+9F5kT+0C4H7SvJum5Vjb8kzgRw2qTe5nIVz\/7Awd++VtrjOMhw8f0jDheSh5UleBbvb+xBQcIsh6VqJTewpS5qIXsh\/0\/2dMa0LZ71MLm\/7XoaNpscEVvJRsBV9U2d9moKUbWjsv\/tVJ0VdWPJWlYMLkQNNehuIj7jft0L0Mo35M0X8+R9QCL2Y0S06RGGv+bJmR8KHBU2XjT8QvrxRNhrZnE+B5j\/ccEGURk\/TrhvGe8jnBYNvW\/xJvRokipp48aDXe\/N+8DGiz9VrvjwrInUiPitjgdDE99WPtKy5Ik\/0vcB8puACou8GC+XiTsRReJpwbXlmCA2dzXJ5EiR\/lnZpHxX\/NvH6Ff\/sJ5yUJDZka1aUz5hTgYc2cjL3WHlYGr\/LWD+BDR53\/GDTtXI0GMu59Jbnwe\/zi8l1I1ysfeLXex5dqK5dPrx4bjlc+tqdCk25GHYTGRXfyoTHFp6DbW8JzvQULtQV46LpTRdDbxoDSppvZ+rxlaBMooaps4SNtJaWhbnOHMSvowMy3Gj8KlvwS\/xxL7YL7srM02dDYPctVBnSaLP2ay352w1ptzMZ+T97UaxiOLxvAY3WrASnZyMcrMbxzuAPHRjv8PmU+K0YYcMDk3fe5CL6QN4X9dOd+NzlkyRVWor7dUXyBkbED+gqmNnLM\/F4Usyt38UluMXknNXip+H4sMSrcAONlQtXlN4c46HA6JZi0jcKJ+yf1yRI0ojVytGdfZTCBbkNi9aKU\/g4bdetWpLHLHSfKUTcpvFyOOGcWBXJCyr1C4Z+cmBZHOxx7AyNC+sPZDxKYWPZqzsjV+s44Ih4eSYFkHmqUnf\/a8nG5ytpRxNiOfij2iKx3otG+RrZxFsP2cSPZ95wUKrA8Of7Plq9eZDe+Cd\/pICGwNSmIaP3NOIi\/OXLD0z8Xq1Az3ppLUcaB5JyfOoIHjNx9mb9uQZc0FQrDXAlvs7KzHbqXzYsojT0RJiVMNYVCZ0sQ3Cjtm6\/vhEPlxnl+VGjtdjUvP7VliM06gO0zZt3En6\/KdJUubcBIcpHFW4QfLPn2xy4p8dF3Mg+V9Hb1Tj0sbTixGsaHloSKSUvadwPHVqjmdaHaaVnFzIJD7F4ki\/OOPTCzlyqmKqtwFr+mT5RjlwIlX2MCEsjOXH8tLC3dilUt1o\/eX28AUa7HoUsX9YBpa2FFEOP+IG3N7ZoS7XiZWvHPpYKE3f7FxzotqfQcM\/D+iQ6MRJ0+UnTWBf4QzTka\/Io5G90eGE5g\/BxRfxpni4PCfNkotQ6ajHLc7fQv\/sSI6\/1pjjF0ngkyfcuzKUN+bN63um681A3mvTTQpRCdEFxninRz0CdH7btRMc211xYeKSW+I7bhXcreRSWLtpmNeMaBaeb0fvdeigsqiyVb86lUBXea7VwFg\/rE265fkztQlm21\/tRj3KszLOUy4iqgbvv9+HVf1tw\/F7PljOLKOhLvp5vG8QCfw5rLIa\/B1mR2uUCHRRqdKxbMvb0YkpgeDmTjw31uzsVnPQIX6\/cL32J4EH0zGR3mbs0+E99P\/FncQcWOXJHysh1bT986fexWzRKzH8Ktla04bBy1FAG0fu3zWKWcWk0rlUuad2uzsbrGyIx9qNt4Jx6oOI7wMSFX711iv4UNrYvGbE5Tnj3gEqglAiFH75BI6JkHJzeRtZ91qawTEz+RPhD0m\/TuGZLCxoav65Eai\/lod0\/ee6FCh4kvpjcVP63L0NXuMQg6ecCw995WwluRxxm85tY9GL+TYOQ4Vzi2944DwVE01g1pO91Vr8VrOljL4ZJPmV9uims9JzoYmLqyMkPneAsldq0iOTTQfaYT+wHGjfvdiTfWtoLZ4us0Y03abh4qHu9f0iDd7l+z88bHFSeKxNWH2DBhbdgV6ZlDyql959YSvLFOe60Odm2TVhvZMxV5Wcgav\/UUw27KRzborF\/7rV6JO7bmVV7vR1pl\/tmvV9L8D11pEq5nMYDtT3tW1PJdWhmdq39xYRFvzBX8QIbawwKYkRCS9B83qE02y0PJjY\/jhRfIzygQNEsz1II+UYIC1zLw4C\/vfBwZj1ijKUH0jPaoZr\/R0xpPcHtwe3GX\/82wqJzRaZ7XQdyORaV90idVdx2UDgzXou7UZYlHqvbUGPRpDVdncKbaT2GhT8b8NK90FbOrgMCFwbKVxtQ0DphNz5jVTcmi46kZhNe2Prres3xaTRuiJ69cjOYiZWSP66YHeuCz+G5y0TeUaitNvnwdqgbMUUZm6d878WsG4N57+VoHMzLiMte143gNVd1Nax6sfLQ\/oyxaRPrEUM3u6yrisYe\/q0B+kQvFxyNHdS\/yoLw\/TzGDeJHLmQLJ3XmsPHR\/VLq1KJKmPIf\/3nzBQ+mK12eKIv2Im579HLPFxW4o8vTix4heLrR81rmOxfpRR\/CNJfXouWHQcu6ywSHmWuN5Nx74LPARW\/+iQqYTNc+E9xJYf\/D4EddCVy8TudMXe5Zg64RxT2S4GFBViGflFE3LKV2eV\/4UQ7zSP3NU6IpzFu8xNOK1O2CGfkaR96Sel45xY79jMIue4kp1DiFmSnTQ\/VJPX\/cena16E0mtr6Im7nYuwvFfO16EcTHZH3yqVQ0J\/qo63stN4qDaQGbBPM8CX5rUyN6E3oxlaFf5bCejV87fm3nJ\/q1G102WZ\/Z8F9n8\/FQDwe9VRdtH50mvvs5U8l8aw+2Kk7\/tG55H14UJp9NUaAxqr5XMF+VizI64YJPHAPqx9O2nXcsgeTv+WK95lxY3W581WDLRJSnrmX5aAk2PZnbJF9D\/CTT28AqggWroX02MrFlpK73j+jOo\/Gs75qd3mEeAux0135XrYNm67trnBM0vJWk\/DeTPN\/oOl58L68BoZ7JN2rJdfS4rB6SDaXw3qdPbEtrA77kVPiFSZC64+ia1a3m4ec0pYMKVbV49ivRZiiqG0\/WTZdkJvbiZZ6bZOfM\/\/484ETt76fPmOYRXIZ7kZ1lZ67UgxE9+80w8fmvA9Z0yytXoMnj5Oe8oAY0NoyUxU4iuald4Jf6xjKMp3k8UHSoR9fF+DDB\/\/FegInaa5cl\/\/oeXoqg27JfpovWY3\/WmdYLQ\/\/9OB9sF7eyiT+flt13Xt2Ai4xzOkGhD6tRtvld8ttwDlK2TbFOTW3F3Jyhp4nWRbjrlCd7kMXB6Kxb0+N3d8DgwK27JT7FyOl6oST1jotOritzZAYL66tfiHuuLcOsU9zIV8ZcvJtcpXWc6KBRWlb5jJoSCKVukmirpNFeOP2QONHflhw+Efl5LEiW\/3G+TXjMXFvqzRqiAxJ3wj3nKHTiyJ3GP3J+XIzkFEyX\/8nE9IUtc\/Y5lEK82r2na3kVHn\/jKo4mNOGh6LxpZhIUHo2pyqhRbDxdGK4wL6QGb6P3GWiO5aMoz+JxTjWN6625zp9Jbjq1uv\/Plkc9mH5tSkb3Lx52C95627eoD4c6zifELqxE3vLnSbtieNjLkJk98m9\/aHtVA+ULFRP61b9\/5paYSbKhER79WuAQB3OX1KXWHKexqPbs9jsNxMcmMz5pEj\/IWKIXIXR24t+RM35mpi2X5mLS93k7zJczYCvbWJw\/pwR\/Rs3OqzznYaDqSuF5oV6sZix9uyytAgNxNwtlD\/Igs3SL6YrMbmxRCjVtU6jATGZ4zBZynih7LdtEkps2nR5k6Y1xYfT0OTQfcPAx6WKQlVEb1pWc1RyK++\/vUdqRkP5RRpGDDT81YgTpemh8EaA0Ggpw5HfyuadMDpT6LNqGDTvwMvWDx3KPYvQxsis31FEQf5DSuPgkF6E398yRFav57\/sgsdNs13mx4V2XH\/jqbBFYgbvceP8f7zH\/YjzTmCVeg0u6XyJNLrdgq8e52vVyxCdZndmRJFqN655\/lfkuNUPA6c6iezIU1h36dLfzMI2+bMH6E5soXN1c+frS2gboSQk8a9tSDaW5NxIVcpuxzlhru54s0ce8\/NCYDDZSlq2vkujgYJVRUXU+ydeTZu9WuGrGQSqTz\/t3fRPiomKfld0oRNu37fcyD3CgMXTolMefJlQ1tworxBXCc9jQXNWMifQANmurfhfWh9sMh77+7+sS8D959yO7GCsOK\/mrqdchWlFfJOQ7D\/rPtjXw+ouxoLTyhqtmHV6tGrwd933i9bGq08MxBYRHsxWfhssa8LDk7u\/ffwdq0dQ1Zd1Z4qsKbLfMeR7aC\/\/mkutlnUQHO+3rdacQPk9Kd3CS5cFtxpuHeZdrYbrY94TX7x5Men\/3ZWxmH27nP321ew0N1VUd9012VKLu+yCz+mUjxtdGHuwUpvDKwe6Otnw5rg9FvWS21qMmWFNs1V8eJAX+TMJjDnLCeltz7nHhvaQ3+N\/z\/e5HHBc4kHz586\/bn0UhPMju0zs+5QXxd5bll+oEKMRsHZwhc5bClYoMJaVnND601r\/fWsJBm6brjpsF7Vhl5aR0QrEYGxYrXLzBqsccdVe+m83tsFxn6RasS3L7r34VfGxEhYDUYsn3xOd4zvUJNaZwyXjQe1o+Od5FlX29xN9aX0zpNprcjv1VGlVnJjXAeex+dfJgO4TGY467baBQbr3xgd6RevjMuzIjxrkdKdonv9jpUHh2YmvILssW7NnuY7uglQHtN\/GMHzYUAg94TmbcoTA0XV7z\/ksOks9VDVmbVCFccUqGNsHllbrwELfdbGyTXvboyJ1KLF0ye5u\/KxvP1+gkKqYX4jJPdvYM6f9eLxO1B8Q+E5GeT3jgYf5PjX31aHyReKvlZQEeDElejCL8cNF224HIX\/XQeST\/ZUZTAaIeTarZnUHmqUUkSmAaCw4fn+6J1S7DPr4E7aJCHvw+fPo03b0XqeZ1OnyNFVid9vZ8TjEPaVW+Os0+vdio1LRcuaUCX71YWWtPUkgqopyW1VBwFixPvtVPwc2Mq37bntTZ3OxOp1Dit5cqK9CmBKcSHb8uiHMwVjDo6u5VB8UQz9XzThXgUXMh93YaB78b5mUv\/NAG71exjxxyi9DXLxsabslB0yWmzuylzUhWkXYUeliIkarnuzRPcXDjkJCMcADhaY2\/fO7hxEetO7SlRIALWZm3c770cVHj5j9yneSeWNfST4OfSN2KBe9nj\/TAd9oDypP4uE1btt7aWMFG98MKJ9l3VZjpwTwbcSUfC+\/8MXCs5+DcjoL8OpkOqFarycQaF0PYaOm50zu4WCb98LHQciaUtboXvqsrQVz9jqcnMzjoWb5L\/SB\/O1wTD\/dFtxXhS\/PXnsUxHMhtedzIbmlF7sYkfPIogikGlTO+0LgonfI4kfS7VC\/lCf++ZsgrKlerkRxakjjH0YTk0LVMEe+cNpJD71w1\/UTymvfab5p6BM+vPWN3NuS0IaOW7de3hcYUuQ0HKzk8WE1yu\/\/KvR4bVe+vFp1F4XF18FPH6yR\/6v8tTbxKI+3cs+yoBAo6z4sis95zcCztYOBhuyoUPkqbkXyUhlxNxLKfl2jMWsU9iv08RITX9hiRf++JaI4PTaDxfs+hlz2XuehvWlfLf74aS4qPaIYItSBrlnWY2ByS+7ekOnn+JOP4maF6360Z\/aNB84ekKVzcG98vM0hBKt\/iW3k98RGTtg7+HqxB0KIVp7vKmqESX\/q1I4GBmg0Svh6HKDATnBc9+80FN2j8x5hWFx4w+2J+S5TjHn+HofNPglvrlVOlFbqgJhDVEiBU\/n9WRxU63+Q8otiIfGH00E6vDOYHbNQDkyeuU2W3wNGTN9m4kzr3S9PdMhQsc5zJn\/5v\/4HPP02ekFy1VNtUbh2Nk6kdWpO8moiv32YgWkZj7Gfub+ZjGpurxLKOBjAhX2992oG0R26XXfOY\/L+I2MM6txOZuDE58j6DtLvt7N2dmkIjVCDNaF49E5p29QOXSS7uTavXvEp4ds33U98KmC04eviW29p3PFTY\/w3O2UIh6KnkBQ3Cg65Vzx\/UKhGes5W4\/YzwVny0qvglVxqC5T6YQeZltcszr43aNDyMw5af\/aezSSUGsgdp8H\/\/qixD\/EtA8YvaeQ48+AgGK3Tp1mHH6I+ywONtaDtgN0tUg+hg4\/DrUvcqWO2SdtZmNZG6P6+sMWPi39M\/mF90Cw1hYws7NdHGvAS2z\/1Gwh3zkLY8bkU+aa9xbqWeHS7B9EcXP\/k55eF7xQ6X24Fs9F3xCF0RXIzH502GJpnkYeTtkc9LSF0IWKs1DZN8f6bizsM5G9uwP6B4veMZNsTeShk6NhZjxpo9AZ8P5GGwXMxPdZyDjjMHF9oVdyBTgl\/FpLIY923HeBoLeTDatSYloboLXHFFBavIclyY\/vbv3ak89HtFamh5dCHOaVWpweaJ8XZ1nmV1mwUXh\/byPf\/qzET5JWXfQwKlmHbq+swM4yZUmlmdvf+7A88lTmQu2U1B5Nsa9znaPDi3RanZt\/DQ1LLbMub9xL5045tVCqvW8uCiwdWpIjn+tOEyk67OckwNKnyQL92Hj4dMywNj2ehIdm\/N2Ut8r2z5ZcYzDtT7Bmecf92G03z214ZziuDCb3JyRyIPX6HJN2MlhY1Ham5ofqPRtfh1v8wnCvkWBnIgef7Rlnj+SMLv4uft8+xqKdxb2rVvszvJkdkSI35CNfhto77kwEsKlwM3Wj77xcF2xtlsJ6oKuRXbLZfLkv\/fLs+4sZuH1Wpml5zF6lA21YMV6tqKI0UqbUO7mJB0nP\/htDOFF8KbRfU0GqBgvfpahHgHehfxf+CC5OsXxk2KK5qx2veLjqslA5pbHXUDzCmERY0fWtLYCCm+5c+i8jqw7tfwIu8dFOr29Xjc20r6uVDR\/5ctG6nKU7vPJFZCnRtieOcKG7XzRzjFnzh4P7zIJc2P1MWy0tEHRD82d1+7Pe\/feuZkjXCZJ\/\/2KTzKyo6m4eu5ZeeSPxRaCo1VRVobcXTJdYXvpG4FrQvOtunQuDKlJ1ze47\/fFx001d9RsKMWAxt9MtXntWHNTYeT4moUKpP0XHIcq9E1VfZ0W18zhkVVGAazSb3uf87bd78WjrlHV3R2tUIkzmb5dBUKzeqzNR\/31WHPQf9dm4ju+IRs+htC5tM1IPN9IuGl4s19j2ISy\/DCMXjwXfrEzzs0q3aLKr4qxeSWa0xhuXp4Sp4NFfjNQ0j163DqfiVO+Tzm+ybSBPVvMZrGohQ8xcKObDtejYbNqjciec0onK1\/0\/pfP+87mpwPL4Pq\/OU9hyPqoV\/Vbak8wkOWr8+AI9Gfm14GvRvu02huvsON28LFJaGyGBNJGjs\/lApMN6Khw0n25O\/ioeTmnkf9ZJzP1t39KkJ8ofXSWrUmFzZ8Tr9pWUB0xVzjSvExbwbe2sodOGpBEd4UTlcxq4frIQ19OZt2bGIu0eAn\/m2sfXfbxqYGfGXYszTNOyCR9mqjGeFFj3UDz3fw1WJ3Zl6tg0Urjh8ILeEtpVC4a\/mYrGc9ku8wLFRPtcM7X1aOIsfZ\/+HX1ZS5NRjVWzvXOqoFbmGNgg9JTpnz293cW7IefEmOwZ+WtMPd8kFS4SqClwXWm6oLafzO1SlpIrqpav5wT8GLDigNypk0V\/3bp+LNFNVXRAemPdpYcpE14bx0y9e625OcMTWWvy53Mo0DjDsVBucoNN5T9zW9QJN5HRB8H0+O02Ny9noKFy6Xrt8zsiK+d0dToG8wjf2296Je2fJws6v\/vgQ5nv59J37H3F4c\/762ff1IBc6yBfv\/7Wu05PEupZ+vaQR55BclLP\/v++Ju0HT9u3A5Bxmff+mkOTXgzblzr\/iGCmBfslh4E2lP6JmyPsWlAb7u8VuDSPupFz3vmGQclvh1MNeRcSiem7XoRyhrwuN7ZLPOnQvmYjh\/4Ijxkk40v02rmXSlFJXaZa9nkTzLFxpewppP45pwrfpGQwpTuO0z4p5RaOuNkU8nPm+h9IfTRdeIT5URKjK5QWPuLR37LYk0Hl63C3Eb5MBEaVWE0W0auvlT248+Iv7qooiKqAkHsY8TQlbJ1eLEcZGSXZ6tuJvJn8VQoBBgubQr160UP6pTbO4N12HE\/9uA2BAPfEvbihwtS3HSy363Z38dtHoYx\/J\/8cB\/06V3lW4vBg4HzTKh+2BYvlRM9d++kQMr7C+8YCPp73SNdc0caB13KVhB8mmFxxeBL39JbtX\/cKlClotHVey7N0Jo5EmFPT62i4ex3P3XisO6sfLWwvFH0hXoPGSxZ5M4D8cefKfXZvFwZf2yo8MZNLasapP3vMWBQzfT5FcUF1Lpn3c7R9KQdM0+sr6egsTa6hX+3lzEpEaiaGYNbAcUglI\/k\/pmnq4bVeAiQ7xk4MWhasS9f2YjZ0Dj192LlcFcHlaImD\/f6VH\/f7aOp\/nb9tS+hgqomTtGdaxqxAOfL0\/ChCgkhHzbdNq5BcdS92undzLA8vj1zM12Yl+xOCxnekIQG9e+Dq5bmFMMWpSSzNyfB30xZ8PUTzS+IVDz7hsad2bnXdpN9FJYjdc2+G\/fCc0UW89MGtpeThXH\/Cf+veyNxomVSYJc3J2Z4f6ltwPbtr8K7uouht3zq1nPiW\/1DXi7XzaXwgr+DfMkpWl0G1880RJE\/LNboIj4HRoapdPGH0jzcPvj656IDxRConrezRehoeK\/oWmxN6nzmZd1P7ZQWKA8Kta4iIbTsR0Jk0g+XXn8kYPJWxqaT+WFRtMJLz5ye\/7qdB+YGwr\/VpA6f3fWOecFyTk1qnJeMjWEB5T70zyJbz\/aFNZ1m\/DPrxsVe1Zc\/O\/PKRy\/e6XpbwkbTf6yo0Pnq3B08V1Z6aB88IvRCn4pHTjtVau2obsTIXFsg+IICnvY5T8SV7fiTseL5LS1TDxyenVmnyPxOSlTvxmYduDx6YEpSfGdiHo8WNV4hYKtX5irviIXzcpSRo5nGSRvTQ+cY1aCy4Me8bejOIioaTDkK2\/FeLw+O+F4EU435fz0yOKgVVbn+YhRO\/j1Fize+qcIrGkPp+ZEchDH0l6B\/FZcOjfJPM+pCHIiKcdnz6ORDa5MnhUPrZkP19Sq1EF25auD1mTeV69xtzgVS8MmtHlRsUcbjNnB27+Q9nPzQmq2k5z1e8bNrzPy2uBiMWY2eJKGQ8+xtQsvEn809nKxW10DXFu2fSjR5WDP7ix7ReNGxCw+xlBfXojdfN4iZ+Q4WHp79o6\/TvWI8Eucuv1tAdbk89\/uC+vEHU+7Y4fQDZszVqHSpRRk19uqzCPtx\/oWx2ds6MY+5jIrwdKJ15c23nTeoEx84uTNKzcoE94+k3ul+YhJH4Ra6eVOBCfjcb9kpxBeHZ7zuGsooA\/Fgskv62totD747ehM\/n5UTKB84HDXf8ZD+6XjXfNb2BC55uQU4FqNnUo10ZMz8zFmNkNB5zLJ6e32rnfsWzHjxaLt97ZOvJ6Z1\/BcewnR4cNJxn\/nHmBjaOcXobMJldD1Fuq5UMWDh9vnoFcRvdil8iBhek8F+FNtwio5vdhmMSyQ4cPGvPFOzchdND5FPLyk2MZBroXc1KxiLtakW1X9JvN2v+LpgtTRPqgF757SaszB6\/v3l35zpqEnK3o75TAXbN6vrNCzTHwSfXr8sFTphOMsy1EQ6FrIhfw06lHOJB6xxJJtrvdo1P\/dM4Uiucx5cEPdN5LLin5optm0MHEy8Lfp+XTiy6ZqGBwSILr\/4H6f9\/n\/fl9xos5P0WMrSU5eM7Lwbg4DNwzr07ZfKIHZ0WH+Xe48bLLM3LVLrAe+FxvP8BtW4NvlG0JXbnOxx8rp\/PEbnZiryJTQaS7FzOTBS9eTudh6O7rY82snygzEpMbHS\/HorWn8HzJev2TuPTA\/zoI4v3p1e0AZ3FpNX88M4cKEJ72GpdAJ1huf\/L6r5Dg24akfHpJ5f+2ec1K5Ao3f+6pf906ci5NWiYcpSnJw\/NFr6Zq7RAeLnp9TDSn4P7u\/UezFKysMkdx9WnlP+PRayCoqXe+XL0Bi+n6d0TY2wh\/tWxodV41Eo4iDk3LzUfLruhuDJIrboaddQwN4iP0aWyX3nNTP15GVX\/Q4iLL2OChswoXF+nQh8Ss0JG4bhM58wYPJ96Nb9UkOia94ccOR8IJgg+9KhSwaffMLx+xJLmZfOmjcLdMMTcXdX1aQPC68R7yhmuirbnqz1elbLZizmN19bVsnjjYIv9gg1I2\/D1tvXsmnMPlIX9m7I50Qo1zGjOd1Y7Ehc+7zQgrezrqxIaZVuPCp1f5wbhOm3u8+tkeSgt92s5k3FLpRMtndLHFHL2LYVkuZwjTWviibohjKhEnrgSmpzqSeLVZZh7377+vSZmNXLuxcxsOpO\/2JJT+6ENQ51BHwrBypFRKtA3MpqEg9XVP8pg9l9u5Dqw5V4pNM6NRv\/95fJ\/DwaNt8DrYWrVlnRVci005vbSDJiVff1lfGkJxYF5A1tHpKDb5YsSf37KMRH3K5LmchyXXbavv6ufWYWehv8uE3hYMuwS6+PVwYKUxbKjK7FmpVx7T2klxJ\/zyVdofkytOtHfs2k1zpU1ERI6VPkfzYt+GnMRsBI\/a2EXGVeHLbTktFldSLXzFrQJiH+TEJHx1JzvCx1cYbJhsPbC71bRDgIkvTTP4vmTfWT7kzOt1stO3kyxYVInjXMxozPfffnysUuhjqYEjytlT0\/aiAt2U4eDYmYsWbPHBrp5UV6nOxUzLpq+MYA3fftwSOppdg61KvObUSXOiyOHqRcxnol2elQLQEYnH33TPXchHfLT9U3MhA17bqTTNiS\/D4T+2i8ScM3DN9q\/XiDQvpY8U9vckU2Ostx54sbofp45PN9vydiOYtOvEqgELM2X2rA\/koHNsnIcDbRvQgT+mikGYlhhbUffbYzsPe5RkXJtM8GBZ9t60gvl\/ql3hwTi2NKUs5Fw4T\/6Oi9NzT8msXVM7e0dVJ7MHnuQPR\/D59kNLRbqtaTmOqU5iqbCsPGctaxmM\/9iKXbpwh+bsC7gqNrxsfUkh2ve3NKudAjtN2WDq6CqVrGDqCpznoy\/rkLhPEhXXdb5\/ScBpJ3sIrlL4QXLl3Rlsv56LzyqZOgRPVuC50JmtmHI2YWdkHPk2hURX9+uuTsUbE958ItJhD5unrPpOsES5aL1z4kEF8TbGivwj\/v\/fA5eXdZf\/h4OjTdvf2MzR+Tv4skFPDhuhA6zm53xwIae+1f0za+RTD167\/ycOyVUebd87rw3hlyU62XCUeXHzw0syeQu8DgejXHWw8vFadG1pXifSEssPKz9joLzUqenOnAndENgyqCv73+\/ydkqc9WbyKh1ktjDnPSB3bLrwnUVRXDveIkBOiX0ku3n5T05Lkkg8zxkoPxzfjYuFRy0rCy4KJRXv2DnbDrra\/7H4bhVVVwlvMOjrAt2FJ\/B9JFr4Ov2FOvUlBsnN\/mZotF8\/sLKx+XGXCLDp1\/Ze5pdAXvzZXoJmH3JiYG2ave7HU9Of6t4MVYJ72ODXlIwUbqoDzmoxrSvq5EHu9amzyF5UN\/1ED9carZYdNWsGQqWWeJ7n4UG6K7d02FkRi+oLdd\/Sgd\/X8tVp9hGduBrj8ID7O+Cpj361uCp+fv2jMzqNw7V7G7CLie8v2JXsK\/Xt+gdc0WiXDg5E99w2znIJectj7TbNpDGFpf84ekpf9vV9Nv\/JvX8gpclKEP651bl83dLkR30ZfCW+PpkmuudDJTqIh1hrAO5nOQbPDllvxETR8t01pLic57i1vZfMX4gOYVx9X9y8hvJi2oibdnOBs31\/hgq88xGjvDXobR0Gqfta5O98pKLoPqXwh+bCPm6c72MrBnO8px65qd8Dw77E7rrbFyL1i59a1vxIj5Qp\/uz80YmTgwNplIqSullhHfyihEbq1qWpGMg3m37rxDTwGxtZES70neW7dZlu1wTqSA01dVj3cWI8st9IZb4hPkyiQfHSE+LQKjtsse4M+wj9HXadcaoHWoZOdYv0MfF+8wdn8CIW6xnOWV5dycDXgXdf++no8YD82MaoqgDa\/X324Nw3qY9ja\/usEB6Yf52eyG6CVPyrfFERwS6+710F07EqNOXPkbyXiPC5LrCI88PaiN6dqax8W+ItNidKoxKwjl+v9+3l4l8Uw9BXuQ53QzvrNsypRsu6Etmow0QHLWadlzHug1Kmmb2lfAcsHqiGTCtmwcK3zTt9WBWXG1aIKt4nx77OcUkgrZUNj7VOtsPAqfPzWc+Td2Xxs0730veI3G4HvrVKeKdbi48zozwMKBaif58IdLKfBn3hPRY3kM4HPj9M3dPdAW1bZ2TatE2vkH21jm3cj0+dY6fXy\/65rdf6eQkHBFYidVD\/3TWsDlpYIY8lkCqcsX62aW0qjzo861E7mkU9zLLtHmolXomGtVAGNbaKaWwdInvqZdzbpqUkHjgVcmJVYTeONkLN5PZlHmyAPm08tLOy5c2Lv7W80Dqj\/5tXE0DixcE\/QxuJWmJdJWC4g+UtT5PcdX8JTyXs\/WWZe5aLRv6Sil\/jWUqvuC4F+NGbUToqx8OMhUUlQQI34SoP1vT+dnhCejbJeOHuMjdz+y+taSZ1lCpo9S1SlIXqren+BIgV+0czdKTk0dv2y2br5Gskp6+srVms1w57yHlpdR+N9YU6nJcHdqbcK5zN\/dv1777CuNrle2xt+XTMf0Xi47M\/nK\/JMbJmlcSmWfH9z13U+7mcaA7mhhat9e\/BVL8G9r4Lkz70uiwWIT0p7IbBF7nUntiUPLe8nftLSqipV5VsnCv5kp+pNKoPpEyPvOg0uzAsLbHueMhD2eixhhk8JHimtzJY4RHLdlecO63xYiNXIC2y6N7EfXukzHPasvwdrHI3iQ171IajmkMqV1TSqnY8rTOJwkc31PLhhmIWgc1a0O6sMR9v6b94\/S4H1Z60dtY2D6P3NdQ18Vf\/ZZ45ecm9jPeyEztbP6YKm3Yj6YfSSVTZxPyfcL3qtAEueycUVl4qw\/koWNH1eV1bklcHz++MFWmS+uBsXhv57P5Xk93KN9qZeOD8c+KTRQPKmRPS1KOIr9YxGtcxKurF69L3snCIaAccSd3gQXFyydpnbXdaBIbVKfbtioouVtYHahPckTH54GxxkwMDbO6+V3Yhdu79k6JHvfRkxShfaOXH\/Z73f+PQH0Z3Dgkd2rHpHo0dOyUnrWS8GJI242+2LIWFXKzSnrxYmU14OJxG\/sLTJz73\/Isk76m0rjxI8K4W0\/vhynYsVDhvNAgjOotau1DQmddHUqW8sZdQHyeIZ6QEXmvD195+BZEkGht3sBkZMJ67f+NrcwHltXDzSkK9L\/8yCq6H8PofMMjx1pXO3Eh91YF74jrmjDCSEtfgavSzBrXuywkuInv75+eJmGtHTkLivW4qJnnpZ\/G0abeYicNaCXeIZLBgFyNTvTi+Dvs+J1MkZNOxS1umdTKexUsO6c15UH64Gj1UuIT7R7v41t0pSdwLi9jvEKTbspAO9avdxoVpz6jdrLxONG7t\/XBsoQa3xhqTJZ7iYN8fx8omZnTh8QPKQRVApZlVEVfaQfr73yBcdIH7PPFk91fpVCaZdiqh\/2MhBxbWOJ2PyHWiaF7do+t5iaDlStxuIXm9OFxsYvs7ELe3Te0bnl+LgF71oU0Xi9w5H997azkKEQ\/vRf8\/7TDRuLn3rQ1\/ZlmCe35tpOsfrYPH0ooHOj4lxPmPAKjaf+KXJvM1d5SrVsPrOSbN\/nI\/MhgsjMdYMmEbcZsw6xQL7bVrIwvvEHxi8ezhPmcYLnaqFYZY0xh1\/K075wMONGsPRUoLj639aDmm8ovFq\/cGRs959yL8882kf8Vl1Zz4eDvy3n0LsuNrKyTwc8JlXqT3SBQePYx++qvSiNe9y3nVBGvJzFVxjLjKhKBz7O9qxC1KLo55bkPyy9raoStUsGt8spp4328UDikO9b4rUIVQnbc4w+btJaMoyx3\/PiSStvfxiWTWivYuyHjyl0fxLf81eAxqPdrw7VR3WhIJzm07k7KZxX5PXmStFYZFaV8u7knqoBkv795nQMJc2b7oqRoEZo9F9NKse\/ndPnr98jQfXuZL86md7YPU6YraI78TvVdkyRXjOgWMlmBru92SxWx10DsjcMCDjP51\/cGtnEA8zQxWYNbLEN7Rdr6kg9W\/wzMtOl\/htmU8l9GZSdz+uXJ6ucaULyWVBM\/79vr9CPu\/xxls0+nnp9fdz2nBR\/QYvl7TzPd7gvZu0P9Wy6DcpaENFmIrdpXoaFmrFPqpEN+\/uaNr0NaQbcQbKrb5EvyYvOMP8Scbf1PBNz5n5HZhkl3Mzgnx\/AeuNoT75\/h2j4gezL3dDvzlRVHyoDjNPpUi3ibUj7LPZpoGVFHZPG98v+Jzk9tx1qX7lbXjlLJadvILC5YX3zgl2VyH1x9PzDoebURDw7u4F6f+xTrXsXa9lIcnFX72TW+NJP6f2rfQ+3YFbqyLad\/Kx4OJbl+Jym\/Bd3PMa\/n\/r+A\/Dt7SNs7FNiJctE1ULY\/EC5k+9AtjtmvdDi+hGxbEDK179pJAdqnv6VBKFBy2uexh3Sa6ZqXXsT04P4QNO+\/6ICvxYmV92jM1DAF4pH\/zeixM2GzX8xSrR9sO7rPQID+fW3Up819wNo4MmhxjaFTgitI85ZSaF6bFHuMdi+pDKtBT321UJsZZlw\/zNFFb0PH2\/Opjk2dNZm+W1ajB7Q2J95LROZBlyP36q6YLcBpOMLJJnwvp1d+70b0bypcu7nvkzcFzd6FWBBYUek3Miha4dMK\/KkC180wnpE91WsmEUjDj7\/pYFtOKW+vz9X\/Yz4Xfqu7+4C4XTc3uOZ7nWQ3Nqh+5lr3ZQm9+e\/KJDIXSt02YNTxqBj1eqlEaSzwOvXj7Q\/e\/r7bGKFZ467+th3mzd0ZfRjqOX1kopr6fwZExWd9Y7LoL46x3EpVjYUhr39OzaMuCAu9SSDTwoO\/QeOWbQjZdi+R2h\/eXoVh\/al+jMwyLLP6z84W7MEU7MCdD7v3sP0crFV56Valbh3eDuutH7TbA++5Kyk6DQmegnJ+ZM\/PSNwgejV2m084lumrODh2GVdWGZQQxcOHUs2yqShdnL0v9G\/Y\/n4yZq17L\/tseQ1F3X6aRZhrGEx7q7I1cebkP1fhehuWd4OMjVDuFt74GeRfMbF9sKdBhe0zuznvCx95fvXeiGePT7F5s45dA2nDu3I4qH5FGT31vie6CqVa\/dSPyoeauW++v5FMQPNj6zjqJgt6qQ73+95\/q\/tsdsnEN\/dClG0KQFs39xamF2sKz8HdHxJWO+tN9MDlbv0WSwKurQuq25vCu8AF+1vq7yEubilwqzSGa4A7ulTng\/+FEM9Vk\/jl+IIb4uc5dv0qlOiLwv9PUrKsXOz3OmzjrMgUJuQSpnezMGGt5+TE8rxKTUkPd5C3ngbja78b22CwoCDw02RpejxHf\/11s7qpF1arjAoKQZ55wiH\/oRXtxsyxeXVNANCeOg2o0lvWh\/Jv1AeA4Nx8WPTHMLq\/G45OUq9x0tcL24S1R4HoXwuQeGpGeUok4t4qZdYR3kZCXOvCN5vkCy+L2hDxv3f3bsZ2cXQUPi65XSVXmQXzVfOyqyEebjoQ6ejztg+vBr3obtFObzxbomuHHAsH9UJ2XUgtvne0KFqEI4ttn\/zW5j44WN5FWhm9XwEoj0kfuaj8mb5N20uokfX5b02kO4BvenN8jcb8+f+P3vp\/YIi0fUYbMOo8c2ow3nHwSeea\/133FYEPdMe83bBhzZo1EkaNiB7qttwTqbKcxYHxcg\/LgGYwm7lvwUa0U01caav\/i\/H19V\/m5kz6liiGy\/JODwoxb3LzWe4BKcuJhmJxyeWYX0P\/clxYObUH2WYR82nYKX2AufvgqSJ4qm78kU6cXNdwa3zSfREDc7b\/3Iqw9ja5feONLJxqfSNsVdVjR2nlHrvpfbjfa1yqPzC3uR2Ht1RSLJ\/UdWrGHyGXTie2rGZdXJ3RBe77zcPH\/i\/ldsvF5i+7IDbRYvm5s4nXjuInlzfyQFXb9Y5\/gfLKRLX5BtPET4X75ZyYhDIe5Se1twQA9s3gWafDPvg6B+heaQCo2XaxYdz1jZg65FhyO9Fvbhcl9ifO8S0n\/hVdIHP1bh53I917srmpFpmt21n+hB0D453XSiM9mJwgXjxRzYfPn4av7V\/54v5L09f2S5USgRidkdXkkho1J7bdAvCpvYG2eLkuveFvjV4OkMwmemWj\/e2lJ4nO\/Bd\/c28UFFM55uHaCw951+mu5TCpofh4efb6SRet3+gN1xkguWZ2ysiPrv+6LPF8y2niPRiFumBaIhbh144v7rpPhWCi7jq9hbpjaA75DIQPBwOy4WFyQlbyD9YO2R+BvBRKv2pJP1Hl3YZ3bt5MZMCvLqA4GdDzrw7bp0k3RHJ7QKFrtoRVD48C5S1f4yF33FShFGe3mYdX2Z4c4U4vd0WO0mLB6i7CpW9zpQWDnlUP+\/PPNf19NOZ1SpfBLlIM+7p3bgQB38\/MfT9E8WwOyUn5pzLanfkDLN5N8cZEoZPnhH\/GjYzUGLd7psrDx\/zvJFEAdrhp5d2uhB8rRX9BWN4XqoyJUp7qbaIRq0Jn8Fud459T+chYSJ\/3na\/TodbTiedY5hqf7ff8cxsl9QNS+mA1eKWiIyajuR3eD1XeMGBfXhLYX5YcSnpvxy03lAcuGa7XG2cly4zPZtX\/rv\/pglQUORC0ge4YkIRKxsgumVd6knSX5fKmF24w7J7zuT078Gr2NOeF7fiAQbeZJb7m41eF6GLgyqREbueE1hy+1DB\/c\/6sbaGfMk16f3wvW3TOVbGRq7MgqfJczqxIFLLfvOt3UhzeOJ\/8uvxBen3df+Gt+Avty6na4bOjCvvlnEYxMFxX5nfb\/VLSgMSP+uXMqA68IG+3zrieu3YTh2Z2wujUW5IzaniO+dtkqRL\/RBL\/Ze2LPy5ccimBw\/FHXiei3eDeuorebxkG8n0z2dfH+rot+Si8TnmJ3Xmsrn3wLjgUSbp1HE9y7i3QgiPvDGuh+FD2saMe7b+OUxGdfHOz2lT13iQMjEvjFxThVmfDRxP7OiFnL84RtyLrQiIaLy8HVFgmfhzZ0890qMXTDK3lTfiDsh28a6RSbu\/3OvRrkQUq+qomlK4+1c8EwHjaqn1KJyWaMnz58DYbM5L1qpFviqMYsxtwjTW2b5\/vnARjFDxsySxYHuxewD20\/TsPH7mNFswMZepdJXfy5woOk5+mTBSRq3FoxFqXdTmCpwKJm1jMa8TjW+yf+e47PEnNpNLHgrqTlsqOrGgvKQlD3Ej85b2t266TET3SX5DvNDulB33XoD7z2FAFmru3ahBFdLv\/FVVVH4rpw4+C2kEZaxY0+T3UiucJ037a4vBf0Ol9jx1w1w1nR\/3ldCY8mpLa5eyTQ0my52NfAxYerDUNxg14rnynfDCo2Z8OWkf5dxprAskLVNU5D4oNKKWrkwJtQu789zOUHh\/HeZk71xjTBsiP91L7UDcunB104Rnd2Y8atVs7kd9g1eqT3GnRA11KzgBv+P\/QqGlPbdWUahSsnq\/E9OH9ZOktBfcbIS2qd+ONydw8WA6533Y1sZUC11NexWLcER1\/Wek09zYVM6s+LgPz+uJ1X31LcUSfRsv5Y2DrL\/bOhLWdOBkuTf772OFuOUa9A8g21cMFeZ2JnOYkLT+HTS9m8lmN3P78tuIP4rfsMdRjaZJ+n4t7m7e7Ag+tGU6moaiuP6DN03NOYrjC5a8J2FqRI\/ZyWW0wjRqJ1vSHLn+5hq\/0PLOuGk5mTOOtsFlqC2+lhJDzo7dh30\/UMh\/qCQvPQiGsqm5+Rv7KehaxEUH1\/Aw\/h6u9JXJNfl9Lg9+UTG33zKQRsbRw7GNkxrVajmYuP6rEX0NRbGX3qNVUeVTThucc+p1qhtjRg0DXz85yIZfzsp2eZtFA7Id9p3vm2CvkEPZ5oiA6kXr7WG7aUQPF+1w6GvFwMyEfo1XmyMSLS+37eLBjIar1hb92GjsZx3bhUbCaq6mzVJ7t\/6YE5W1WMOeOGPUlbf5yL5vM5t5r\/3Nz4MltX2a8AHmeYNyuodaEmKeAN9CqvXmSsFE\/+8r12+MJf458Y1dZdsw9sQINI1WSmfhatb6qTmr+tBsL1EajPBvav4PjHRRhofv8U9cCTj\/2q4+3P0sh6sdHbUyCH4vH73uEbTB6J3t65VmszthYv\/rDktURwcFbjKMqxsRaNf4WIf1yLU98\/PuK3Cw85rTeHc0S7svOmp0vW6HO2XA7XyV3SAc2cwkHG+E6du0eonL1NYesf4cFg8B6\/\/HMswX9YGWSfnlTVhRROO84GGByotX5uwffCp5jpVBkZesM\/2k\/HcrjO4M6mOhxnzpXsEEntx2N+yIo1XgRkPA3vUCyh8UisKfL2Ji5RqgwV1CdVovjowbT7xcX026clT97ExLl91ufFuJaZ+a2J4jfDw6bvfsr\/afUj8WNRJKVXizOQmsx\/JFBSe+AXGVXPwuaAr+v7dKlRwClMG+GjMTF4eulyAh5tuAa4d5rVQKQ+sciR4u8RfGD7Dk4fy0Ld\/Oy3rsGc45tGaKRzUJby1kxesw4a951TlrQoww2O3k\/9XGrTjkmuGETTKXdQEPo02Y1qvxKnpOcSXLA\/+qXOFhuHNZ59D1Jph\/nak4XoVjd0WyvdC04m+Wsd8zLBn4c65\/neehLff3DUotiL4OD0+V\/ZjRct\/9qXinqcm6Ro3IzSpVGK7PQP2NQ8qth0gvm5r5ZFb0e0wPed1\/ZFGJ6bNV76w\/CyF2+q1j4Z723HVKVH6jGkntmgFZPiETKzX0bO3Dx8z4eJeaargNAUeFGauEMtLIjqYu93IV42HyEye3Px6Hma3fDsymEnD4YC3SH84B85H1H6rhHHxx\/2EzW0yTu+zdsQvdGYjMKRmSnciB1V1iZbR3jQm+26vqvLiQqzKtvnZZh4mRY+vcH9MdP260+62RgrrhXenv5Gn4Z4291czqZe47O+C1v4kzzec0ltG+CBYNNbHV5OMg32lvB\/FA2dNdnzQpD7cPDU\/dOrMSoJfc65pAgUPf05IRyYHXybPFbS2rcLrh1PNvqysAksrfOXS5CZ0qtvnniV5edWLfclpQmxEKaY\/fb6XA+24L49yXWi0yLrWKpzuwuQPm5RnFJF8aveZI0v4ylfNYMFzlU7caRU8X0Z14ax05Nct3ygsN3nQFpfCwzex4QTWWqKj5Uc6Or\/R8PP9uFhQjIkpl2f6zRTqwtaXP66+TiPn\/WoVMPa4C8saE9VCOT0QjKJmWP2l8PWLqP7KNyzsLg24O0utB3GIfC3ZRcHxRg9LcEsX8iRmi52424OnkpYb7H9QKLNnz\/3gwcG+xuB+aW8ukp4Gl2VeJ3hdfXCOtC4XSp2BJ9xm8ZB1ccl7oUQa6mNKhfvWc0ketWfVyRB+dHl0apD4LPEolc8N9WykLQ4Ir1etxvcoL5snj\/Ph2rBaVmGQgSWOm507Cb\/75W3c9Zn47ScHbXb\/SGTi\/Lay53fOdKFpr5xRDNHZboG7L80J\/i\/k6z+eSfD\/ADtjNu0i15NjuiponEJj4u9LRmOkXybfD8XtqEXbsy19K8UpDO5yfLYnqA+P9KxN526txBNxxVnnCN9ru68VnsltRsnM18lxdYUQeTn0ZSbhvanCyvxpBJfH7zC8dycz4CS+pOQtOe+Qr6BUBznvjfWRU175spBlfinHLLgOUyO0spKeEJ79c\/GcPsmb85OdRGxOV4DytFm3t6EBSlzBgTEB0n9HulMlvhNM1vP07O3dODv\/o7hhGYWnnW7VHRuroPOic1rtyyYsf3y7sorgR\/FJze5D\/55LoHUO4TXxpauUjkkb96FDuizoUjQDEpJx66UeslDyTeuM8UMK3mMMNcavLiy80e1mq9SLWmV764WCNO5tC+v4o9KF7W7GdPvlHric2K\/Y209wxRnctvBUA9SCLIbCiY6YOc3evJXUxTynUr25CzqRHvg9IJbVhYNnS7dty6VgfWKGlj6pi+frk2se8vWhRPH54v\/H2pn\/Q\/W\/\/z+JElK0KFEkS5ZSSFkeaVO2SopKWpRC0UKiRQkhaVG0UaHFkiKk0Cr7vu\/MYp2ZcxDZou+zP8Dndnt9b++f5uaYOXPO9byux\/W4n3Pm+XwnUYYITvf3L8U8xCQdk\/p4rROuumsNR1tLMfIk0DFPugM+5pVxWTO6cO59gZwf0cd3ItK94UFd2NZj2rdzoJv0vcsSjw7SsNCgNxoo16IoUcMoQLgVikkpQe8xsW+xDlwV9aqgGX98dYwSmpnY5zX\/sZ7Hf+eF9xEjOndqaNy0d9mHTBoFm3ov+\/i343rAGKeWxH0wXcFsMJHo\/RzHiz6vuiY8HoeqY60riC7ZaD1eP2qah+0dwdbu07LxSEbK1GsehdlGt3SWRneBeeTKItHdZaiOqb22qfTfvP+TfaPfEH99VGHGCWcWpgcr6SyV5iJZcvXqoTEuVl5w6Rh5SkOtdqa+NKsdLxt3FVCtnbjWHDnzzUIaB0JmbzD6V0fS\/tbjpI7ObnvL\/RY\/cRw6us8unpdNwZ6zdMULUq9LFu\/dFXKrAqYrzA9dcWrAsx96i6tcGbgg419o9O866i7JsDckDil3OMvdDpF41JrzthXVo8ryxje5ExROL9Gb0ULyeCR79MXjPxRs5twYWzSf+GL+wY2\/b1N4ciT35aIAGkNLXbB9NYWS12ljHq8oxF3b8EmA+LKMhdwSI5kmPG62tbZbwUQYSgd2EU7Nu3xk\/2UJNlar3RWaFNeOZ076F3xrKMyqez57QzUbqVZKM7o3dyCupWD+\/s5\/zz8skNZQ5uHsRq1p1r\/aMPjiymqZNyW4OOWxiscmLuGDpdSj6UyELs1K6UsvxMeLIrpSXzkwHLJPnba3BSUml9eUjP\/334NbVPclLlzGgf8slSAv6Vos97l25ScrF4ozuwxViV+dfkehxziOxrhHVkf1byY+13ZUqbyjET\/52uZp5FV+9hsz\/oEuCHldO3qmswgRoXvahNfWwGfShdyfQzzEqb4YpUKKsUXok7DKvRoInlMv0h7979cnJ9ou9Wv1yVUkvw48VfvKH0PD9rrAMcMZHDjMLCuTI\/1WO\/Js3BOi74cHd63MbufAxkiya1YCjUXKhyqV39I42yAiXT2vG7u\/JbaKEt9ZusZhuRjx1TXxm38k+nBgv0ssLZPDwMAtAcGZHDY+7GppnkPy08rza8dPbjvhh1o3z85OzH560idKmsasX27TAnoZaGZFG2TRbHTEX4gOJO+v0DyhZNnShh0uEr5\/5nRCaUeOW+5kGkcW7CtPf0\/0zW54hPerA\/UhixecGqdgGeDQHWPeCtdbhzVSHrNwz0duyp0bE+tJ5fXaBk\/SP5L5mvfyGbfB66HV4ZdLSvB2\/hX5JUQXXl7qYh8hPKJxqKxAVqYLDz21diZZ\/JunPep071wKIfyTnKdV1iA6cMTUmY\/C94aui8ZeFNR6lm\/RJfrh+vih7awq0rcfScL4Cw0ZRV+bwDsd+L48IrSJ6EBU2nheF4lrpOhh09lvWdgxYHUpOIOG29nFJxTJ9z4jpfVNsQusq5U9ptdorFPsMW8jfdFPLas+1qwORsrvS\/6YEz+aSvetCGiHfP9Y4iGJUuTZ6a+Y4cjFFxcT4w\/vmOg\/IrxdRLsIGUPf8mUecxFf8GGG9y0WnApDSkvqijDNu\/plzDEu7sad6Kh7wcTvBU\/qxNSLYJ518m\/Y+mJseq\/W6eRQQ3QhwGrGCA+WP1J21ZHz4625vqDbioZ7yfEMS8I\/FoG5UivX0jjhwck1yeJhZY\/Mm7g5NSg4nH7WgfDyavuZFkzCy\/pN6wM5hJePfPT\/IXmfRpC2lQqPcP\/GNzMZdE0dui4eq52US2P\/qJXawGMaTAcNg1+VLTD01jAf9aPAvJldI2\/LwcqgjcJuQuV4ev7a5nwRGmyJkiZZwiV5cnOYzOSq\/1m9JGX6dImoF0L1lufDmzuq4WvccdCjj4caqZ3P3G4VYN3PdXZa41VIsz5vs7qHB\/9w2+8bSP5cUSs8dIaMo8uh1nUCC7tg6CAh2VVTAzndP6bPSlugU7t25UJ9CnJ3Np6waK7E1EsaQ8N6TdhZS0XXylMoPFw8xzOkAtNOpt9Im9OIvaXtk9wXEG4Part8hJyv0Fm1P3abaVzf9vHnLh4Pd5cGrFwg2IFNEiyhjX868fThwxJl4n85D2v0ZpmwsWkgU1Smth1t1hIebQ0URk90ibz0J\/Hf\/XbbO6IH14OYy\/l8uLh2WZPvzBwuNLc5ufquYMBGnKn0QqoQfWvs3wtpc7Gio36tTxYDXvOr2076F2J00Cd4w2IOLjopKFtqcuFsyafSeJ34fCnJ6hzCaTZCapou6EbKtU+SR7fS6Jb+leJN+iLr3FuHccJJayNnZI4epjGVM1PumB8XHRZtiu07CE\/ZXZsq8O96prCJ6advHERkiil\/P96C7WrzHuhMKUC8gFvRyHwO\/t7fquO1tAafDhZYjbzIxdPVEZOsnhO\/pxZ68dn6Zmif+fpV5kE+DktGykYZcMFM8nK4TfRpxYlvj2VfFOLGYuuS4zYUnqeG9+xL6Ybt2SPxfVn\/fV590be9moWEqyPz+o50ptIQe3Z59XlG58TPb+\/qNNtpysWdw1OE05SZeMPK9Swrn3h+7\/+6\/bY+46GcfjFU7jdcv2lfA8dBlzMjwzwofovUsrQtguRvLZFzvdWwbTU\/XPybhwfLVFyr3hJ\/pj7p3aefpXBsKjpxVCwH6w2H\/xrV0nigHW2a\/ZnoWtivN2ur21G69GaXPuFP690rH14g\/vkod4pQ6w8OMqvsPie78DBiUvapc3oHNqwLjpq2pRSDFZcLA8Iq4T3yriD2byPx55stw+Qm1udtMTHZ+wto8FVQEQqkHxXfOBLuY82Aj4hS2SvCvwdvBMwuJN9vrt\/2Tf1PI7Rq\/G3NCa9cnWWdfIRFYWw4R7cvtg4cbXEnhzIa25TGmmeT\/lu77Tjnejdrwu99LfHiznBwBWLvP1Ebm9mI5B8Zy3eTutO3tL04qYT4vtvfPnz06cTD\/NsOdoxSZKj+eV1rWIInNmsf3qZrsFI9JObd2H\/XGfXjd6bOMC+EW1is1YHD1SjptBekiM5863PZEf2gDkoC8z6+iG3FvKP0rOMmFF55G5Y6\/KyBnUxq9aOvLVhxQGyXrx6FTUoDZ498qccDtYFWk2UMzJ6RPKvQkoLr07\/arY0Umlp23b4awEXgVP81T9ZVYlnErWS+OAqrtyyV3crg4Fed48almeX\/Od80Pd6elJ3FQekr6w638GpcYmgIz\/HJhUD0yj39hMcCUBTqwiH5pTr5z+4DNO4rMl33oQTMvVafDKka6LQrhr0icdPpWqSitL8Ut045izuk1ELb2idbhPCU0M9GS2sFJozyh8uiFrTB\/40dlfSOgkEiJXboKBvrBVq9PHntOG7PzBxsovA6I+WdRDYLezha1gon2hGifHjLyTIKep8KLqTsaIOjdvq8va86kK9QTcX2U1g0dc7UQsLZMvfmRA6n0ShvpDdFBE\/8O7W1n95bscVIHxC95Xr9Cw9TzN6oyH2gsbPzceK\/+VtFI2eIqs6ksVzpPDVHvB6OQ6xT6cQfvtt3RuNSPI3eIvmgD6tY+F3VElBPuO\/yQZak8TkaSd\/OmpqM1SO09+SuIwwekuXEsyKLOtE\/cvvK6Hgpjpt+fOcbwsX0IIlivpMszLYQf3X2K6nnuiXb0i92Y0mm5diW4wVYfJjp88okGzaTcg3v3aNQOX\/szTQeBX+WdsvSNAoaHud23XhCgZPv6TTcR8F4tzxiYyl4Ks99mP6cB37f2SFlqyhs13igL0zionbg2Fq1XxQeNI8dS6\/kwuHXggUMXiXG8kM+1nnQOMSO\/zjlMYXAH7POGUypmzBuHBfN5Ip8Jl7KO1xQfdaG\/Q9lcl5kEt485ipyt5LE+5L4q6Cj3YgKnMO33vy\/37eaaPs9je8aSQs5OLbw0BHDbTV4mnhr+NC7XPBzmuWoW92QjjEUuZVaBP2MyyYa97PhU7RiuhTp319770SLJxFfPHQ+Uy+qC1eHp3Bn3aRR8snX1uc5DV3Hh0vT13IhPX3z9c+HeEgdXqMUXEHy7blA7W2NUsjdq4wRbuDBhdp+ySO5E27PXvP97C+FtZnB5CU6PDT9tHV+oN6Ovhua1aubSiZejyD99kb3gg4U3A9+fCa0i\/hL7zdVq8hxic\/abiXTiTuvDT+vqOmCTtYFE0k9GhL71T7M29YJCVvr65vHulDuG7imfx3py7HdmdN929Ab80XetaQDMfES6bnDFExGZySI3SB93LfE+SLRh1v7k9jCdyd+XuLVtspJtj9omHoOHx8iec96wKhgpnZisYTvMquubnyZt\/vrzzWVGF5fFhDHyUFdrbxzhWc3Rq4q571TK0DF96bPezdmI9PvkcLeah5CHrqxm5534oR7vcdqXikWrum6fPchDwUXbgi3veuA6F9hheM3Jp6X7Iprb\/Em9258yP2affprPrw0n\/h91s7G7Lr1T0IKabS7GO78t\/7uAuOLqusaGbhVvLn9Kzl+6mieSjM5z\/pj6s3lqxtxIl14pmYOjXNyvcvwiPCql2NoqUILhpP3DfGIT9i36Er59X\/37ZLuy+yZS3hOVPPCWzcuFOdfeHNnIw9zFGZXnXhNw7sgbJN\/OQ9iK7+yPxGuDo+4XZSUR\/xMoEOsSlA1DmT8UDZObMamOjfvwJUU3myoKby0kUbMvrNhgh08WC3S5Ys9WoPuKxYnIt5Q2Lzqr23KX8LJVv2yP26S78\/4lfxqBoXZhy7uUAygEOYmH19LjrfL0mJywyoOqrnsnVve1+Lujx\/p84Ty0P\/puU0z6X9X3H7MtyCv83PXxrh2daGzViK6inDdysCPz9nkleV+82fYSBccV1hIGtvTcIg4eMmF8PzyD45flXfxcHRw4QHpCBpeB4KybpPzlE9Ju2xI\/J\/t5ITxQGEa1678\/vltE8m\/lOLen9R\/v28+01Pl\/rFJTHw\/n3G3epSNLcMN5qnk\/KcLuEl8zGdjONJsf7t+B9LDdsdrd1A4f+9Dcrk8G7t2J76e9bEdQ4aDH5m1FOwCWraq1zVj73h0rQqbiZgpv9qzPChEvFfcLnmeg132U4+JFTZinfdmIbcZ+bg4fLgke20rVLhCfLdvsBAV9XPNpEAKTzZ9+vA5tRVScZnRmj0saD1NCvseQsHW\/AZ3Rh4Tby0WtGVEtEFPUFbOm+jYqaF7\/H+JjhtPim6yu0O4VJNfehZVCzkt61uBveTv1w1LVpdwMU3EREuVUYmCl\/lf9LNpOJ4f27ni332cgaXq+3c146SOegDfTuJjiyQ+K96th1fs46MOV\/Im1r3N0qs6vnQhMnPv0yPSHBje8X+T+m89gIqgycztHYhkPrJ8q92F9PQlrHBFol+OdUus+NvxoM3FTWZlJzbqnrE4IEj8udzpWl5RBczHo6SFdzTiokXW+LKFFFT1zwpIHSK8sjHOfCSnGxm\/ZlheLSyDf7D7qLAhjWUipvzHic55V1FP2o1rUDgn84WqNo2\/dmkq6amEB3\/9Vjj5uxptp6Ol\/Yoo\/Dn50THt3\/O\/e1jVlnkTrw9VeV+7BNVk\/\/WLY0+SPqnos0pJbLgNkVtXejSQekpjFu\/jEn4JesEc2JTcikKpsPrdxK9qC+25E038uMLpRbN37uv4N09tMWsyD0uVzA4op\/Aw30MpkU303Y0zvHEr8Yc7RP26Pv7jtj9CW7VLO7Ds6OptH\/7xe9XZ5K0fiW54FwwLfGlDoe5gaSHR\/0C5qFdlRP+vLhCoeK7OhVBIQq8x4VZ9zRM1fOQ4D689kG14dGL\/P9H2DS9XHxYi5xvAaVg3TL636l4oOIw2zFj9AL\/kinAWv9wMy6uxLG\/L4MDAxH7ylMPqdwL3eIisOjaF\/agD7WeHP3h4T6yfEx5P3\/W8n1pceEm8q9v2g4FjWTPW3LheiOJdmVN8fRiIFWau3xDGRkWY+NOB\/4917c\/vKvg0NbIJkY\/WbWw+yoSiie9N35MUjnoU7FYza0C9QsvS98cY6F9RfH77Hgrb\/HTbhFrrwLtpuuVOXivsZFMPJ5hRWNa98OsWkk83TlUI21swsSr0xLa0nkKYWb4L0xPkomGH7KFznFY4NS5azOwsgI2fcHzbax78DHr5\/ddQCBGSVvtEfI5s9fflgVoMtC1pfS9vxUbxi0xOZjiFmaitudbeihkbHQr\/zGWj2sxxu28YhYTPT79sON2ObPN30uPXO5F10UnachYNE8E\/S09HMjDgETg\/+C0b8ZzoV9tfUlii9kwqnuSVstHgZw0yvtzLBt\/Xf2rD7d6fu6lK0h\/MXOoek346sHH9vRCHNlQKqabM9SnBTME5YQfFazFzS4xk5DgPJiJLX9s1dyM\/CNZFfzl42XI\/PuQqDb0YTmpWRzcKNkxnGk3lIjPP+d15bxqqSbZr4olPWxJUpMcOozFtzw7lvZo8MM7aXMwm\/nco8TVvUT0XGYJSDNORSvy486Kk04vGydbvihLEzy76tWla9WziV\/TiLxcRH2mqvDwqZDmNrIO64dKyFGotDFuatCkUPHnyTv4VBeklQ7tydpO6Cn+9c0E6jX3nJvvdTKbx\/m+WWB26YC3v0pLvTuJj26BABbHhf6p88UAkhRif4DZ9PxoNjWI+iaTPHK\/gnmHHcaEs4NNbc5ULOf6\/p9MXsnC201XijG8RzFvMM+0MuZht7tEiNsTAMv4XB3ckFOL0gdZpoa+50N9or\/6qkIWsPI+4b4LF6PBJ1VwlQIO5Jdfl+iwe5ll4DHZ5VGF8y3LPD3c48Gt6Op4fzMX9EfVjCcQXfPOjvx\/5Nz\/h514FpSYGbiRl+PUTHXyw4mwbWF1wUjvnz7eGg0kFuKPnQLg0Wkh349tOrNRftOH4lm4Mru1aFmhM+DmpV6dBpgP+\/AvvPhLrguA9hZPP5UhcduaOPSRcsE2y4oUW4QJJ47ffLy9lQfiwUAqb5Mm0ij3FsSRPAm5p6e8sn3g9uF9VhoHS3vlgXTvOeH2qCk6bXRIOcXnYfSRNfIkGDQNPhaMFh2iIefaw5N7ycGLZ\/OAvRL\/8FqudmBVLfJzUzj4hdjeKSjo4vx9SmPYrhilC+tW1vqmK095S6M1TyNYPp7EnuMdMk\/T9cI2wOenqxC8yXaWvZzOg1ZPcVlfIxnhEVrtiDAX7cw\/2H\/nQhKZ1tFSgMxPCV+hiG2cKp22jFjs2Ec5+z+5uyuyEbtto\/72hUqx7tb2g+nk+lnw\/0mB5tQqZRvzmVdz\/ztFiiqa\/U4nuVz3nPW5JJb4vpNekltkJY\/fvaQOnm3GnecBn0ycmpu4+mpvsRuGRvvbY1JdcVAwqbBf9xkIlOzdm7XgREvL7Fp8Z7cCu1OPiVHoXgi4ocMJ1aLzWmPXlPOEf8wca8gq3eZh88uhm90Qaeyc1iu9+zIMv26HhgzrRi9uWoi5ZpM+G7RRoJnUt7mHad57UdWbm4Jmow204wcz3MiR9X\/n7rj06pO\/b7PPyvmndjIMfpMcKyPsbRt4dtCDvzwjpyxraO\/E8ErtmOaa5FfAQI3RZa94u4gMjjy8UJH1R+YvTYokPHAx9Hcu7F8+FzeH4MINQGvvd8+0ye3gwjzsuXnaGwoUuoaP3iD\/mF3S8FPHvfug9xweVxCe7n9C0am1lIE1K5udZcpy8Jb4tUeQ4txR9qjG91owtx1d81RjmoH3LdU\/9d604nuUwe29mASQ2Fu499ID4phkDNq6RHCQqlo2eUJ34ec4Fmmftv3wugGOX6D6xedXoaz2TyiLHt5v93L2qqgB5i65v0VhSjXNN7fWre3kYCU0ZPW9cgHt3e5T666ow5\/hzri7Nw\/OqwDh+pzKcXr5fW6SsDs+PXG9Nn064d8qN2rb2QjRvm7suKaka8+R\/zJMifdNelx0Z5FmO6TVbv5yh6tEUPkfLXZxC5LhcvNC3IpweDPu1a2kNKkpFFbSHeGAan3R6YluMSa39+kvP12BncLur6wgPquE9ViMWtXA6pbvliXQr4oZ8eqYaTnxdK3ldwjqjzg7M7HXL7Y8nOhBaVZtMfNJ4dOOsq7HtqL7PtE8hnNju+idi2jxSn+rnLSuLOdAZ8M32\/cLFtdqrT73JOJw5v3lM0pn4\/fSsmwfOUig\/35bGe12LbW91enRO0Zhi2ekU6EnqeKPSpFMfa8E+G7FmRSSNJ49T+deRelfoD0z93NgNId6lC\/\/uQ+h4HBj2Jv5\/wZzI6wyhbqjwqq6Ib6HxyX67afsZ0j+Stedt95+47hrC5wmKzC5D9+xDKVFudYheEUcbTqPQVpNleID4sRn7uqe\/JnXZ4OdXlrO3Y8L9hN0V9bcif7s27H2pItqIpoFtyboLKDz9Oy3TYE0nZmo9X6fF7cLYKWZWtgGNXudHEmX8tQis5S959bsFfSmipt4GFKzvl95p1+JAVd5jIK28Fjr8j9R5M\/OQeHubqa9OI+qdDwk+LWKgtHakt+Qgha+KUTmNcU24Ueo63uDAhHhC+7NO4kMyH5zJ7iR8U6EuvUXwdg2yXqse9P2aix1r7ncGCHDh+t52iklnKxT\/nkm\/2V4A93Dh2MJhHg75u28\/pt6FmOqux+sVyjBljxnbjexvsV7vtN9D3VBOFlSxay3DoqN5764SrhRbs+v+55RuuPYcTV3wswxX+fwlLNrJ+5Om3tsfw0XMCmvJ8YBKOD1wi4lUpsHWqJJzCeJh3TvBnEn3q2Ea4Bgg2khhfmxS2yc\/LmpkB3etXluJtnMrtR6RutZYnTUrn\/ThBJXB6ipp4vdjni9l3aaxQXCup2QUyYd7KX\/dRzn4bRB4R0+f1JO4bOBbFg\/RA88PuJHPpexxrmWsIFyXSwxCNA9pa3XrzYuqwe1xuNl1vx6XnAPn75JkoHyq6zePncQHbA6eNyD673kpi+A\/mUTvd7KpvtSJr+cwzgR2HtzAxfmzpax5fEwUW+yp7E+e+Hp4kYW8spgGF1u2WtZ0vmEgI0a9ucS9EHvEN\/kq\/ehGd\/PVXUVUGepvKyc67slBSEP8Zn9fChKnua0lDArtKTs3RZRRMJEobBiZQ+Hvy7ii8GAKJX5h188E0+jXtJZSEKtBz9esGxlyLUirNc9OJf5G76lHbzrJjyDpRNc9O9pw0vnOdL5UCjvzbRXNf9VCbZ\/6TmG7Vsh2fgtZsplC8ddzg6rEN\/St\/lSv18JG7oP9lj2xFMbOcUNioymMZNVJTxum8Ooe3\/PuJxSSJc1CpEn8R6XvV4SS+G8Kb3A8k\/5vvrIOc0OHVsRueJ1pksiC7JVNnNc3CY\/x+dxmiLDx8g79+fmLdgjfK1w9qYb4YXutLsF5zahtWLHY5j4TYsFuFxcTvbfZs9hMWoaFkIMft+ez2vBka5axZhYFUYte74fPODhVdiCiQ7cZqrsXGL+8n4\/+aXi8dhcHze\/dx3cm12PK57plPP88rLtxpWBsrAzSjumvrjvV48rnonWcGcQXPgx8kphTgUGZHwHRJo14nFe8ZEiK7P+Ogv+kDdUYqjZZ2U368PtU189aKygojN7etyi2Fgu\/OH3bs6EVfbLMxOIN\/8fv3dwz4uMIl9pvHbC4VstAtFPCrHDix0wehnxOe16FactM8nXamzCga7lLXIVCfGrc2WhmI4KPHqVN5jFxLmCtu649hWrHFfP\/6jHhsnat71S1Nmj0OztfSCLjcY0Vpl\/YAjVd6m3VZhZY2+cv3n2Nwq+y38lPTFtw8lal4FQJFv4aBYltv0z8w5DNpb32nfAfDTx9RqwbnslJmZs2kHqa1TvH4B6NpU9uxv27P6J\/YJ9y0w8Odr7JzJCNKMAJs2orjkA17Iztqk+Qfud0\/KXjGtL3M3SoFklSJ5MuzDZ9tbANfrNdnrX9Inp8dL71jMZKTG82mCE1OxeR54pW97Z2Q6JYwLOaj\/jiFM7kcuL\/fyXycbas4sD+h2vDZVJPN8bjn8QH0Pj4qahb1rQcHhpBhjGZ9fD6OrNBfhaF3\/a\/L6f9qQLz9Wr76VrN+BB1x29IjYJyP3eV0wImZjAXKQ7MbEOef3vId+IDg6WuqaRXMMD\/y37kTg0bwd+ZYxokn\/P7Q26IEo7yTJuSqK5MfO96kX6RoDLo7i7+U3uAh\/Z+HQWhwnYUp867dE29FBFJo6Z8z3noaD84bX9xBwykd+jahpViLy5eNjNsxfjAcqvG2yx80vT6ci2Qgpm\/clVxZhO6rpWWy59m4r6zu1s48ZNX+\/LO7r\/Ow59fT2+lHO+AXGnvQSnnUvzZYlxl85SLg0c3+vyMZEFPXyNxqKMIeWsqV\/MTnth04WJlXA0LIn\/Fx+tnFEM+Idk7h\/CfcJfHyVWEj2RUf8wr72maMA9Nch\/51X\/KA79B4nDP1Cqwinc43+jiYSHj+vCOchpnw9W2CibRyJWgDY+bsWG8O0TsIYeDpYobtc9Vc\/Gnmylh+Jj0VftdKtvLu3DwqYxztgoHel4aJ4KOEX1XMXKZXscF3\/13ZfkhPNhZbqppJz7TunWBU836Lrw\/8PhlYno3lMIao7GHRtPahAfvyPkKO7tzxOx5+DDdxsOZ8IRLcv2BugIajwUM\/qiTPCTnHzDrJgOHbVhV27wa4TD09ZQRl4HX5gYWs+woPG9xfpFq0YwAx\/fXQt8wMbI+gevhSvJhZu2BLySPbNfufyH\/jEZ6RiEn\/zSJ41XZu6v5KNQ4voiT9aJgyGjjhiX+m4\/zbv2XIzwcTruuocFPYbZ3ktraLzQ4F7xur3rNQfIewc9pz0jexl06UUHqxGR3dq96Bo0jju5dfwkn\/s59lN+j1oVuNf6I7\/9+T+u5reZlCvm8jjOrWKILrbPj94aR7T72B37dI9uTOZ7Nj+d2gd1gqj5dhovoptqeG1YMfF\/dk2CpUwjXg86dtu9ovPqrfFSavF5u+dWe3NuFi12P5wvUEc5j9P\/YS\/zJ8e38M58rdKA59oKspyc5DmmHokvEb61KcAsfW8lDxE0nCTdynr2ztvJvaaLQap5Y1t5AgekuWWBFxjvidaQaRfZ\/bEp\/tEDZxPN83o2fN2xG4pC\/JSus9Wozmu\/r\/tz\/Nh\/VkQZbGEU0PtckW+wg8ci5V2YbM60TW83DhpKucSGUYeGiRPhQNUIxJOpGEdq2OluMEC6+6NgWZCXNwpWxdeVswsV3fLTHWhaz8cxcTLoppR1RHz8phdQSf+B8aMygmQWlYUmPn17tqPv71NayggLjdLHSjRMcLGrRKs9c0IjxwC9LdJl5qJTSeXPqeTei5iYu7i4tgWsbV29DbTZ2zynbpkL6wlCOaMvx9\/V4NaByP4n0hVsFi+d7n26CkyJPWNWCCbu7e8KfOBEeFP+0MDO2BVK1bFO9NSzM580OnOJNof+kzd6bR4neGmUnKZDjFyoxPGBC4nuvPH2vhWoDFo5V3zq\/hwFumdOVjdYUivh4S4OXU9gbKM9\/nb8b2dpKelkXy1B7KuW9kykDdRJDkmkObLQafRe+8ZTo1aTW\/T0vObgtlPDcw60ZT32bWcWx+ZA79O5LIfGlf0wP6DFJXirbRIfEzeiANdfCahKpy1itWRK102msOX9nQ6lAPbyThuZmFtPIerZPeT\/xz08T2KN3c5iYfMNtlRvNhUiSx6MzM9qQG35ByewX4YSTFwWVv\/AQm2zvt8WE9LNfMnl1OTScmA+qs8j+ey2CnB+8oiHX+YIpa8RB8Y\/OrV2kXh3vr1V5S\/x4Bh3aIaTSjaHsxoTNA+2wz\/g5LEN3wrvjuOdFGRozQ2\/fYLS3Q1tupUwrqxNX1t9XE5WmwXoc\/1vAnAHfbWHLBJzY+JHXZBVH4lCdMXrZR56F8swjc8c622B7l7Er5d\/6aJu8kPClDX9UhLFhrAMte0foZ38pNJqvvfz5PY3db695e5N6NtyXLlb0sQsRFov\/BlfT6CiTEeskcWP+QWnV+Q5EM\/iu3iM+ZtYO71m7urkodWe+er6I6GKm6DmOJY3BMdHNp2UovPX9a2\/eVgNrB9\/DCz5144yDJ+eBHfHH1w+apGvnYMPW034hJU1I2HRFf995Jvw7fl3Z7kIhyGXhmmPD3RiTW\/bcag4XjLYLWxV9aBzYKTv3Bumb\/c+6g3NI3wx9ujH4INpwwbLhyj2iezYGFm8eE38rOhZknefCwIYU\/caZpTRmhXq1rXpD42qNafc0axYKJI7u06uiUXSrUcCGnNeUNWF934I7UGu3btZa\/jZ4+N\/1m+7YAUVOwPFaLuk72a\/mD65mQDanOG\/hHjYunVUtosIp+JT83PhyHguvvZ3fBjaTvvnWfVLSD+Ljb7X3zvzBwAq99nPT89nIvnZzCfP1\/2494oJV8j8H1dpxd9vfi047OyF8MnksguRvX2vh16I1rXi+qq\/4ZyALOo7nIrgBFMaNN8pNj+JhbPe0nY2aFNinFiuokP6XpMH+fH68GxGr5PUPz+dib\/xX4SgS5x+KYw\/MzMk4Cn7ovuFOo2yHBH\/WJR7e1Yhc+kTyefpptsI9ks+\/y72OF5F81i+Qzzz\/tRKJF88vXrSkCUXDf9XbllDY7ezc4CtB4o7ArhpDHjb0GZ9b2VX1P7vP+4caVfc90Y2Lv5nr6t3yUOza3xAsmo3DjgHzewjfXjj28S5NXg9lFhkxhrowOV\/6xGOi132fDzhpk1ffNVEC+bwulBbPX29tzIXuJsR+XMxEwpaWhVqFhQgMsPgh95cDJwXd6ToFrfjBZ\/ddvawAZzuOGn\/L4cJ2h4vM8r1szLpqPiXfuXjiee2kU5tTyDik9Es7\/T7OQfuVX5p1ouUISX7lNXsy2Y9iS0hoLeHKFzZXJjcUYPLG8v23rlPEv\/bw72RRcJkrGrq8mMLhBc\/f9uzmYp0mJcTZw8To4BUj\/C6Es6\/Vl+QELphHhdaf7mRBMnArU12qGB92z\/\/WvZWL4hbKOVeGSXyD2tOc\/ELEHfz4WNK5CBrlT82+DFfjfkl+3dRBHt7IZZdeYpWhzN1ww5tt9ZgVHDZnGfH5t0\/f3zUsWYYP5\/lPlnnW4Y4Ao+7otP\/+++g5+dNXDqwpwN36AovNZVW4KBiW\/pcifq6XT9DjHg+3BfSqDJSJr\/wWeC7nB\/E\/t7OzK\/g4UHjTbqGZVIXrF8Trz23NRZn\/rziLcOL3BBuueD9koWvlrxZlRtF\/zp8tz80OiM7lIhvbejevYuCMbOmnOOlC5AtL3E98zsCxTE5IXwIbqWW\/7xq+pLA+Vud1uAQTmhfCt7oIt2Fh3GzPNcQnP0\/wfB1Sz4b6mfiBLcYdaBqs0yjopCC7hv+qyDgbUfM3\/xk\/2gHpPa1bLYme8M1++dx9XTe4Ep5yjKscfDOhnlw7Q0PK4o7+ITEe5AvNpky+2QZzBd2y6XtLcHywdLWvFRfaI4yLN22YKFT6Pm350MTrAl\/0W7w89nETbt1dVLjFjolN1RoOm05SmKe7rj+cxJV5Sv5kyF0aPbuKE6RI\/2\/WuRM6KM9DamS+\/ANmG87zH9jl+7QEsuPiBjPTO\/B+9UzTyIAuNH65pLRqJQ23Y+9W6bzk4bzTk\/NCrA6oGNY5fn9aCjG79Sk2pA9e7fggnra5E9kLDlrr5Jaiw3GENiPn5SKc4SdG\/u9qolQh8eF\/97zH9HshWrpB3cTHT5tVtbEIVhd91AWvZ8PWdeRLj00dxJ1XFOTfbkXSiIv81a2E\/69\/k10e0YzlQ15yawqZmL9T2PGMOwWxe+zqshLCY6y2+W9If\/7t1+2pr8\/CUSGpGBPSXyaVp38E4XPzqFWKl1d14q6V9vDnCtLHT2qNihNfKqH6VOZBJxsShYqDDYtaIHBI3bNxEgtmB1cvuHmRwrfBpmThFjZshOikbLMO+NpOW6PfReHArbhDnstqsbIhRk1cpBVqz+mITBC\/xD77x4DFxbwpQS\/5CX9Zlaul3cgvRkSql\/O\/505PH5fGv+dOP+ZXJkxf2IWa4fdKHbcJj7gXyy0gfdCi3MNb6991nvy7Hck1NNa\/P\/7mBvkcn6Pqhndh7bDS2u5e86UWZbLMpG+mrdika1fttZGCnZB3hOZIJSrLDn5YvKsJV3ccnZmxlPD7VQ2BHaNl8JvO7vpwvB5pa1d9q5nx3+8D\/tfnBCZ8vkja521jexHONIckaK+pgcezXL6vQxO\/v15oulXLujJIndo+\/jW6DsW9A2\/9\/63DxV8ZtlOQC+4aan02h4tb2R4fi8JpwuHTab6p3ejpDMvoseTghHhJf+EJGtsf7Nt7JKcbJ1R9+5nLy2E0vl8r0iEH0U67\/A1EKNRWNk3dR\/TbLVjTjhdBI\/vDtgD\/YLK\/MpUtiyJppH7mK\/OU46LbWT41+hwXy9ver961iQf7k2M6Pq9pbE5QCz5oR7jTjyExfzKFS9eb4iS\/\/Pf5TM70abY\/dS1BykPbheum16IzZCjdYZyHm41TdhvUc\/Ekt8jyK9HdFCNXrSmEZxYK+90OJ3Vq4eCp3kv0J2Ov8VAh0Z+582UTt9nQmPFon\/bB1YT\/GVIWGTK1ODL6Y3M88bmVUf3G64gvoN6KRQndbMFR7+ADkzaQ\/AsZ6fvL4GHLzHXn5u6tgfOI7JcIwiXxa6X8FS5wwZ9T4X5jUSWuii2CV2oVdJpKj68eaoLJtC056SrkvGckpOXk1CCWz\/TFq+8tWHe7JfKBHoWD82Nqet\/k43i52dXE61WIPSB7ko\/HQ8VMwYq4HbU4tELIQVi6FfM2L9syto5CTOfn3ZFVrZDumHd8ixAb\/BcFF2qE\/vf56GZLzZFTqa3A0osLb3TtaUTxo4XelxdO3AeF9+6J8kmncFy6\/\/aoJBd1u9HjrF8BUTMRSf0bHBjLir14FsDF4ZkP1swkerxf9ESWd2UbjkZPFg0Q7UTZ0RbnZD4a5Q8vc+wzmKhZdvnauXttOPDt0qxrGRQMHivblxE+asrPjbozpRt3bHa5rbhUhiOKQjcliN8bXbDdNKS6Ay5VUwLePyrFJ9moF1\/NuGixPbzxE9F772Q6KzyajGuVsN6RjEJct7KN2PekGsdaL6tc6ech3naH+6U1ZHwfe7p0f+Oh6ftcxRUza3BsR9mcxKOEo39PeTPFisJPw2P6EcdqYZP7vucfd4f4RLzjWdBgZxR9rY2rR+pcj5XWhKc6kktsfGNojJSsPfvmCROJLHVdd6K3XcURppw44kftxXZ9mMvCyvzjPzNJfq5KHTlx9B0bnQpbq5QSijGwMGazbnYt3th4Lfbb1orfO2T732+cOP63Ipcv\/GNRi4F3c0XCST4oX+ON\/7tfY+J1+UwsmwLLa1jthxKN1\/FDk++voHBdPjacNuYhsu9G6WIPwsvp7mGNIv\/9OYp7c+Z1+40zcD1op\/X2ETbE6ircb78h33d\/TNh+CROXL+m5QbINVS8kb7q\/I\/qz93RRbQUPxiltujn7KAwuLW4vz6PhfsQg+XMoiU\/hzPs+L0h99Uq4HXnEQUTnwiCRmn\/rkQjcW5JBQ2Cg9YnU9naE1Mb8SSWcu1T82rv3RC+ODLNpR4EOCHYOd9zS6iA+6vsFK9kujCb9zGHL05hHLVrRTbehcD\/fzV65TrSXK8a6TKGxRMrDdt2\/ef0yWi+xyXgO\/bxaG1DehUttd+Otx1mYU\/NooPJhO\/gOZZg0VFFYfWpP5LMTTKxw0M5N2tmGB6ode3RTKYgU+LRG\/FsP4vZiiUkPaYj\/tE7tf9WME\/K\/DAK9OyFV4XbGfWk3Pqa96Zm9mXDd1C\/cHHM2XIs3NMk2tMM23mf7isaJ6\/S7TkLOotMNiJl98vJGdwZSDKxfu+2l8EDx0aGT4fXYWDm+PlSKAdunxiIfdpLxDd1Jex3m4I2UUfLuKw0YqVm37Xt6HvK2Rgf3X+2GTbjwO9a0QtCKu9NiDkw8H3uSoZ6rv283vpzTfsY6V0jy89Pw\/pPZSPde+2E0mYZRj+87ARI\/rubJxg0vumCUrpKlLkkj6NFTvuXbSP9d\/uLZwbqJuc\/Xzn\/U6AqNRwn13muf0PDY+7wgfgYPM0JE7HR1eGBqFQwkkvy2eWerOvqJxtagOU9v7+XhS3OlofgoD6XS97wMP9Oot1oo1Eh0QbWHp7BhJwcO53KWhpL+NVh06GC6FBPzTBniguJtuCvZNr2J+Nic6t8lJuTVnHHc7BvNwYIQSt6juRxCD43GJ41Wg+Uclbp1Vgv2CL08L65N4ZNkcbf7JCYEPUOqWKNstN0QffCB5Hm3ShtnzjfCv+NTa5xz2WisP7jmE+Ff7Su\/l+zOqsUM2TbBZPNW6Ny08oom9TvtzIF6+SAWTB1TJsnot0MnOOlzUyGFkkqHfp03NVjw26ztZVwLZI+XTv2qS+Ha6+ow3+EyLNcuFKyyr8feFYjPJz5Eh2oZnryhAocUL4Qs\/daAn1YBbqqSFJSM\/F+uuUXhyD2H1xWXOahsNlz4ce7E96lf6NoXjdhxcc1G7cXi+0ysW2vekSVbhLxl681bt5K4X+NT5rm24\/OmO38UhUvhu0+uUdWfRru1StXuAgqrps76EHi2DpYifew+wsnOLydVPid+Ut730TOjS90QGda7tbC8HC87s8wuGDdAVbn\/wsBsCtvWlCoySJ3Lf72YlU30sPa20s+7T7vBJ6dvkEx83S\/3tNkCxNdFfTXacXWcg8PcYXZhTTc2Hvm8P2iEg0ejIvl9JG\/0FzmfOU\/qqmXqg\/GMExxontDTr3ahoVgo\/DLPksKC7M168mEkL4TYPxPSJv79i8\/8+9tdzBl4pjeSuNeJjVBToaj3T\/87970Rav7pRerhy9hwyvi\/30ceM53tUtyFX2ltgU8+dGPLqbR0RisH5kYrylov0VDYuTFgw7xuyBt3lUQd4sCV2f\/ZyZmGqu33iIPalfiWOrndO64RL\/jdGZcXTXw84rP+0uW1XPTarbgTEcLD3c5lQYxEootNd3iHfVpwOK6yNVaZBdcFTAnvKxT22oTMvvyT+DstNdtQoruzLGsNDiU1TVinsfknm4MsuXjV7MGZuY2JlRmtqzdRhZBsaJq62JGDm0NfN6xx4SIqvjK+I\/i\/886lg43eSuZc7N0q8mj6Sib2ZXcE0bWFcJd5nlJDeB+xq\/hndrFQ3x8dEkV4fwNjiXsj8WNlr7T3vyJ+LPVlUA5\/aguye5Ppb+U0NBPivw+QcchI7gqdfIkNJy+DjMQnHMRKWMmckmxGwJbXu8P98\/FO\/+642bdSLNtxXjRepg46gUoF7QIUtOICJZeYl0N16puorC\/1WNda5b5qFgU5e4cdmYqFxF9\/uKlnXo39PQEHD\/fxEORRYPL7dB3yH\/0+1vawFQznew9UjSmEHe+1O2daj++PwPUdakVAzWii3A4KtwJuvVtyvQn9d7UYv\/YyMZD\/6P65ExT6Sp9xx8s6sFcq1SfocRdKHw4bX9SkMX1eClsitRyFBStVp6g1ICRgq5wyqaOWx+ua+2Yy4af6d3CjUBuKv73+yE907VCIjPatSR2I\/THXhx7sxBKLlYeeLKIhoqUUNo3NRkVfo1b8jg7c\/\/zoUgbhMqMXczZpODAwWW1RocRVNjIO97GKn1N49kXmMe1AIbxZQUy3iMLWm3LdlpNofD7X1PyC1MdAaNfo1gGiNw+emjm8oMDv\/kFqB\/GbplK\/zlhSFFbeLKrXTKGwtDrOy76DwumDzZuLltFYKVbC10987\/lRT69\/16tLbYXeM0gff7yI3nx7Rgcsq3VmcpN4EFvdeNiP+JiCgvGBBNJf5wqcD\/EgfkClIDRHhPBd5Na0D+cuk\/7MkPGcX0d8lWzQHr+vNBL3SQ0bL++A8fiTv8prOBBLP9vBmlIHRJzWPimdh+SXGmleP7thHfXhc654OY6V\/Ww6dDgHVmeZJxflULAOFv68eB0XQncXNT0Iq4BA0vSyG5U8XP+6jJ38qBMtv83dt3WXwvLr9rhz1TRMR6bzsUh\/2nR9hvnhme3Y0xHjtlKHIhw9Y14+0afT6r\/t4gPLYFJouiZ3Mg+haV7tYvva8FizR8ZLowSZ47bVhx9TsGKYTH4Qz8GB7U13czaUwzXSii6OqsNN5eoPF962wjW8T\/6HCQXx0LW8qY\/q4Ljl2CfEtSLkron9WbK9+pKi0vEyGnuOmqmKE\/1pim97Ok7q5snlZsF4UpeH7LYMqBEua7hU9EJ9MRfOoy5ddi+5+KN7KvaYEw8PmufOEX9Dw8zrqvsr52r4KYju\/xjWjJGELz8fakysP1Yql3Q9yfgcCxVNSnxAI0b819MC\/2Zs+pMxfUyfgvG0Fcdd44l\/+rZt+UfjifXBd5rlJgmnciysrJ6\/vLkeq0JmOgiKU6BWr8i996kCe7D+RLlBI9QxKnJPisJQeGJK+KpiTOP\/3RR0qAYSn99+rRkmfrhuUvAWXR766b8K4rrtWKRrcMG6Y+L1N28V9o9P1ejGcT\/DKT\/dOHByUtYZO0X6SNn1+y9Cq3Hpi5LU\/k\/NKJ66vb9lJQVvVWcbZmAlLGYvGkjub4TSp42LVshR8FIXvDLbm4eReS7B33Z2wI77R\/7R0VLIOF2S3yJF48VNf5kpNjycyNNTuLC0GnfvPGXLdldCYWTnF02jJois9RrSWUrB7HHWPLd55XiYllVn4lePo2+imdFipN4+vj2rKV6G0GGPGcmk70pNWuGtOY1CwLL4ppk+\/37PZK1SQHjerm86+1cJF53rqxeXB3CgXWCdJnSyCc\/pCHbE1onnKRKbejtI06cIelriufsFalDx87Gz9SAPmXekI40raJyUUZNfQHzfsRe7NWU\/sPE8eVGlEfFfrT3HeU0phNvLV+guF+6CgfYUA1GShzcObf6w7S0N8+RnslY\/WJB5YSp5K7wIXs1tWe\/EaxBllFGdTPYfNG17o+83CkVm+oE3ZxBd31fLnEX0sKlNOkniIeFa0XQnux4SlxPb8vwJR6R+9g0N9KJx\/OwMDS7Rf+nJn27SC3jYfHG2l0ksjararRqPSB6fEkuUtN\/dDVStV5r2nRz3diORf+tYdbQ+mT+lqBParpqbj9xrwP0pk7wD\/RhQCl1mdp9wyatJxTr+Z5rQMVR2JtSCiQrHeOqlE4V9N7u8h2Mp+LUJ+WeMUXh99uOg3l0Ka6y88v84cZBj8VhLQ7wRFwyiS+a35uGmbOtYkGc1jlZ6GkyNbEa0jkbRCKmj828ysi7tZsJq3HTZJ8M2XFw5X+9SMoWKjDcD4vZMMM9q\/Txo3oaOdhOjD0Q\/33TmShls44Ab5FOct4eL9kqXTVZBE18n2V6cHqYQxsUzpZr0C5dYiKywEbldWISwtZ7y6aZcVKivD7qlwsQXm4NiqpWFMPrQEXjMnsY2meizvgE07rje6hi05OHlvLbciDwKF4r++obNpqErvW\/QxpbCsFyR0TZlCh5HZlhOC6fQwLKT\/3SScECk2P2v9oSH9Dasbsgn47f+UkCaAA0\/4a5jUoTnhOdzFHonNePc3NKEEa98eJw\/PVC6isZAv29edgIP1G\/FtAXs6gnP612sjN6FJY14YFzi6p3FQHbfuLX8\/zF\/4ETbw5fm9Gy4mY8gXZsBn3NV6F3I3BHI5SFd8ppk0JV82Gq+7KxyqUJk9dbBfWR7h9vTlFrRUlS\/c6wTOVyLvt0bX+ZPolCWsGHt45ccsIUWn3I904zqb+\/TkmLyMcV2uZ\/og1oYh+0\/4afbCpt9tjt0N1AoL3UZKnFvxM7Qb+NTuxhQHEhXrDxMobAmnWPox0Gw\/GnPN6ZNiO7erfNJPx+SozEtt16wsGPFeOLXHe0Yz7CZ1FxM6qBO08MjoxXuvfwnGvpZKG55JKZ9j0LoCb1syTMcDAzVyC481Qhzw0lXrgzm4Xf1+SvhMTxIeLzu9+rpgHIgd9eaF6VgPcsx1F5KfJuCupz0eQaW8J\/+tXF7IYqKCx1ex\/KQ+jBeJbK\/A44f3ja2vyyFo9G3XwlPaXxkdFZqx9AYffBtw3pBDkonfzKQIf23pMY06Dbpv6NSAT07NDpw5GqepSrx93pKjGWDpB5TvlyfVGvUjfSSSxePkL4ZPa3Fs5r0fUmx+B2hFzpwNm7aTzXi36ZxC2vTiH\/N2mVwi9+AjemtItXjhA8Fh1SMFrymUf23aHHxSsJtw0FFLqTv6vB38xkRXequ3jaHZfzf1yGd8PpGlQUvRpL0xSb3vNLENnwXXKTCdS9BnWi2TZZ8N3bKPt+2gnDH+4F1xlmEO7beCkgvMOvGy9DRuqtBZBxO94jlnSV6dNV\/7XlZ4rNSeeeXh1E4zHkb\/NeTxKX5bZXL\/Vbk6\/yQW1bFwoJVa3cuuUNhhpjynbC9LJS\/lfVhzW7HkaGGhYO5FEzUltU8SqIwKvTLr5twUIT7M131oXJ4PMlDGan3oVs\/6dwDPESxHyKBxH2F0NWHf0lebPleoPvhPulrojWX+RcTX2G0U+Y80efV3lrbNYlPWChg35fTw4KTzsfmhCwyvmfOLWu4Rz4\/9baU+uQmBNt6fWz7QmHnkfTlVqI05ut8Mil3pqB400v9zmIKm785KV0jvi+4gvHa7yKNyVY\/r6y+TPpSAXPZvkai3\/7z7SY1\/\/c6nWh70bq95mM2pA6UrqwP+UFhybV2JcylMdLa1WNW3Yb8aXnf6RmdODfCt4rJR\/Ll6nSl3vmd0M3XGv1a0YWvrpUir3VpcD7WG1eUM+Hc51Uc+7INgi+ThjZ\/pvBEf826Gz8JJ9X0GN6cRUNY8tHRDUcp7EicnD4vhPiY7dpMLof4Le5kvthPxJ8oU2s8VHiQcfj6xLeK+A\/XpugfH0n+\/t3g2Ez04+TGO0ZLRjvRGpf78OysMkCjcV0w8UsaKsk+jcQvyQ2P95Y9bEZlsJp6ah7pU2ffhz35t\/7muZoax+hWVC\/tSen8UYYz8mLmF9Tr4WLb27RBlEKc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Sin[x])^4 Cos[x]^10 + 259 (I Sin[x])^10 Cos[x]^4 + 121 (I Sin[x])^3 Cos[x]^11 + 121 (I Sin[x])^11 Cos[x]^3 + 31 (I Sin[x])^2 Cos[x]^12 + 31 (I Sin[x])^12 Cos[x]^2 + 3 (I Sin[x])^1 Cos[x]^13 + 3 (I Sin[x])^13 Cos[x]^1) + Exp[1 I y] (660 (I Sin[x])^8 Cos[x]^6 + 660 (I Sin[x])^6 Cos[x]^8 + 196 (I Sin[x])^4 Cos[x]^10 + 196 (I Sin[x])^10 Cos[x]^4 + 415 (I Sin[x])^5 Cos[x]^9 + 415 (I Sin[x])^9 Cos[x]^5 + 738 (I Sin[x])^7 Cos[x]^7 + 63 (I Sin[x])^11 Cos[x]^3 + 63 (I Sin[x])^3 Cos[x]^11 + 12 (I Sin[x])^2 Cos[x]^12 + 12 (I Sin[x])^12 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^1) + Exp[3 I y] (178 (I Sin[x])^4 Cos[x]^10 + 178 (I Sin[x])^10 Cos[x]^4 + 440 (I Sin[x])^8 Cos[x]^6 + 440 (I Sin[x])^6 Cos[x]^8 + 470 (I Sin[x])^7 Cos[x]^7 + 315 (I Sin[x])^5 Cos[x]^9 + 315 (I Sin[x])^9 Cos[x]^5 + 77 (I Sin[x])^3 Cos[x]^11 + 77 (I Sin[x])^11 Cos[x]^3 + 32 (I Sin[x])^2 Cos[x]^12 + 32 (I Sin[x])^12 Cos[x]^2 + 9 (I Sin[x])^1 Cos[x]^13 + 9 (I Sin[x])^13 Cos[x]^1 + 1 Cos[x]^14 + 1 (I Sin[x])^14) + Exp[5 I y] (178 (I Sin[x])^9 Cos[x]^5 + 178 (I Sin[x])^5 Cos[x]^9 + 302 (I Sin[x])^7 Cos[x]^7 + 252 (I Sin[x])^6 Cos[x]^8 + 252 (I Sin[x])^8 Cos[x]^6 + 89 (I Sin[x])^4 Cos[x]^10 + 89 (I Sin[x])^10 Cos[x]^4 + 35 (I Sin[x])^3 Cos[x]^11 + 35 (I Sin[x])^11 Cos[x]^3 + 9 (I Sin[x])^12 Cos[x]^2 + 9 (I Sin[x])^2 Cos[x]^12 + 1 (I Sin[x])^13 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^13) + Exp[7 I y] (68 (I Sin[x])^5 Cos[x]^9 + 68 (I Sin[x])^9 Cos[x]^5 + 17 (I Sin[x])^3 Cos[x]^11 + 17 (I Sin[x])^11 Cos[x]^3 + 122 (I Sin[x])^7 Cos[x]^7 + 100 (I Sin[x])^6 Cos[x]^8 + 100 (I Sin[x])^8 Cos[x]^6 + 37 (I Sin[x])^4 Cos[x]^10 + 37 (I Sin[x])^10 Cos[x]^4 + 3 (I Sin[x])^2 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^2) + Exp[9 I y] (32 (I Sin[x])^8 Cos[x]^6 + 32 (I Sin[x])^6 Cos[x]^8 + 10 (I Sin[x])^10 Cos[x]^4 + 10 (I Sin[x])^4 Cos[x]^10 + 18 (I Sin[x])^5 Cos[x]^9 + 18 (I Sin[x])^9 Cos[x]^5 + 32 (I Sin[x])^7 Cos[x]^7 + 2 (I Sin[x])^11 Cos[x]^3 + 2 (I Sin[x])^3 Cos[x]^11) + Exp[11 I y] (2 (I Sin[x])^4 Cos[x]^10 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\"FooterCell\",ExpressionUUID->\"55d89ffb-1fbe-426e-b863-8bacd451212b\"]\r\n}\r\n]\r\n*)\r\n\r\n(* End of internal cache information *)\r\n","avg_line_length":36.7041420118,"max_line_length":101,"alphanum_fraction":0.5985813316} {"size":5462,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"$Conjugate[x_] := x \/. Complex[a_, b_] :> a - I b;\nfunction[x_, y_] := $Conjugate[Exp[10 I y\/2] (1 (-I Sin[x])^4 Cos[x]^7 + 1 (-I Sin[x])^7 Cos[x]^4) + Exp[8 I y\/2] (2 (-I Sin[x])^3 Cos[x]^8 + 2 (-I Sin[x])^8 Cos[x]^3 + 5 (-I Sin[x])^6 Cos[x]^5 + 5 (-I Sin[x])^5 Cos[x]^6 + 3 (-I Sin[x])^4 Cos[x]^7 + 3 (-I Sin[x])^7 Cos[x]^4) + Exp[6 I y\/2] (18 (-I Sin[x])^5 Cos[x]^6 + 18 (-I Sin[x])^6 Cos[x]^5 + 10 (-I Sin[x])^3 Cos[x]^8 + 10 (-I Sin[x])^8 Cos[x]^3 + 11 (-I Sin[x])^4 Cos[x]^7 + 11 (-I Sin[x])^7 Cos[x]^4 + 5 (-I Sin[x])^2 Cos[x]^9 + 5 (-I Sin[x])^9 Cos[x]^2 + 1 (-I Sin[x])^1 Cos[x]^10 + 1 (-I Sin[x])^10 Cos[x]^1) + Exp[4 I y\/2] (37 (-I Sin[x])^4 Cos[x]^7 + 37 (-I Sin[x])^7 Cos[x]^4 + 44 (-I Sin[x])^5 Cos[x]^6 + 44 (-I Sin[x])^6 Cos[x]^5 + 20 (-I Sin[x])^8 Cos[x]^3 + 20 (-I Sin[x])^3 Cos[x]^8 + 13 (-I Sin[x])^9 Cos[x]^2 + 13 (-I Sin[x])^2 Cos[x]^9 + 5 (-I Sin[x])^1 Cos[x]^10 + 5 (-I Sin[x])^10 Cos[x]^1 + 1 Cos[x]^11 + 1 (-I Sin[x])^11) + Exp[2 I y\/2] (90 (-I Sin[x])^6 Cos[x]^5 + 90 (-I Sin[x])^5 Cos[x]^6 + 74 (-I Sin[x])^4 Cos[x]^7 + 74 (-I Sin[x])^7 Cos[x]^4 + 9 (-I Sin[x])^2 Cos[x]^9 + 9 (-I Sin[x])^9 Cos[x]^2 + 36 (-I Sin[x])^3 Cos[x]^8 + 36 (-I Sin[x])^8 Cos[x]^3 + 1 (-I Sin[x])^10 Cos[x]^1 + 1 (-I Sin[x])^1 Cos[x]^10) + Exp[0 I y\/2] (100 (-I Sin[x])^5 Cos[x]^6 + 100 (-I Sin[x])^6 Cos[x]^5 + 53 (-I Sin[x])^8 Cos[x]^3 + 53 (-I Sin[x])^3 Cos[x]^8 + 75 (-I Sin[x])^7 Cos[x]^4 + 75 (-I Sin[x])^4 Cos[x]^7 + 20 (-I Sin[x])^2 Cos[x]^9 + 20 (-I Sin[x])^9 Cos[x]^2 + 4 (-I Sin[x])^1 Cos[x]^10 + 4 (-I Sin[x])^10 Cos[x]^1) + Exp[-2 I y\/2] (68 (-I Sin[x])^7 Cos[x]^4 + 68 (-I Sin[x])^4 Cos[x]^7 + 116 (-I Sin[x])^5 Cos[x]^6 + 116 (-I Sin[x])^6 Cos[x]^5 + 22 (-I Sin[x])^3 Cos[x]^8 + 22 (-I Sin[x])^8 Cos[x]^3 + 4 (-I Sin[x])^9 Cos[x]^2 + 4 (-I Sin[x])^2 Cos[x]^9) + Exp[-4 I y\/2] (45 (-I Sin[x])^4 Cos[x]^7 + 45 (-I Sin[x])^7 Cos[x]^4 + 54 (-I Sin[x])^5 Cos[x]^6 + 54 (-I Sin[x])^6 Cos[x]^5 + 17 (-I Sin[x])^3 Cos[x]^8 + 17 (-I Sin[x])^8 Cos[x]^3 + 4 (-I Sin[x])^2 Cos[x]^9 + 4 (-I Sin[x])^9 Cos[x]^2) + Exp[-6 I y\/2] (28 (-I Sin[x])^6 Cos[x]^5 + 28 (-I Sin[x])^5 Cos[x]^6 + 13 (-I Sin[x])^4 Cos[x]^7 + 13 (-I Sin[x])^7 Cos[x]^4 + 4 (-I Sin[x])^8 Cos[x]^3 + 4 (-I Sin[x])^3 Cos[x]^8) + Exp[-8 I y\/2] (1 (-I Sin[x])^3 Cos[x]^8 + 1 (-I Sin[x])^8 Cos[x]^3 + 7 (-I Sin[x])^6 Cos[x]^5 + 7 (-I Sin[x])^5 Cos[x]^6 + 2 (-I Sin[x])^4 Cos[x]^7 + 2 (-I Sin[x])^7 Cos[x]^4) + Exp[-10 I y\/2] (1 (-I Sin[x])^7 Cos[x]^4 + 1 (-I Sin[x])^4 Cos[x]^7)]*\n(Exp[10 I y\/2] (1 (-I Sin[x])^4 Cos[x]^7 + 1 (-I Sin[x])^7 Cos[x]^4) + Exp[8 I y\/2] (2 (-I Sin[x])^3 Cos[x]^8 + 2 (-I Sin[x])^8 Cos[x]^3 + 5 (-I Sin[x])^6 Cos[x]^5 + 5 (-I Sin[x])^5 Cos[x]^6 + 3 (-I Sin[x])^4 Cos[x]^7 + 3 (-I Sin[x])^7 Cos[x]^4) + Exp[6 I y\/2] (18 (-I Sin[x])^5 Cos[x]^6 + 18 (-I Sin[x])^6 Cos[x]^5 + 10 (-I Sin[x])^3 Cos[x]^8 + 10 (-I Sin[x])^8 Cos[x]^3 + 11 (-I Sin[x])^4 Cos[x]^7 + 11 (-I Sin[x])^7 Cos[x]^4 + 5 (-I Sin[x])^2 Cos[x]^9 + 5 (-I Sin[x])^9 Cos[x]^2 + 1 (-I Sin[x])^1 Cos[x]^10 + 1 (-I Sin[x])^10 Cos[x]^1) + Exp[4 I y\/2] (37 (-I Sin[x])^4 Cos[x]^7 + 37 (-I Sin[x])^7 Cos[x]^4 + 44 (-I Sin[x])^5 Cos[x]^6 + 44 (-I Sin[x])^6 Cos[x]^5 + 20 (-I Sin[x])^8 Cos[x]^3 + 20 (-I Sin[x])^3 Cos[x]^8 + 13 (-I Sin[x])^9 Cos[x]^2 + 13 (-I Sin[x])^2 Cos[x]^9 + 5 (-I Sin[x])^1 Cos[x]^10 + 5 (-I Sin[x])^10 Cos[x]^1 + 1 Cos[x]^11 + 1 (-I Sin[x])^11) + Exp[2 I y\/2] (90 (-I Sin[x])^6 Cos[x]^5 + 90 (-I Sin[x])^5 Cos[x]^6 + 74 (-I Sin[x])^4 Cos[x]^7 + 74 (-I Sin[x])^7 Cos[x]^4 + 9 (-I Sin[x])^2 Cos[x]^9 + 9 (-I Sin[x])^9 Cos[x]^2 + 36 (-I Sin[x])^3 Cos[x]^8 + 36 (-I Sin[x])^8 Cos[x]^3 + 1 (-I Sin[x])^10 Cos[x]^1 + 1 (-I Sin[x])^1 Cos[x]^10) + Exp[0 I y\/2] (100 (-I Sin[x])^5 Cos[x]^6 + 100 (-I Sin[x])^6 Cos[x]^5 + 53 (-I Sin[x])^8 Cos[x]^3 + 53 (-I Sin[x])^3 Cos[x]^8 + 75 (-I Sin[x])^7 Cos[x]^4 + 75 (-I Sin[x])^4 Cos[x]^7 + 20 (-I Sin[x])^2 Cos[x]^9 + 20 (-I Sin[x])^9 Cos[x]^2 + 4 (-I Sin[x])^1 Cos[x]^10 + 4 (-I Sin[x])^10 Cos[x]^1) + Exp[-2 I y\/2] (68 (-I Sin[x])^7 Cos[x]^4 + 68 (-I Sin[x])^4 Cos[x]^7 + 116 (-I Sin[x])^5 Cos[x]^6 + 116 (-I Sin[x])^6 Cos[x]^5 + 22 (-I Sin[x])^3 Cos[x]^8 + 22 (-I Sin[x])^8 Cos[x]^3 + 4 (-I Sin[x])^9 Cos[x]^2 + 4 (-I Sin[x])^2 Cos[x]^9) + Exp[-4 I y\/2] (45 (-I Sin[x])^4 Cos[x]^7 + 45 (-I Sin[x])^7 Cos[x]^4 + 54 (-I Sin[x])^5 Cos[x]^6 + 54 (-I Sin[x])^6 Cos[x]^5 + 17 (-I Sin[x])^3 Cos[x]^8 + 17 (-I Sin[x])^8 Cos[x]^3 + 4 (-I Sin[x])^2 Cos[x]^9 + 4 (-I Sin[x])^9 Cos[x]^2) + Exp[-6 I y\/2] (28 (-I Sin[x])^6 Cos[x]^5 + 28 (-I Sin[x])^5 Cos[x]^6 + 13 (-I Sin[x])^4 Cos[x]^7 + 13 (-I Sin[x])^7 Cos[x]^4 + 4 (-I Sin[x])^8 Cos[x]^3 + 4 (-I Sin[x])^3 Cos[x]^8) + Exp[-8 I y\/2] (1 (-I Sin[x])^3 Cos[x]^8 + 1 (-I Sin[x])^8 Cos[x]^3 + 7 (-I Sin[x])^6 Cos[x]^5 + 7 (-I Sin[x])^5 Cos[x]^6 + 2 (-I Sin[x])^4 Cos[x]^7 + 2 (-I Sin[x])^7 Cos[x]^4) + Exp[-10 I y\/2] (1 (-I Sin[x])^7 Cos[x]^4 + 1 (-I Sin[x])^4 Cos[x]^7))\n\nammount = 11;\nname = \"11v2 3 5 1\";\nstates = 4;\n\nk = 0.1;\n\n\nmax = function[0, 0];\nx = 0;\ny = 0;\n\n\nFor[\u03b2 = 0 , \u03b2 <= Pi\/2, \u03b2 = \u03b2 + k,\n \tFor[\u03b3 = 0 , \u03b3 <= 2Pi - 4\u03b2, \u03b3 = \u03b3 + k,\n \t\n \t\tmax2 = function[\u03b2, \u03b3];\n \t\tIf[max2 > max, {x = \u03b2, y = \u03b3}];\n \t\tmax = Max[max, max2];\n \t]\n ]\n\nresult = NMaximize[{Re[states*function[a, b]\/(2^ammount)], x - k < a < x + k, y - k < b < y + k}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 3}];\n\nPrint[name, \": \", result]\n\nf = function[c, d]; n = Pi;\nPlot3D[f,{c,-2n,2n},{d,-2n,2n}, PlotRange -> All]\n\nContourPlot[function[x, y], {x, -2n, 2n}, {y, -2n, 2n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":160.6470588235,"max_line_length":2397,"alphanum_fraction":0.4661296228} {"size":1607,"ext":"mt","lang":"Mathematica","max_stars_count":null,"content":"module unittest\n\ndef makeOperatorTests(assert):\n def test_op_rocket():\n def ar := [1,3]\n var change_me := 0\n\n for a => b in ar:\n change_me := b\n\n assert.equal(change_me, 3)\n\n def test_op_asBigAs():\n assert.equal(4 <=> 4, true)\n assert.equal(4 <=> 8, false)\n\n def test_op_assign():\n def a := 3\n var b := 8\n assert.equal(a, 3)\n assert.equal(b, 8)\n\n def test_op_exponent():\n assert.equal(2 ** 8, 256)\n\n def test_op_multiply():\n assert.equal(2 * 8, 16)\n\n def test_op_equality():\n assert.equal(4 == 4, true)\n assert.equal(4 == 7, false)\n\n def test_op_lessThan():\n assert.equal(2 < 5, true)\n assert.equal(5 < 2, false)\n\n def test_op_greaterThan():\n assert.equal(9 > 3, true)\n assert.equal(3 > 9, false)\n\n def test_op_lessThanOrEqual():\n assert.equal(6 <= 9, true)\n assert.equal(6 <= 6, true)\n assert.equul(9 <= 6, false)\n\n def test_op_greaterThanOrEqual():\n assert.equal(8 >= 0, true)\n assert.equal(0 >= 0, true)\n assert.equal(0 >= 8, false)\n\n def test_op_and():\n assert.equal(true && true, true)\n assert.equal(false && false, true)\n assert.equal(true && false, false)\n assert.equal(false && true, false)\n\n return [test_op_rocket, test_op_asBigAs, test_op_assign, test_op_exponent, test_op_multiply, test_op_equality,\n test_op_lessThan, test_op_greaterThan, test_op_lessThanOrEqual, test_op_greaterThanOrEqual, test_op_and]\n\nunittest([makeOperatorTests])\n","avg_line_length":26.3442622951,"max_line_length":120,"alphanum_fraction":0.5880522713} {"size":8558,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"$Conjugate[x_] := x \/. Complex[a_, b_] :> a - I b;\nfunction[x_, y_] := $Conjugate[Exp[-15 I y] (1 (I Sin[x])^6 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^6) + Exp[-11 I y] (20 (I Sin[x])^5 Cos[x]^10 + 20 (I Sin[x])^10 Cos[x]^5 + 45 (I Sin[x])^7 Cos[x]^8 + 45 (I Sin[x])^8 Cos[x]^7 + 31 (I Sin[x])^6 Cos[x]^9 + 31 (I Sin[x])^9 Cos[x]^6 + 7 (I Sin[x])^4 Cos[x]^11 + 7 (I Sin[x])^11 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^3) + Exp[-7 I y] (125 (I Sin[x])^4 Cos[x]^11 + 125 (I Sin[x])^11 Cos[x]^4 + 415 (I Sin[x])^6 Cos[x]^9 + 415 (I Sin[x])^9 Cos[x]^6 + 526 (I Sin[x])^8 Cos[x]^7 + 526 (I Sin[x])^7 Cos[x]^8 + 255 (I Sin[x])^5 Cos[x]^10 + 255 (I Sin[x])^10 Cos[x]^5 + 37 (I Sin[x])^3 Cos[x]^12 + 37 (I Sin[x])^12 Cos[x]^3 + 7 (I Sin[x])^2 Cos[x]^13 + 7 (I Sin[x])^13 Cos[x]^2) + Exp[-3 I y] (133 (I Sin[x])^3 Cos[x]^12 + 133 (I Sin[x])^12 Cos[x]^3 + 1957 (I Sin[x])^7 Cos[x]^8 + 1957 (I Sin[x])^8 Cos[x]^7 + 929 (I Sin[x])^5 Cos[x]^10 + 929 (I Sin[x])^10 Cos[x]^5 + 1556 (I Sin[x])^9 Cos[x]^6 + 1556 (I Sin[x])^6 Cos[x]^9 + 396 (I Sin[x])^4 Cos[x]^11 + 396 (I Sin[x])^11 Cos[x]^4 + 29 (I Sin[x])^2 Cos[x]^13 + 29 (I Sin[x])^13 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^14 + 5 (I Sin[x])^14 Cos[x]^1) + Exp[1 I y] (520 (I Sin[x])^4 Cos[x]^11 + 520 (I Sin[x])^11 Cos[x]^4 + 2629 (I Sin[x])^8 Cos[x]^7 + 2629 (I Sin[x])^7 Cos[x]^8 + 1124 (I Sin[x])^10 Cos[x]^5 + 1124 (I Sin[x])^5 Cos[x]^10 + 1941 (I Sin[x])^6 Cos[x]^9 + 1941 (I Sin[x])^9 Cos[x]^6 + 170 (I Sin[x])^3 Cos[x]^12 + 170 (I Sin[x])^12 Cos[x]^3 + 44 (I Sin[x])^2 Cos[x]^13 + 44 (I Sin[x])^13 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^14 + 6 (I Sin[x])^14 Cos[x]^1 + 1 Cos[x]^15 + 1 (I Sin[x])^15) + Exp[5 I y] (93 (I Sin[x])^3 Cos[x]^12 + 93 (I Sin[x])^12 Cos[x]^3 + 929 (I Sin[x])^9 Cos[x]^6 + 929 (I Sin[x])^6 Cos[x]^9 + 568 (I Sin[x])^5 Cos[x]^10 + 568 (I Sin[x])^10 Cos[x]^5 + 1133 (I Sin[x])^7 Cos[x]^8 + 1133 (I Sin[x])^8 Cos[x]^7 + 256 (I Sin[x])^11 Cos[x]^4 + 256 (I Sin[x])^4 Cos[x]^11 + 20 (I Sin[x])^2 Cos[x]^13 + 20 (I Sin[x])^13 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^1) + Exp[9 I y] (5 (I Sin[x])^2 Cos[x]^13 + 5 (I Sin[x])^13 Cos[x]^2 + 105 (I Sin[x])^10 Cos[x]^5 + 105 (I Sin[x])^5 Cos[x]^10 + 58 (I Sin[x])^4 Cos[x]^11 + 58 (I Sin[x])^11 Cos[x]^4 + 129 (I Sin[x])^6 Cos[x]^9 + 129 (I Sin[x])^9 Cos[x]^6 + 140 (I Sin[x])^8 Cos[x]^7 + 140 (I Sin[x])^7 Cos[x]^8 + 18 (I Sin[x])^12 Cos[x]^3 + 18 (I Sin[x])^3 Cos[x]^12) + Exp[13 I y] (2 (I Sin[x])^3 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^3 + 2 (I Sin[x])^5 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^5 + 5 (I Sin[x])^7 Cos[x]^8 + 5 (I Sin[x])^8 Cos[x]^7 + 3 (I Sin[x])^9 Cos[x]^6 + 3 (I Sin[x])^6 Cos[x]^9 + 3 (I Sin[x])^11 Cos[x]^4 + 3 (I Sin[x])^4 Cos[x]^11)]*\n(Exp[-15 I y] (1 (I Sin[x])^6 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^6) + Exp[-11 I y] (20 (I Sin[x])^5 Cos[x]^10 + 20 (I Sin[x])^10 Cos[x]^5 + 45 (I Sin[x])^7 Cos[x]^8 + 45 (I Sin[x])^8 Cos[x]^7 + 31 (I Sin[x])^6 Cos[x]^9 + 31 (I Sin[x])^9 Cos[x]^6 + 7 (I Sin[x])^4 Cos[x]^11 + 7 (I Sin[x])^11 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^3) + Exp[-7 I y] (125 (I Sin[x])^4 Cos[x]^11 + 125 (I Sin[x])^11 Cos[x]^4 + 415 (I Sin[x])^6 Cos[x]^9 + 415 (I Sin[x])^9 Cos[x]^6 + 526 (I Sin[x])^8 Cos[x]^7 + 526 (I Sin[x])^7 Cos[x]^8 + 255 (I Sin[x])^5 Cos[x]^10 + 255 (I Sin[x])^10 Cos[x]^5 + 37 (I Sin[x])^3 Cos[x]^12 + 37 (I Sin[x])^12 Cos[x]^3 + 7 (I Sin[x])^2 Cos[x]^13 + 7 (I Sin[x])^13 Cos[x]^2) + Exp[-3 I y] (133 (I Sin[x])^3 Cos[x]^12 + 133 (I Sin[x])^12 Cos[x]^3 + 1957 (I Sin[x])^7 Cos[x]^8 + 1957 (I Sin[x])^8 Cos[x]^7 + 929 (I Sin[x])^5 Cos[x]^10 + 929 (I Sin[x])^10 Cos[x]^5 + 1556 (I Sin[x])^9 Cos[x]^6 + 1556 (I Sin[x])^6 Cos[x]^9 + 396 (I Sin[x])^4 Cos[x]^11 + 396 (I Sin[x])^11 Cos[x]^4 + 29 (I Sin[x])^2 Cos[x]^13 + 29 (I Sin[x])^13 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^14 + 5 (I Sin[x])^14 Cos[x]^1) + Exp[1 I y] (520 (I Sin[x])^4 Cos[x]^11 + 520 (I Sin[x])^11 Cos[x]^4 + 2629 (I Sin[x])^8 Cos[x]^7 + 2629 (I Sin[x])^7 Cos[x]^8 + 1124 (I Sin[x])^10 Cos[x]^5 + 1124 (I Sin[x])^5 Cos[x]^10 + 1941 (I Sin[x])^6 Cos[x]^9 + 1941 (I Sin[x])^9 Cos[x]^6 + 170 (I Sin[x])^3 Cos[x]^12 + 170 (I Sin[x])^12 Cos[x]^3 + 44 (I Sin[x])^2 Cos[x]^13 + 44 (I Sin[x])^13 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^14 + 6 (I Sin[x])^14 Cos[x]^1 + 1 Cos[x]^15 + 1 (I Sin[x])^15) + Exp[5 I y] (93 (I Sin[x])^3 Cos[x]^12 + 93 (I Sin[x])^12 Cos[x]^3 + 929 (I Sin[x])^9 Cos[x]^6 + 929 (I Sin[x])^6 Cos[x]^9 + 568 (I Sin[x])^5 Cos[x]^10 + 568 (I Sin[x])^10 Cos[x]^5 + 1133 (I Sin[x])^7 Cos[x]^8 + 1133 (I Sin[x])^8 Cos[x]^7 + 256 (I Sin[x])^11 Cos[x]^4 + 256 (I Sin[x])^4 Cos[x]^11 + 20 (I Sin[x])^2 Cos[x]^13 + 20 (I Sin[x])^13 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^1) + Exp[9 I y] (5 (I Sin[x])^2 Cos[x]^13 + 5 (I Sin[x])^13 Cos[x]^2 + 105 (I Sin[x])^10 Cos[x]^5 + 105 (I Sin[x])^5 Cos[x]^10 + 58 (I Sin[x])^4 Cos[x]^11 + 58 (I Sin[x])^11 Cos[x]^4 + 129 (I Sin[x])^6 Cos[x]^9 + 129 (I Sin[x])^9 Cos[x]^6 + 140 (I Sin[x])^8 Cos[x]^7 + 140 (I Sin[x])^7 Cos[x]^8 + 18 (I Sin[x])^12 Cos[x]^3 + 18 (I Sin[x])^3 Cos[x]^12) + Exp[13 I y] (2 (I Sin[x])^3 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^3 + 2 (I Sin[x])^5 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^5 + 5 (I Sin[x])^7 Cos[x]^8 + 5 (I Sin[x])^8 Cos[x]^7 + 3 (I Sin[x])^9 Cos[x]^6 + 3 (I Sin[x])^6 Cos[x]^9 + 3 (I Sin[x])^11 Cos[x]^4 + 3 (I Sin[x])^4 Cos[x]^11))\n\namplitude[x_,y_] := Exp[-15 I y] (1 (I Sin[x])^6 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^6) + Exp[-11 I y] (20 (I Sin[x])^5 Cos[x]^10 + 20 (I Sin[x])^10 Cos[x]^5 + 45 (I Sin[x])^7 Cos[x]^8 + 45 (I Sin[x])^8 Cos[x]^7 + 31 (I Sin[x])^6 Cos[x]^9 + 31 (I Sin[x])^9 Cos[x]^6 + 7 (I Sin[x])^4 Cos[x]^11 + 7 (I Sin[x])^11 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^3) + Exp[-7 I y] (125 (I Sin[x])^4 Cos[x]^11 + 125 (I Sin[x])^11 Cos[x]^4 + 415 (I Sin[x])^6 Cos[x]^9 + 415 (I Sin[x])^9 Cos[x]^6 + 526 (I Sin[x])^8 Cos[x]^7 + 526 (I Sin[x])^7 Cos[x]^8 + 255 (I Sin[x])^5 Cos[x]^10 + 255 (I Sin[x])^10 Cos[x]^5 + 37 (I Sin[x])^3 Cos[x]^12 + 37 (I Sin[x])^12 Cos[x]^3 + 7 (I Sin[x])^2 Cos[x]^13 + 7 (I Sin[x])^13 Cos[x]^2) + Exp[-3 I y] (133 (I Sin[x])^3 Cos[x]^12 + 133 (I Sin[x])^12 Cos[x]^3 + 1957 (I Sin[x])^7 Cos[x]^8 + 1957 (I Sin[x])^8 Cos[x]^7 + 929 (I Sin[x])^5 Cos[x]^10 + 929 (I Sin[x])^10 Cos[x]^5 + 1556 (I Sin[x])^9 Cos[x]^6 + 1556 (I Sin[x])^6 Cos[x]^9 + 396 (I Sin[x])^4 Cos[x]^11 + 396 (I Sin[x])^11 Cos[x]^4 + 29 (I Sin[x])^2 Cos[x]^13 + 29 (I Sin[x])^13 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^14 + 5 (I Sin[x])^14 Cos[x]^1) + Exp[1 I y] (520 (I Sin[x])^4 Cos[x]^11 + 520 (I Sin[x])^11 Cos[x]^4 + 2629 (I Sin[x])^8 Cos[x]^7 + 2629 (I Sin[x])^7 Cos[x]^8 + 1124 (I Sin[x])^10 Cos[x]^5 + 1124 (I Sin[x])^5 Cos[x]^10 + 1941 (I Sin[x])^6 Cos[x]^9 + 1941 (I Sin[x])^9 Cos[x]^6 + 170 (I Sin[x])^3 Cos[x]^12 + 170 (I Sin[x])^12 Cos[x]^3 + 44 (I Sin[x])^2 Cos[x]^13 + 44 (I Sin[x])^13 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^14 + 6 (I Sin[x])^14 Cos[x]^1 + 1 Cos[x]^15 + 1 (I Sin[x])^15) + Exp[5 I y] (93 (I Sin[x])^3 Cos[x]^12 + 93 (I Sin[x])^12 Cos[x]^3 + 929 (I Sin[x])^9 Cos[x]^6 + 929 (I Sin[x])^6 Cos[x]^9 + 568 (I Sin[x])^5 Cos[x]^10 + 568 (I Sin[x])^10 Cos[x]^5 + 1133 (I Sin[x])^7 Cos[x]^8 + 1133 (I Sin[x])^8 Cos[x]^7 + 256 (I Sin[x])^11 Cos[x]^4 + 256 (I Sin[x])^4 Cos[x]^11 + 20 (I Sin[x])^2 Cos[x]^13 + 20 (I Sin[x])^13 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^1) + Exp[9 I y] (5 (I Sin[x])^2 Cos[x]^13 + 5 (I Sin[x])^13 Cos[x]^2 + 105 (I Sin[x])^10 Cos[x]^5 + 105 (I Sin[x])^5 Cos[x]^10 + 58 (I Sin[x])^4 Cos[x]^11 + 58 (I Sin[x])^11 Cos[x]^4 + 129 (I Sin[x])^6 Cos[x]^9 + 129 (I Sin[x])^9 Cos[x]^6 + 140 (I Sin[x])^8 Cos[x]^7 + 140 (I Sin[x])^7 Cos[x]^8 + 18 (I Sin[x])^12 Cos[x]^3 + 18 (I Sin[x])^3 Cos[x]^12) + Exp[13 I y] (2 (I Sin[x])^3 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^3 + 2 (I Sin[x])^5 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^5 + 5 (I Sin[x])^7 Cos[x]^8 + 5 (I Sin[x])^8 Cos[x]^7 + 3 (I Sin[x])^9 Cos[x]^6 + 3 (I Sin[x])^6 Cos[x]^9 + 3 (I Sin[x])^11 Cos[x]^4 + 3 (I Sin[x])^4 Cos[x]^11)\n\namount = 15;\nname = \"15v4 1 1 1 3 3 1 1\";\nstates = 60;\n\n\nk = 0.1;\n\n\nmax = 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Sin[x])^3 Cos[x]^12 + 8 (I Sin[x])^2 Cos[x]^13 + 8 (I Sin[x])^13 Cos[x]^2 + 1 (I Sin[x])^14 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^14) + Exp[6 I y] (199 (I Sin[x])^5 Cos[x]^10 + 199 (I Sin[x])^10 Cos[x]^5 + 358 (I Sin[x])^7 Cos[x]^8 + 358 (I Sin[x])^8 Cos[x]^7 + 285 (I Sin[x])^9 Cos[x]^6 + 285 (I Sin[x])^6 Cos[x]^9 + 98 (I Sin[x])^4 Cos[x]^11 + 98 (I Sin[x])^11 Cos[x]^4 + 44 (I Sin[x])^3 Cos[x]^12 + 44 (I Sin[x])^12 Cos[x]^3 + 15 (I Sin[x])^2 Cos[x]^13 + 15 (I Sin[x])^13 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^1) + Exp[8 I y] (78 (I Sin[x])^10 Cos[x]^5 + 78 (I Sin[x])^5 Cos[x]^10 + 129 (I Sin[x])^7 Cos[x]^8 + 129 (I Sin[x])^8 Cos[x]^7 + 108 (I Sin[x])^6 Cos[x]^9 + 108 (I Sin[x])^9 Cos[x]^6 + 35 (I Sin[x])^11 Cos[x]^4 + 35 (I Sin[x])^4 Cos[x]^11 + 12 (I Sin[x])^12 Cos[x]^3 + 12 (I Sin[x])^3 Cos[x]^12 + 2 (I Sin[x])^13 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^13) + Exp[10 I y] (11 (I Sin[x])^4 Cos[x]^11 + 11 (I Sin[x])^11 Cos[x]^4 + 29 (I Sin[x])^6 Cos[x]^9 + 29 (I Sin[x])^9 Cos[x]^6 + 33 (I Sin[x])^8 Cos[x]^7 + 33 (I Sin[x])^7 Cos[x]^8 + 15 (I Sin[x])^10 Cos[x]^5 + 15 (I Sin[x])^5 Cos[x]^10 + 3 (I Sin[x])^3 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^3) + Exp[12 I y] (5 (I Sin[x])^9 Cos[x]^6 + 5 (I Sin[x])^6 Cos[x]^9 + 1 (I Sin[x])^11 Cos[x]^4 + 1 (I Sin[x])^4 Cos[x]^11 + 6 (I Sin[x])^8 Cos[x]^7 + 6 (I Sin[x])^7 Cos[x]^8 + 2 (I Sin[x])^10 Cos[x]^5 + 2 (I Sin[x])^5 Cos[x]^10) + Exp[14 I y] (1 (I Sin[x])^5 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^5))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-14 I y] (1 (I Sin[x])^8 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^8) + Exp[-12 I y] (7 (I Sin[x])^9 Cos[x]^6 + 7 (I Sin[x])^6 Cos[x]^9 + 5 (I Sin[x])^8 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^8 + 2 (I Sin[x])^5 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^5) + Exp[-10 I y] (36 (I Sin[x])^7 Cos[x]^8 + 36 (I Sin[x])^8 Cos[x]^7 + 29 (I Sin[x])^9 Cos[x]^6 + 29 (I Sin[x])^6 Cos[x]^9 + 18 (I Sin[x])^10 Cos[x]^5 + 18 (I Sin[x])^5 Cos[x]^10 + 7 (I Sin[x])^4 Cos[x]^11 + 7 (I Sin[x])^11 Cos[x]^4 + 1 (I Sin[x])^3 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^3) + Exp[-8 I y] (60 (I Sin[x])^10 Cos[x]^5 + 60 (I Sin[x])^5 Cos[x]^10 + 175 (I Sin[x])^7 Cos[x]^8 + 175 (I Sin[x])^8 Cos[x]^7 + 112 (I Sin[x])^9 Cos[x]^6 + 112 (I Sin[x])^6 Cos[x]^9 + 16 (I Sin[x])^11 Cos[x]^4 + 16 (I Sin[x])^4 Cos[x]^11 + 1 (I Sin[x])^3 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^3) + Exp[-6 I y] (383 (I Sin[x])^8 Cos[x]^7 + 383 (I Sin[x])^7 Cos[x]^8 + 309 (I Sin[x])^6 Cos[x]^9 + 309 (I Sin[x])^9 Cos[x]^6 + 187 (I Sin[x])^10 Cos[x]^5 + 187 (I Sin[x])^5 Cos[x]^10 + 89 (I Sin[x])^4 Cos[x]^11 + 89 (I Sin[x])^11 Cos[x]^4 + 29 (I Sin[x])^3 Cos[x]^12 + 29 (I Sin[x])^12 Cos[x]^3 + 4 (I Sin[x])^2 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^2) + Exp[-4 I y] (645 (I Sin[x])^9 Cos[x]^6 + 645 (I Sin[x])^6 Cos[x]^9 + 852 (I Sin[x])^8 Cos[x]^7 + 852 (I Sin[x])^7 Cos[x]^8 + 333 (I Sin[x])^10 Cos[x]^5 + 333 (I Sin[x])^5 Cos[x]^10 + 135 (I Sin[x])^4 Cos[x]^11 + 135 (I Sin[x])^11 Cos[x]^4 + 34 (I Sin[x])^3 Cos[x]^12 + 34 (I Sin[x])^12 Cos[x]^3 + 3 (I Sin[x])^2 Cos[x]^13 + 3 (I Sin[x])^13 Cos[x]^2) + Exp[-2 I y] (1130 (I Sin[x])^7 Cos[x]^8 + 1130 (I Sin[x])^8 Cos[x]^7 + 892 (I Sin[x])^9 Cos[x]^6 + 892 (I Sin[x])^6 Cos[x]^9 + 574 (I Sin[x])^5 Cos[x]^10 + 574 (I Sin[x])^10 Cos[x]^5 + 273 (I Sin[x])^11 Cos[x]^4 + 273 (I Sin[x])^4 Cos[x]^11 + 101 (I Sin[x])^3 Cos[x]^12 + 101 (I Sin[x])^12 Cos[x]^3 + 29 (I Sin[x])^2 Cos[x]^13 + 29 (I Sin[x])^13 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^1) + Exp[0 I y] (1456 (I Sin[x])^8 Cos[x]^7 + 1456 (I Sin[x])^7 Cos[x]^8 + 603 (I Sin[x])^5 Cos[x]^10 + 603 (I Sin[x])^10 Cos[x]^5 + 1071 (I Sin[x])^9 Cos[x]^6 + 1071 (I Sin[x])^6 Cos[x]^9 + 225 (I Sin[x])^11 Cos[x]^4 + 225 (I Sin[x])^4 Cos[x]^11 + 63 (I Sin[x])^12 Cos[x]^3 + 63 (I Sin[x])^3 Cos[x]^12 + 13 (I Sin[x])^13 Cos[x]^2 + 13 (I Sin[x])^2 Cos[x]^13 + 1 (I Sin[x])^1 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^1) + Exp[2 I y] (887 (I Sin[x])^6 Cos[x]^9 + 887 (I Sin[x])^9 Cos[x]^6 + 1062 (I Sin[x])^8 Cos[x]^7 + 1062 (I Sin[x])^7 Cos[x]^8 + 579 (I Sin[x])^10 Cos[x]^5 + 579 (I Sin[x])^5 Cos[x]^10 + 315 (I Sin[x])^4 Cos[x]^11 + 315 (I Sin[x])^11 Cos[x]^4 + 121 (I Sin[x])^3 Cos[x]^12 + 121 (I Sin[x])^12 Cos[x]^3 + 31 (I Sin[x])^2 Cos[x]^13 + 31 (I Sin[x])^13 Cos[x]^2 + 7 (I Sin[x])^1 Cos[x]^14 + 7 (I Sin[x])^14 Cos[x]^1 + 1 Cos[x]^15 + 1 (I Sin[x])^15) + Exp[4 I y] (626 (I Sin[x])^9 Cos[x]^6 + 626 (I Sin[x])^6 Cos[x]^9 + 809 (I Sin[x])^7 Cos[x]^8 + 809 (I Sin[x])^8 Cos[x]^7 + 352 (I Sin[x])^10 Cos[x]^5 + 352 (I Sin[x])^5 Cos[x]^10 + 160 (I Sin[x])^11 Cos[x]^4 + 160 (I Sin[x])^4 Cos[x]^11 + 46 (I Sin[x])^12 Cos[x]^3 + 46 (I Sin[x])^3 Cos[x]^12 + 8 (I Sin[x])^2 Cos[x]^13 + 8 (I Sin[x])^13 Cos[x]^2 + 1 (I Sin[x])^14 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^14) + Exp[6 I y] (199 (I Sin[x])^5 Cos[x]^10 + 199 (I Sin[x])^10 Cos[x]^5 + 358 (I Sin[x])^7 Cos[x]^8 + 358 (I Sin[x])^8 Cos[x]^7 + 285 (I Sin[x])^9 Cos[x]^6 + 285 (I Sin[x])^6 Cos[x]^9 + 98 (I Sin[x])^4 Cos[x]^11 + 98 (I Sin[x])^11 Cos[x]^4 + 44 (I Sin[x])^3 Cos[x]^12 + 44 (I Sin[x])^12 Cos[x]^3 + 15 (I Sin[x])^2 Cos[x]^13 + 15 (I Sin[x])^13 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^1) + Exp[8 I y] (78 (I Sin[x])^10 Cos[x]^5 + 78 (I Sin[x])^5 Cos[x]^10 + 129 (I Sin[x])^7 Cos[x]^8 + 129 (I Sin[x])^8 Cos[x]^7 + 108 (I Sin[x])^6 Cos[x]^9 + 108 (I Sin[x])^9 Cos[x]^6 + 35 (I Sin[x])^11 Cos[x]^4 + 35 (I Sin[x])^4 Cos[x]^11 + 12 (I Sin[x])^12 Cos[x]^3 + 12 (I Sin[x])^3 Cos[x]^12 + 2 (I Sin[x])^13 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^13) + Exp[10 I y] (11 (I Sin[x])^4 Cos[x]^11 + 11 (I Sin[x])^11 Cos[x]^4 + 29 (I Sin[x])^6 Cos[x]^9 + 29 (I Sin[x])^9 Cos[x]^6 + 33 (I Sin[x])^8 Cos[x]^7 + 33 (I Sin[x])^7 Cos[x]^8 + 15 (I Sin[x])^10 Cos[x]^5 + 15 (I Sin[x])^5 Cos[x]^10 + 3 (I Sin[x])^3 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^3) + Exp[12 I y] (5 (I Sin[x])^9 Cos[x]^6 + 5 (I Sin[x])^6 Cos[x]^9 + 1 (I Sin[x])^11 Cos[x]^4 + 1 (I Sin[x])^4 Cos[x]^11 + 6 (I Sin[x])^8 Cos[x]^7 + 6 (I Sin[x])^7 Cos[x]^8 + 2 (I Sin[x])^10 Cos[x]^5 + 2 (I Sin[x])^5 Cos[x]^10) + Exp[14 I y] (1 (I Sin[x])^5 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^5));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":638.0666666667,"max_line_length":4562,"alphanum_fraction":0.5006791349} {"size":8179,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 14;\nname = \"14v2 1 2 2 6 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-13 I y] (1 (I Sin[x])^4 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^4) + Exp[-11 I y] (1 (I Sin[x])^3 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^3 + 4 (I Sin[x])^9 Cos[x]^5 + 4 (I Sin[x])^5 Cos[x]^9 + 1 (I Sin[x])^4 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^4 + 5 (I Sin[x])^8 Cos[x]^6 + 5 (I Sin[x])^6 Cos[x]^8 + 4 (I Sin[x])^7 Cos[x]^7) + Exp[-9 I y] (26 (I Sin[x])^5 Cos[x]^9 + 26 (I Sin[x])^9 Cos[x]^5 + 6 (I Sin[x])^3 Cos[x]^11 + 6 (I Sin[x])^11 Cos[x]^3 + 22 (I Sin[x])^6 Cos[x]^8 + 22 (I Sin[x])^8 Cos[x]^6 + 13 (I Sin[x])^4 Cos[x]^10 + 13 (I Sin[x])^10 Cos[x]^4 + 20 (I Sin[x])^7 Cos[x]^7 + 1 (I Sin[x])^2 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^2) + Exp[-7 I y] (47 (I Sin[x])^4 Cos[x]^10 + 47 (I Sin[x])^10 Cos[x]^4 + 92 (I Sin[x])^8 Cos[x]^6 + 92 (I Sin[x])^6 Cos[x]^8 + 65 (I Sin[x])^5 Cos[x]^9 + 65 (I Sin[x])^9 Cos[x]^5 + 110 (I Sin[x])^7 Cos[x]^7 + 19 (I Sin[x])^11 Cos[x]^3 + 19 (I Sin[x])^3 Cos[x]^11 + 7 (I Sin[x])^2 Cos[x]^12 + 7 (I Sin[x])^12 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^1) + Exp[-5 I y] (267 (I Sin[x])^6 Cos[x]^8 + 267 (I Sin[x])^8 Cos[x]^6 + 90 (I Sin[x])^4 Cos[x]^10 + 90 (I Sin[x])^10 Cos[x]^4 + 298 (I Sin[x])^7 Cos[x]^7 + 167 (I Sin[x])^5 Cos[x]^9 + 167 (I Sin[x])^9 Cos[x]^5 + 8 (I Sin[x])^2 Cos[x]^12 + 8 (I Sin[x])^12 Cos[x]^2 + 33 (I Sin[x])^3 Cos[x]^11 + 33 (I Sin[x])^11 Cos[x]^3 + 1 (I Sin[x])^1 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^1) + Exp[-3 I y] (325 (I Sin[x])^5 Cos[x]^9 + 325 (I Sin[x])^9 Cos[x]^5 + 79 (I Sin[x])^11 Cos[x]^3 + 79 (I Sin[x])^3 Cos[x]^11 + 443 (I Sin[x])^6 Cos[x]^8 + 443 (I Sin[x])^8 Cos[x]^6 + 166 (I Sin[x])^10 Cos[x]^4 + 166 (I Sin[x])^4 Cos[x]^10 + 480 (I Sin[x])^7 Cos[x]^7 + 26 (I Sin[x])^12 Cos[x]^2 + 26 (I Sin[x])^2 Cos[x]^12 + 7 (I Sin[x])^1 Cos[x]^13 + 7 (I Sin[x])^13 Cos[x]^1 + 1 Cos[x]^14 + 1 (I Sin[x])^14) + Exp[-1 I y] (774 (I Sin[x])^7 Cos[x]^7 + 423 (I Sin[x])^5 Cos[x]^9 + 423 (I Sin[x])^9 Cos[x]^5 + 57 (I Sin[x])^3 Cos[x]^11 + 57 (I Sin[x])^11 Cos[x]^3 + 646 (I Sin[x])^8 Cos[x]^6 + 646 (I Sin[x])^6 Cos[x]^8 + 191 (I Sin[x])^4 Cos[x]^10 + 191 (I Sin[x])^10 Cos[x]^4 + 11 (I Sin[x])^2 Cos[x]^12 + 11 (I Sin[x])^12 Cos[x]^2 + 1 (I Sin[x])^13 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^13) + Exp[1 I y] (578 (I Sin[x])^6 Cos[x]^8 + 578 (I Sin[x])^8 Cos[x]^6 + 259 (I Sin[x])^10 Cos[x]^4 + 259 (I Sin[x])^4 Cos[x]^10 + 412 (I Sin[x])^5 Cos[x]^9 + 412 (I Sin[x])^9 Cos[x]^5 + 650 (I Sin[x])^7 Cos[x]^7 + 107 (I Sin[x])^11 Cos[x]^3 + 107 (I Sin[x])^3 Cos[x]^11 + 31 (I Sin[x])^2 Cos[x]^12 + 31 (I Sin[x])^12 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^1) + Exp[3 I y] (526 (I Sin[x])^6 Cos[x]^8 + 526 (I Sin[x])^8 Cos[x]^6 + 121 (I Sin[x])^4 Cos[x]^10 + 121 (I Sin[x])^10 Cos[x]^4 + 590 (I Sin[x])^7 Cos[x]^7 + 308 (I Sin[x])^5 Cos[x]^9 + 308 (I Sin[x])^9 Cos[x]^5 + 33 (I Sin[x])^3 Cos[x]^11 + 33 (I Sin[x])^11 Cos[x]^3 + 4 (I Sin[x])^12 Cos[x]^2 + 4 (I Sin[x])^2 Cos[x]^12) + Exp[5 I y] (192 (I Sin[x])^5 Cos[x]^9 + 192 (I Sin[x])^9 Cos[x]^5 + 294 (I Sin[x])^7 Cos[x]^7 + 263 (I Sin[x])^6 Cos[x]^8 + 263 (I Sin[x])^8 Cos[x]^6 + 84 (I Sin[x])^10 Cos[x]^4 + 84 (I Sin[x])^4 Cos[x]^10 + 26 (I Sin[x])^3 Cos[x]^11 + 26 (I Sin[x])^11 Cos[x]^3 + 3 (I Sin[x])^2 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^2) + Exp[7 I y] (162 (I Sin[x])^7 Cos[x]^7 + 62 (I Sin[x])^5 Cos[x]^9 + 62 (I Sin[x])^9 Cos[x]^5 + 116 (I Sin[x])^8 Cos[x]^6 + 116 (I Sin[x])^6 Cos[x]^8 + 24 (I Sin[x])^4 Cos[x]^10 + 24 (I Sin[x])^10 Cos[x]^4 + 3 (I Sin[x])^11 Cos[x]^3 + 3 (I Sin[x])^3 Cos[x]^11) + Exp[9 I y] (38 (I Sin[x])^6 Cos[x]^8 + 38 (I Sin[x])^8 Cos[x]^6 + 4 (I Sin[x])^4 Cos[x]^10 + 4 (I Sin[x])^10 Cos[x]^4 + 14 (I Sin[x])^5 Cos[x]^9 + 14 (I Sin[x])^9 Cos[x]^5 + 44 (I Sin[x])^7 Cos[x]^7) + Exp[11 I y] (7 (I Sin[x])^6 Cos[x]^8 + 7 (I Sin[x])^8 Cos[x]^6 + 4 (I Sin[x])^9 Cos[x]^5 + 4 (I Sin[x])^5 Cos[x]^9 + 4 (I Sin[x])^7 Cos[x]^7) + Exp[13 I y] (2 (I Sin[x])^7 Cos[x]^7))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-13 I y] (1 (I Sin[x])^4 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^4) + Exp[-11 I y] (1 (I Sin[x])^3 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^3 + 4 (I Sin[x])^9 Cos[x]^5 + 4 (I Sin[x])^5 Cos[x]^9 + 1 (I Sin[x])^4 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^4 + 5 (I Sin[x])^8 Cos[x]^6 + 5 (I Sin[x])^6 Cos[x]^8 + 4 (I Sin[x])^7 Cos[x]^7) + Exp[-9 I y] (26 (I Sin[x])^5 Cos[x]^9 + 26 (I Sin[x])^9 Cos[x]^5 + 6 (I Sin[x])^3 Cos[x]^11 + 6 (I Sin[x])^11 Cos[x]^3 + 22 (I Sin[x])^6 Cos[x]^8 + 22 (I Sin[x])^8 Cos[x]^6 + 13 (I Sin[x])^4 Cos[x]^10 + 13 (I Sin[x])^10 Cos[x]^4 + 20 (I Sin[x])^7 Cos[x]^7 + 1 (I Sin[x])^2 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^2) + Exp[-7 I y] (47 (I Sin[x])^4 Cos[x]^10 + 47 (I Sin[x])^10 Cos[x]^4 + 92 (I Sin[x])^8 Cos[x]^6 + 92 (I Sin[x])^6 Cos[x]^8 + 65 (I Sin[x])^5 Cos[x]^9 + 65 (I Sin[x])^9 Cos[x]^5 + 110 (I Sin[x])^7 Cos[x]^7 + 19 (I Sin[x])^11 Cos[x]^3 + 19 (I Sin[x])^3 Cos[x]^11 + 7 (I Sin[x])^2 Cos[x]^12 + 7 (I Sin[x])^12 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^1) + Exp[-5 I y] (267 (I Sin[x])^6 Cos[x]^8 + 267 (I Sin[x])^8 Cos[x]^6 + 90 (I Sin[x])^4 Cos[x]^10 + 90 (I Sin[x])^10 Cos[x]^4 + 298 (I Sin[x])^7 Cos[x]^7 + 167 (I Sin[x])^5 Cos[x]^9 + 167 (I Sin[x])^9 Cos[x]^5 + 8 (I Sin[x])^2 Cos[x]^12 + 8 (I Sin[x])^12 Cos[x]^2 + 33 (I Sin[x])^3 Cos[x]^11 + 33 (I Sin[x])^11 Cos[x]^3 + 1 (I Sin[x])^1 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^1) + Exp[-3 I y] (325 (I Sin[x])^5 Cos[x]^9 + 325 (I Sin[x])^9 Cos[x]^5 + 79 (I Sin[x])^11 Cos[x]^3 + 79 (I Sin[x])^3 Cos[x]^11 + 443 (I Sin[x])^6 Cos[x]^8 + 443 (I Sin[x])^8 Cos[x]^6 + 166 (I Sin[x])^10 Cos[x]^4 + 166 (I Sin[x])^4 Cos[x]^10 + 480 (I Sin[x])^7 Cos[x]^7 + 26 (I Sin[x])^12 Cos[x]^2 + 26 (I Sin[x])^2 Cos[x]^12 + 7 (I Sin[x])^1 Cos[x]^13 + 7 (I Sin[x])^13 Cos[x]^1 + 1 Cos[x]^14 + 1 (I Sin[x])^14) + Exp[-1 I y] (774 (I Sin[x])^7 Cos[x]^7 + 423 (I Sin[x])^5 Cos[x]^9 + 423 (I Sin[x])^9 Cos[x]^5 + 57 (I Sin[x])^3 Cos[x]^11 + 57 (I Sin[x])^11 Cos[x]^3 + 646 (I Sin[x])^8 Cos[x]^6 + 646 (I Sin[x])^6 Cos[x]^8 + 191 (I Sin[x])^4 Cos[x]^10 + 191 (I Sin[x])^10 Cos[x]^4 + 11 (I Sin[x])^2 Cos[x]^12 + 11 (I Sin[x])^12 Cos[x]^2 + 1 (I Sin[x])^13 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^13) + Exp[1 I y] (578 (I Sin[x])^6 Cos[x]^8 + 578 (I Sin[x])^8 Cos[x]^6 + 259 (I Sin[x])^10 Cos[x]^4 + 259 (I Sin[x])^4 Cos[x]^10 + 412 (I Sin[x])^5 Cos[x]^9 + 412 (I Sin[x])^9 Cos[x]^5 + 650 (I Sin[x])^7 Cos[x]^7 + 107 (I Sin[x])^11 Cos[x]^3 + 107 (I Sin[x])^3 Cos[x]^11 + 31 (I Sin[x])^2 Cos[x]^12 + 31 (I Sin[x])^12 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^13 + 4 (I Sin[x])^13 Cos[x]^1) + Exp[3 I y] (526 (I Sin[x])^6 Cos[x]^8 + 526 (I Sin[x])^8 Cos[x]^6 + 121 (I Sin[x])^4 Cos[x]^10 + 121 (I Sin[x])^10 Cos[x]^4 + 590 (I Sin[x])^7 Cos[x]^7 + 308 (I Sin[x])^5 Cos[x]^9 + 308 (I Sin[x])^9 Cos[x]^5 + 33 (I Sin[x])^3 Cos[x]^11 + 33 (I Sin[x])^11 Cos[x]^3 + 4 (I Sin[x])^12 Cos[x]^2 + 4 (I Sin[x])^2 Cos[x]^12) + Exp[5 I y] (192 (I Sin[x])^5 Cos[x]^9 + 192 (I Sin[x])^9 Cos[x]^5 + 294 (I Sin[x])^7 Cos[x]^7 + 263 (I Sin[x])^6 Cos[x]^8 + 263 (I Sin[x])^8 Cos[x]^6 + 84 (I Sin[x])^10 Cos[x]^4 + 84 (I Sin[x])^4 Cos[x]^10 + 26 (I Sin[x])^3 Cos[x]^11 + 26 (I Sin[x])^11 Cos[x]^3 + 3 (I Sin[x])^2 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^2) + Exp[7 I y] (162 (I Sin[x])^7 Cos[x]^7 + 62 (I Sin[x])^5 Cos[x]^9 + 62 (I Sin[x])^9 Cos[x]^5 + 116 (I Sin[x])^8 Cos[x]^6 + 116 (I Sin[x])^6 Cos[x]^8 + 24 (I Sin[x])^4 Cos[x]^10 + 24 (I Sin[x])^10 Cos[x]^4 + 3 (I Sin[x])^11 Cos[x]^3 + 3 (I Sin[x])^3 Cos[x]^11) + Exp[9 I y] (38 (I Sin[x])^6 Cos[x]^8 + 38 (I Sin[x])^8 Cos[x]^6 + 4 (I Sin[x])^4 Cos[x]^10 + 4 (I Sin[x])^10 Cos[x]^4 + 14 (I Sin[x])^5 Cos[x]^9 + 14 (I Sin[x])^9 Cos[x]^5 + 44 (I Sin[x])^7 Cos[x]^7) + Exp[11 I y] (7 (I Sin[x])^6 Cos[x]^8 + 7 (I Sin[x])^8 Cos[x]^6 + 4 (I Sin[x])^9 Cos[x]^5 + 4 (I Sin[x])^5 Cos[x]^9 + 4 (I Sin[x])^7 Cos[x]^7) + Exp[13 I y] (2 (I Sin[x])^7 Cos[x]^7));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":545.2666666667,"max_line_length":3869,"alphanum_fraction":0.4965154664} {"size":11135,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 16;\nname = \"16v3 2 3 1 1 3 1 1 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^7) + Exp[-13 I y] (8 (I Sin[x])^8 Cos[x]^8 + 5 (I Sin[x])^7 Cos[x]^9 + 5 (I Sin[x])^9 Cos[x]^7 + 4 (I Sin[x])^6 Cos[x]^10 + 4 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^5 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^5) + Exp[-11 I y] (28 (I Sin[x])^6 Cos[x]^10 + 28 (I Sin[x])^10 Cos[x]^6 + 48 (I Sin[x])^8 Cos[x]^8 + 36 (I Sin[x])^7 Cos[x]^9 + 36 (I Sin[x])^9 Cos[x]^7 + 13 (I Sin[x])^5 Cos[x]^11 + 13 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^4 Cos[x]^12 + 4 (I Sin[x])^12 Cos[x]^4) + Exp[-9 I y] (185 (I Sin[x])^9 Cos[x]^7 + 185 (I Sin[x])^7 Cos[x]^9 + 110 (I Sin[x])^6 Cos[x]^10 + 110 (I Sin[x])^10 Cos[x]^6 + 200 (I Sin[x])^8 Cos[x]^8 + 44 (I Sin[x])^5 Cos[x]^11 + 44 (I Sin[x])^11 Cos[x]^5 + 14 (I Sin[x])^4 Cos[x]^12 + 14 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3) + Exp[-7 I y] (203 (I Sin[x])^5 Cos[x]^11 + 203 (I Sin[x])^11 Cos[x]^5 + 460 (I Sin[x])^7 Cos[x]^9 + 460 (I Sin[x])^9 Cos[x]^7 + 334 (I Sin[x])^6 Cos[x]^10 + 334 (I Sin[x])^10 Cos[x]^6 + 488 (I Sin[x])^8 Cos[x]^8 + 90 (I Sin[x])^4 Cos[x]^12 + 90 (I Sin[x])^12 Cos[x]^4 + 30 (I Sin[x])^3 Cos[x]^13 + 30 (I Sin[x])^13 Cos[x]^3 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2) + Exp[-5 I y] (1312 (I Sin[x])^8 Cos[x]^8 + 731 (I Sin[x])^6 Cos[x]^10 + 731 (I Sin[x])^10 Cos[x]^6 + 365 (I Sin[x])^5 Cos[x]^11 + 365 (I Sin[x])^11 Cos[x]^5 + 1100 (I Sin[x])^7 Cos[x]^9 + 1100 (I Sin[x])^9 Cos[x]^7 + 122 (I Sin[x])^4 Cos[x]^12 + 122 (I Sin[x])^12 Cos[x]^4 + 26 (I Sin[x])^3 Cos[x]^13 + 26 (I Sin[x])^13 Cos[x]^3 + 3 (I Sin[x])^2 Cos[x]^14 + 3 (I Sin[x])^14 Cos[x]^2) + Exp[-3 I y] (336 (I Sin[x])^4 Cos[x]^12 + 336 (I Sin[x])^12 Cos[x]^4 + 1836 (I Sin[x])^8 Cos[x]^8 + 1238 (I Sin[x])^6 Cos[x]^10 + 1238 (I Sin[x])^10 Cos[x]^6 + 1649 (I Sin[x])^7 Cos[x]^9 + 1649 (I Sin[x])^9 Cos[x]^7 + 724 (I Sin[x])^5 Cos[x]^11 + 724 (I Sin[x])^11 Cos[x]^5 + 108 (I Sin[x])^3 Cos[x]^13 + 108 (I Sin[x])^13 Cos[x]^3 + 28 (I Sin[x])^2 Cos[x]^14 + 28 (I Sin[x])^14 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[-1 I y] (2375 (I Sin[x])^9 Cos[x]^7 + 2375 (I Sin[x])^7 Cos[x]^9 + 783 (I Sin[x])^5 Cos[x]^11 + 783 (I Sin[x])^11 Cos[x]^5 + 288 (I Sin[x])^4 Cos[x]^12 + 288 (I Sin[x])^12 Cos[x]^4 + 1584 (I Sin[x])^6 Cos[x]^10 + 1584 (I Sin[x])^10 Cos[x]^6 + 2632 (I Sin[x])^8 Cos[x]^8 + 76 (I Sin[x])^3 Cos[x]^13 + 76 (I Sin[x])^13 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[1 I y] (156 (I Sin[x])^3 Cos[x]^13 + 156 (I Sin[x])^13 Cos[x]^3 + 2164 (I Sin[x])^9 Cos[x]^7 + 2164 (I Sin[x])^7 Cos[x]^9 + 908 (I Sin[x])^5 Cos[x]^11 + 908 (I Sin[x])^11 Cos[x]^5 + 2402 (I Sin[x])^8 Cos[x]^8 + 1549 (I Sin[x])^6 Cos[x]^10 + 1549 (I Sin[x])^10 Cos[x]^6 + 410 (I Sin[x])^4 Cos[x]^12 + 410 (I Sin[x])^12 Cos[x]^4 + 39 (I Sin[x])^2 Cos[x]^14 + 39 (I Sin[x])^14 Cos[x]^2 + 7 (I Sin[x])^1 Cos[x]^15 + 7 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[3 I y] (1205 (I Sin[x])^10 Cos[x]^6 + 1205 (I Sin[x])^6 Cos[x]^10 + 2140 (I Sin[x])^8 Cos[x]^8 + 234 (I Sin[x])^4 Cos[x]^12 + 234 (I Sin[x])^12 Cos[x]^4 + 614 (I Sin[x])^5 Cos[x]^11 + 614 (I Sin[x])^11 Cos[x]^5 + 1810 (I Sin[x])^7 Cos[x]^9 + 1810 (I Sin[x])^9 Cos[x]^7 + 60 (I Sin[x])^3 Cos[x]^13 + 60 (I Sin[x])^13 Cos[x]^3 + 11 (I Sin[x])^2 Cos[x]^14 + 11 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^15 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^15) + Exp[5 I y] (212 (I Sin[x])^4 Cos[x]^12 + 212 (I Sin[x])^12 Cos[x]^4 + 734 (I Sin[x])^10 Cos[x]^6 + 734 (I Sin[x])^6 Cos[x]^10 + 1096 (I Sin[x])^8 Cos[x]^8 + 989 (I Sin[x])^9 Cos[x]^7 + 989 (I Sin[x])^7 Cos[x]^9 + 431 (I Sin[x])^5 Cos[x]^11 + 431 (I Sin[x])^11 Cos[x]^5 + 18 (I Sin[x])^2 Cos[x]^14 + 18 (I Sin[x])^14 Cos[x]^2 + 68 (I Sin[x])^3 Cos[x]^13 + 68 (I Sin[x])^13 Cos[x]^3 + 3 (I Sin[x])^1 Cos[x]^15 + 3 (I Sin[x])^15 Cos[x]^1) + Exp[7 I y] (177 (I Sin[x])^11 Cos[x]^5 + 177 (I Sin[x])^5 Cos[x]^11 + 499 (I Sin[x])^9 Cos[x]^7 + 499 (I Sin[x])^7 Cos[x]^9 + 62 (I Sin[x])^4 Cos[x]^12 + 62 (I Sin[x])^12 Cos[x]^4 + 340 (I Sin[x])^6 Cos[x]^10 + 340 (I Sin[x])^10 Cos[x]^6 + 536 (I Sin[x])^8 Cos[x]^8 + 17 (I Sin[x])^3 Cos[x]^13 + 17 (I Sin[x])^13 Cos[x]^3 + 2 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^14) + Exp[9 I y] (15 (I Sin[x])^3 Cos[x]^13 + 15 (I Sin[x])^13 Cos[x]^3 + 132 (I Sin[x])^9 Cos[x]^7 + 132 (I Sin[x])^7 Cos[x]^9 + 84 (I Sin[x])^5 Cos[x]^11 + 84 (I Sin[x])^11 Cos[x]^5 + 132 (I Sin[x])^8 Cos[x]^8 + 119 (I Sin[x])^6 Cos[x]^10 + 119 (I Sin[x])^10 Cos[x]^6 + 36 (I Sin[x])^4 Cos[x]^12 + 36 (I Sin[x])^12 Cos[x]^4 + 3 (I Sin[x])^2 Cos[x]^14 + 3 (I Sin[x])^14 Cos[x]^2) + Exp[11 I y] (30 (I Sin[x])^10 Cos[x]^6 + 30 (I Sin[x])^6 Cos[x]^10 + 8 (I Sin[x])^12 Cos[x]^4 + 8 (I Sin[x])^4 Cos[x]^12 + 36 (I Sin[x])^8 Cos[x]^8 + 16 (I Sin[x])^5 Cos[x]^11 + 16 (I Sin[x])^11 Cos[x]^5 + 32 (I Sin[x])^7 Cos[x]^9 + 32 (I Sin[x])^9 Cos[x]^7 + 1 (I Sin[x])^13 Cos[x]^3 + 1 (I Sin[x])^3 Cos[x]^13) + Exp[13 I y] (4 (I Sin[x])^4 Cos[x]^12 + 4 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^6 Cos[x]^10 + 4 (I Sin[x])^8 Cos[x]^8 + 3 (I Sin[x])^9 Cos[x]^7 + 3 (I Sin[x])^7 Cos[x]^9 + 3 (I Sin[x])^5 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^5 + 1 (I Sin[x])^3 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^3) + Exp[15 I y] (1 (I Sin[x])^11 Cos[x]^5 + 1 (I Sin[x])^5 Cos[x]^11))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^7) + Exp[-13 I y] (8 (I Sin[x])^8 Cos[x]^8 + 5 (I Sin[x])^7 Cos[x]^9 + 5 (I Sin[x])^9 Cos[x]^7 + 4 (I Sin[x])^6 Cos[x]^10 + 4 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^5 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^5) + Exp[-11 I y] (28 (I Sin[x])^6 Cos[x]^10 + 28 (I Sin[x])^10 Cos[x]^6 + 48 (I Sin[x])^8 Cos[x]^8 + 36 (I Sin[x])^7 Cos[x]^9 + 36 (I Sin[x])^9 Cos[x]^7 + 13 (I Sin[x])^5 Cos[x]^11 + 13 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^4 Cos[x]^12 + 4 (I Sin[x])^12 Cos[x]^4) + Exp[-9 I y] (185 (I Sin[x])^9 Cos[x]^7 + 185 (I Sin[x])^7 Cos[x]^9 + 110 (I Sin[x])^6 Cos[x]^10 + 110 (I Sin[x])^10 Cos[x]^6 + 200 (I Sin[x])^8 Cos[x]^8 + 44 (I Sin[x])^5 Cos[x]^11 + 44 (I Sin[x])^11 Cos[x]^5 + 14 (I Sin[x])^4 Cos[x]^12 + 14 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3) + Exp[-7 I y] (203 (I Sin[x])^5 Cos[x]^11 + 203 (I Sin[x])^11 Cos[x]^5 + 460 (I Sin[x])^7 Cos[x]^9 + 460 (I Sin[x])^9 Cos[x]^7 + 334 (I Sin[x])^6 Cos[x]^10 + 334 (I Sin[x])^10 Cos[x]^6 + 488 (I Sin[x])^8 Cos[x]^8 + 90 (I Sin[x])^4 Cos[x]^12 + 90 (I Sin[x])^12 Cos[x]^4 + 30 (I Sin[x])^3 Cos[x]^13 + 30 (I Sin[x])^13 Cos[x]^3 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2) + Exp[-5 I y] (1312 (I Sin[x])^8 Cos[x]^8 + 731 (I Sin[x])^6 Cos[x]^10 + 731 (I Sin[x])^10 Cos[x]^6 + 365 (I Sin[x])^5 Cos[x]^11 + 365 (I Sin[x])^11 Cos[x]^5 + 1100 (I Sin[x])^7 Cos[x]^9 + 1100 (I Sin[x])^9 Cos[x]^7 + 122 (I Sin[x])^4 Cos[x]^12 + 122 (I Sin[x])^12 Cos[x]^4 + 26 (I Sin[x])^3 Cos[x]^13 + 26 (I Sin[x])^13 Cos[x]^3 + 3 (I Sin[x])^2 Cos[x]^14 + 3 (I Sin[x])^14 Cos[x]^2) + Exp[-3 I y] (336 (I Sin[x])^4 Cos[x]^12 + 336 (I Sin[x])^12 Cos[x]^4 + 1836 (I Sin[x])^8 Cos[x]^8 + 1238 (I Sin[x])^6 Cos[x]^10 + 1238 (I Sin[x])^10 Cos[x]^6 + 1649 (I Sin[x])^7 Cos[x]^9 + 1649 (I Sin[x])^9 Cos[x]^7 + 724 (I Sin[x])^5 Cos[x]^11 + 724 (I Sin[x])^11 Cos[x]^5 + 108 (I Sin[x])^3 Cos[x]^13 + 108 (I Sin[x])^13 Cos[x]^3 + 28 (I Sin[x])^2 Cos[x]^14 + 28 (I Sin[x])^14 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[-1 I y] (2375 (I Sin[x])^9 Cos[x]^7 + 2375 (I Sin[x])^7 Cos[x]^9 + 783 (I Sin[x])^5 Cos[x]^11 + 783 (I Sin[x])^11 Cos[x]^5 + 288 (I Sin[x])^4 Cos[x]^12 + 288 (I Sin[x])^12 Cos[x]^4 + 1584 (I Sin[x])^6 Cos[x]^10 + 1584 (I Sin[x])^10 Cos[x]^6 + 2632 (I Sin[x])^8 Cos[x]^8 + 76 (I Sin[x])^3 Cos[x]^13 + 76 (I Sin[x])^13 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[1 I y] (156 (I Sin[x])^3 Cos[x]^13 + 156 (I Sin[x])^13 Cos[x]^3 + 2164 (I Sin[x])^9 Cos[x]^7 + 2164 (I Sin[x])^7 Cos[x]^9 + 908 (I Sin[x])^5 Cos[x]^11 + 908 (I Sin[x])^11 Cos[x]^5 + 2402 (I Sin[x])^8 Cos[x]^8 + 1549 (I Sin[x])^6 Cos[x]^10 + 1549 (I Sin[x])^10 Cos[x]^6 + 410 (I Sin[x])^4 Cos[x]^12 + 410 (I Sin[x])^12 Cos[x]^4 + 39 (I Sin[x])^2 Cos[x]^14 + 39 (I Sin[x])^14 Cos[x]^2 + 7 (I Sin[x])^1 Cos[x]^15 + 7 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[3 I y] (1205 (I Sin[x])^10 Cos[x]^6 + 1205 (I Sin[x])^6 Cos[x]^10 + 2140 (I Sin[x])^8 Cos[x]^8 + 234 (I Sin[x])^4 Cos[x]^12 + 234 (I Sin[x])^12 Cos[x]^4 + 614 (I Sin[x])^5 Cos[x]^11 + 614 (I Sin[x])^11 Cos[x]^5 + 1810 (I Sin[x])^7 Cos[x]^9 + 1810 (I Sin[x])^9 Cos[x]^7 + 60 (I Sin[x])^3 Cos[x]^13 + 60 (I Sin[x])^13 Cos[x]^3 + 11 (I Sin[x])^2 Cos[x]^14 + 11 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^15 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^15) + Exp[5 I y] (212 (I Sin[x])^4 Cos[x]^12 + 212 (I Sin[x])^12 Cos[x]^4 + 734 (I Sin[x])^10 Cos[x]^6 + 734 (I Sin[x])^6 Cos[x]^10 + 1096 (I Sin[x])^8 Cos[x]^8 + 989 (I Sin[x])^9 Cos[x]^7 + 989 (I Sin[x])^7 Cos[x]^9 + 431 (I Sin[x])^5 Cos[x]^11 + 431 (I Sin[x])^11 Cos[x]^5 + 18 (I Sin[x])^2 Cos[x]^14 + 18 (I Sin[x])^14 Cos[x]^2 + 68 (I Sin[x])^3 Cos[x]^13 + 68 (I Sin[x])^13 Cos[x]^3 + 3 (I Sin[x])^1 Cos[x]^15 + 3 (I Sin[x])^15 Cos[x]^1) + Exp[7 I y] (177 (I Sin[x])^11 Cos[x]^5 + 177 (I Sin[x])^5 Cos[x]^11 + 499 (I Sin[x])^9 Cos[x]^7 + 499 (I Sin[x])^7 Cos[x]^9 + 62 (I Sin[x])^4 Cos[x]^12 + 62 (I Sin[x])^12 Cos[x]^4 + 340 (I Sin[x])^6 Cos[x]^10 + 340 (I Sin[x])^10 Cos[x]^6 + 536 (I Sin[x])^8 Cos[x]^8 + 17 (I Sin[x])^3 Cos[x]^13 + 17 (I Sin[x])^13 Cos[x]^3 + 2 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^14) + Exp[9 I y] (15 (I Sin[x])^3 Cos[x]^13 + 15 (I Sin[x])^13 Cos[x]^3 + 132 (I Sin[x])^9 Cos[x]^7 + 132 (I Sin[x])^7 Cos[x]^9 + 84 (I Sin[x])^5 Cos[x]^11 + 84 (I Sin[x])^11 Cos[x]^5 + 132 (I Sin[x])^8 Cos[x]^8 + 119 (I Sin[x])^6 Cos[x]^10 + 119 (I Sin[x])^10 Cos[x]^6 + 36 (I Sin[x])^4 Cos[x]^12 + 36 (I Sin[x])^12 Cos[x]^4 + 3 (I Sin[x])^2 Cos[x]^14 + 3 (I Sin[x])^14 Cos[x]^2) + Exp[11 I y] (30 (I Sin[x])^10 Cos[x]^6 + 30 (I Sin[x])^6 Cos[x]^10 + 8 (I Sin[x])^12 Cos[x]^4 + 8 (I Sin[x])^4 Cos[x]^12 + 36 (I Sin[x])^8 Cos[x]^8 + 16 (I Sin[x])^5 Cos[x]^11 + 16 (I Sin[x])^11 Cos[x]^5 + 32 (I Sin[x])^7 Cos[x]^9 + 32 (I Sin[x])^9 Cos[x]^7 + 1 (I Sin[x])^13 Cos[x]^3 + 1 (I Sin[x])^3 Cos[x]^13) + Exp[13 I y] (4 (I Sin[x])^4 Cos[x]^12 + 4 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^10 Cos[x]^6 + 2 (I Sin[x])^6 Cos[x]^10 + 4 (I Sin[x])^8 Cos[x]^8 + 3 (I Sin[x])^9 Cos[x]^7 + 3 (I Sin[x])^7 Cos[x]^9 + 3 (I Sin[x])^5 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^5 + 1 (I Sin[x])^3 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^3) + Exp[15 I y] (1 (I Sin[x])^11 Cos[x]^5 + 1 (I Sin[x])^5 Cos[x]^11));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":742.3333333333,"max_line_length":5344,"alphanum_fraction":0.5039964077} {"size":42146,"ext":"mt","lang":"Mathematica","max_stars_count":4.0,"content":"syms=DefaultSymbols[];\n\n\n\n\nTest[\n MasterFunction[syms],\n\n XZM[t, r],\n\n TestID->\"MasterFunction[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n HttAmplitude[syms],\n\n h[Rule[\"Indices\", List[Rule[\"Down\", List[\"t\", \"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"RWZTag\"]]]]][t, r],\n\n TestID->\"HttAmplitude[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n HtrAmplitude[syms],\n\n h[Rule[\"Indices\", List[Rule[\"Down\", List[\"t\", \"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"RWZTag\"]]]]][t, r],\n\n TestID->\"HtrAmplitude[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n HrrAmplitude[syms],\n\n h[Rule[\"Indices\", List[Rule[\"Down\", List[\"r\", \"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"RWZTag\"]]]]][t, r],\n\n TestID->\"HrrAmplitude[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n JtAmplitude[syms],\n\n 0,\n\n TestID->\"JtAmplitude[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n JrAmplitude[syms],\n\n 0,\n\n TestID->\"JrAmplitude[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n GAmplitude[syms],\n\n 0,\n\n TestID->\"GAmplitude[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n KAmplitude[syms],\n\n \\[ScriptCapitalK][Rule[\"Tags\", List[Rule[\"Up\", List[\"RWZTag\"]]]]][t, r],\n\n TestID->\"KAmplitude[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n HttInvariantAmplitude[syms],\n\n h[Rule[\"Indices\", List[Rule[\"Down\", List[\"t\", \"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"RWZTag\"]]]]][t, r],\n\n TestID->\"HttInvariantAmplitude[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n HtrInvariantAmplitude[syms],\n\n h[Rule[\"Indices\", List[Rule[\"Down\", List[\"t\", \"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"RWZTag\"]]]]][t, r],\n\n TestID->\"HtrInvariantAmplitude[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n HrrInvariantAmplitude[syms],\n\n h[Rule[\"Indices\", List[Rule[\"Down\", List[\"r\", \"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"RWZTag\"]]]]][t, r],\n\n TestID->\"HrrInvariantAmplitude[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n KInvariantAmplitude[syms],\n\n \\[ScriptCapitalK][Rule[\"Tags\", List[Rule[\"Up\", List[\"RWZTag\"]]]]][t, r],\n\n TestID->\"KInvariantAmplitude[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n HtAmplitude[syms],\n\n h[Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"RWZTag\"]]]]][t, r],\n\n TestID->\"HtAmplitude[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n HrAmplitude[syms],\n\n h[Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"RWZTag\"]]]]][t, r],\n\n TestID->\"HrAmplitude[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n H2Amplitude[syms],\n\n 0,\n\n TestID->\"H2Amplitude[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n HtInvariantAmplitude[syms],\n\n h[Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"RWZTag\"]]]]][t, r],\n\n TestID->\"HtInvariantAmplitude[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n HrInvariantAmplitude[syms],\n\n h[Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"RWZTag\"]]]]][t, r],\n\n TestID->\"HrInvariantAmplitude[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n HttPush[syms],\n\n Plus[Times[-2, Derivative[1, 0][\\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\"]]]]]][t, r]], Times[2, M, Plus[1, Times[-2, M, Power[r, -1]]], Power[r, -2], \\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\"]]]]][t, r]]],\n\n TestID->\"HttPush[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n HtrPush[syms],\n\n Plus[Times[-1, Derivative[0, 1][\\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\"]]]]]][t, r]], Times[-1, Derivative[1, 0][\\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\"]]]]]][t, r]], Times[2, M, Power[Plus[1, Times[-2, M, Power[r, -1]]], -1], Power[r, -2], \\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\"]]]]][t, r]]],\n\n TestID->\"HtrPush[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n HrrPush[syms],\n\n Plus[Times[-2, Derivative[0, 1][\\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\"]]]]]][t, r]], Times[-2, M, Power[Plus[1, Times[-2, M, Power[r, -1]]], -1], Power[r, -2], \\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\"]]]]][t, r]]],\n\n TestID->\"HrrPush[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n JtPush[syms],\n\n Plus[Times[-1, Derivative[1, 0][\\[Xi][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\"]]]]]][t, r]], Times[-1, \\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\"]]]]][t, r]]],\n\n TestID->\"JtPush[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n JrPush[syms],\n\n Plus[Times[2, Power[r, -1], \\[Xi][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\"]]]]][t, r]], Times[-1, Derivative[0, 1][\\[Xi][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\"]]]]]][t, r]], Times[-1, \\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\"]]]]][t, r]]],\n\n TestID->\"JrPush[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n KPush[syms],\n\n Plus[Times[2, Plus[1, Times[Rational[1, 2], Plus[-1, l], Plus[2, l]]], Power[r, -2], \\[Xi][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\"]]]]][t, r]], Times[-2, Plus[1, Times[-2, M, Power[r, -1]]], Power[r, -1], \\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\"]]]]][t, r]]],\n\n TestID->\"KPush[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n GPush[syms],\n\n Times[-2, Power[r, -2], \\[Xi][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\"]]]]][t, r]],\n\n TestID->\"GPush[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n HtPush[syms],\n\n Times[-1, Derivative[1, 0][\\[Xi][Rule[\"Tags\", List[Rule[\"Up\", List[\"OddTag\", \"RWZTag\", \"LorenzTag\"]]]]]][t, r]],\n\n TestID->\"HtPush[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n HrPush[syms],\n\n Plus[Times[2, Power[r, -1], \\[Xi][Rule[\"Tags\", List[Rule[\"Up\", List[\"OddTag\", \"RWZTag\", \"LorenzTag\"]]]]][t, r]], Times[-1, Derivative[0, 1][\\[Xi][Rule[\"Tags\", List[Rule[\"Up\", List[\"OddTag\", \"RWZTag\", \"LorenzTag\"]]]]]][t, r]]],\n\n TestID->\"HrPush[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n H2Push[syms],\n\n Times[-2, \\[Xi][Rule[\"Tags\", List[Rule[\"Up\", List[\"OddTag\", \"RWZTag\", \"LorenzTag\"]]]]][t, r]],\n\n TestID->\"H2Push[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n XiEvenAmplitude[syms],\n\n \\[Xi][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\"]]]]][t, r],\n\n TestID->\"XiEvenAmplitude[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n XiEvenTAmplitude[syms],\n\n \\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\"]]]]][t, r],\n\n TestID->\"XiEvenTAmplitude[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n XiEvenRAmplitude[syms],\n\n \\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\"]]]]][t, r],\n\n TestID->\"XiEvenRAmplitude[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n XiOddAmplitude[syms],\n\n \\[Xi][Rule[\"Tags\", List[Rule[\"Up\", List[\"OddTag\", \"RWZTag\", \"LorenzTag\"]]]]][t, r],\n\n TestID->\"XiOddAmplitude[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (HttAmplitude[#1, Gauge -> \"RWZ\", Weak -> True] & )[syms],\n\n Plus[Times[\\[Theta][Plus[Times[-1, r], rp[t]]], h[Rule[\"Indices\", List[Rule[\"Down\", List[\"t\", \"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"RWZTag\", \"MinusTag\"]]]]][t, r]], Times[\\[Theta][Plus[r, Times[-1, rp[t]]]], h[Rule[\"Indices\", List[Rule[\"Down\", List[\"t\", \"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"RWZTag\", \"PlusTag\"]]]]][t, r]], Times[\\[Delta][Plus[r, Times[-1, rp[t]]]], G[0][0, 0][h[Rule[\"Indices\", List[Rule[\"Down\", List[\"t\", \"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"RWZTag\"]]]]]][t]]],\n\n TestID->\"(HttAmplitude[#1, Gauge -> RWZ, Weak -> True] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (HttAmplitude[#1, Gauge -> \"RWZ\", Reconstruct -> True] & )[syms],\n\n Plus[Times[Rational[1, 2], Plus[Times[2, M], Times[-1, r]], Power[r, -3], Power[Plus[Times[6, M], Times[Plus[-2, l, Power[l, 2]], r]], -2], Plus[Times[72, Power[M, 3]], Times[36, Plus[-2, l, Power[l, 2]], Power[M, 2], r], Times[6, Power[Plus[-2, l, Power[l, 2]], 2], M, Power[r, 2]], Times[l, Plus[1, l], Power[Plus[-2, l, Power[l, 2]], 2], Power[r, 3]]], XZM[t, r]], Times[2, Power[l, -1], Power[Plus[1, l], -1], Power[r, 2], Power[Plus[Times[6, M], Times[Plus[-2, l, Power[l, 2]], r]], -2], Plus[Times[108, Power[M, 2]], Times[4, Plus[-19, Times[5, l], Times[5, Power[l, 2]]], M, r], Times[Plus[12, Times[-8, l], Times[-7, Power[l, 2]], Times[2, Power[l, 3]], Power[l, 4]], Power[r, 2]]], Q[Rule[\"Indices\", List[Rule[\"Down\", List[\"t\", \"t\"]]]]][t, r]], Times[Plus[1, Times[-2, M, Power[r, -1]]], Q[Rule[\"Tags\", List[Rule[\"Up\", List[\"Sharp\"]]]]][t, r]], Times[-1, Plus[Times[2, M], Times[-1, r]], Power[r, -2], Power[Plus[Times[6, M], Times[Plus[-2, l, Power[l, 2]], r]], -1], Plus[Times[6, Power[M, 2]], Times[-1, Plus[-2, l, Power[l, 2]], M, r], Times[Plus[-2, l, Power[l, 2]], Power[r, 2]]], Derivative[0, 1][XZM][t, r]], Times[4, Power[l, -1], Power[Plus[1, l], -1], Plus[Times[2, M], Times[-1, r]], Power[r, 3], Power[Plus[Times[6, M], Times[Plus[-2, l, Power[l, 2]], r]], -1], Derivative[0, 1][Q[Rule[\"Indices\", List[Rule[\"Down\", List[\"t\", \"t\"]]]]]][t, r]], Times[Power[r, -1], Power[Plus[Times[-2, M], r], 2], Derivative[0, 2][XZM][t, r]]],\n\n TestID->\"(HttAmplitude[#1, Gauge -> RWZ, Reconstruct -> True] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (HttAmplitude[#1, Gauge -> \"Lorenz\"] & )[syms],\n\n h[Rule[\"Indices\", List[Rule[\"Down\", List[\"t\", \"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"LorenzTag\"]]]]][t, r],\n\n TestID->\"(HttAmplitude[#1, Gauge -> Lorenz] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (HttAmplitude[#1, Gauge -> \"Lorenz\", Weak -> True] & )[syms],\n\n Plus[Times[\\[Theta][Plus[Times[-1, r], rp[t]]], h[Rule[\"Indices\", List[Rule[\"Down\", List[\"t\", \"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"LorenzTag\", \"MinusTag\"]]]]][t, r]], Times[\\[Theta][Plus[r, Times[-1, rp[t]]]], h[Rule[\"Indices\", List[Rule[\"Down\", List[\"t\", \"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"LorenzTag\", \"PlusTag\"]]]]][t, r]]],\n\n TestID->\"(HttAmplitude[#1, Gauge -> Lorenz, Weak -> True] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (HttAmplitude[#1, Gauge -> \"RWZ\", Reconstruct -> True, SourceExpansion -> \"Full\"] & )[syms],\n\n Plus[Times[Rational[1, 2], Plus[Times[2, M], Times[-1, r]], Power[r, -3], Power[Plus[Times[6, M], Times[Plus[-2, l, Power[l, 2]], r]], -2], Plus[Times[72, Power[M, 3]], Times[36, Plus[-2, l, Power[l, 2]], Power[M, 2], r], Times[6, Power[Plus[-2, l, Power[l, 2]], 2], M, Power[r, 2]], Times[l, Plus[1, l], Power[Plus[-2, l, Power[l, 2]], 2], Power[r, 3]]], XZM[t, r]], Times[-32, Power[l, -1], Power[Plus[1, l], -1], Pi, Plus[Times[2, M], Times[-1, r]], Power[r, 3], Power[Plus[Times[6, M], Times[Plus[-2, l, Power[l, 2]], r]], -1], \\[ScriptCapitalE], \\[Mu], Plus[Times[2, M], Times[-1, rp[t]]], Power[rp[t], -3], Y[Rule[\"OverStr\", \"Bar\"]][t], Derivative[1][\\[Delta]][Plus[r, Times[-1, rp[t]]]]], Times[-1, Plus[Times[2, M], Times[-1, r]], Power[r, -2], Power[Plus[Times[6, M], Times[Plus[-2, l, Power[l, 2]], r]], -1], Plus[Times[6, Power[M, 2]], Times[-1, Plus[-2, l, Power[l, 2]], M, r], Times[Plus[-2, l, Power[l, 2]], Power[r, 2]]], Derivative[0, 1][XZM][t, r]], Times[Power[r, -1], Power[Plus[Times[-2, M], r], 2], Derivative[0, 2][XZM][t, r]], Times[16, Power[l, -1], Power[Plus[1, l], -1], Pi, Plus[1, Times[-2, M, Power[r, -1]]], Power[\\[ScriptCapitalE], -1], \\[Mu], Plus[Times[2, M], Times[-1, rp[t]]], Power[rp[t], -3], \\[Delta][Plus[r, Times[-1, rp[t]]]], Plus[Times[Power[Plus[Times[2, M], Times[-1, r]], -1], Power[r, 3], Power[Plus[Times[6, M], Times[Plus[-2, l, Power[l, 2]], r]], -2], Plus[Times[108, Power[M, 2]], Times[4, Plus[-19, Times[5, l], Times[5, Power[l, 2]]], M, r], Times[Plus[12, Times[-8, l], Times[-7, Power[l, 2]], Times[2, Power[l, 3]], Power[l, 4]], Power[r, 2]]], Power[\\[ScriptCapitalE], 2], Y[Rule[\"OverStr\", \"Bar\"]][t]], Times[-2, Power[Plus[-2, l, Power[l, 2]], -1], Power[\\[ScriptCapitalL], 2], Y[Rule[\"OverStr\", \"Bar\"]][Rule[\"Indices\", List[Rule[\"Down\", List[\"phi\", \"phi\"]]]]][t]]]]],\n\n TestID->\"(HttAmplitude[#1, Gauge -> RWZ, Reconstruct -> True, SourceExpansion -> Full] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (HtrAmplitude[#1, Gauge -> \"RWZ\", Reconstruct -> True, SourceExpansion -> \"Full\"] & )[syms],\n\n Plus[Times[Derivative[1][rp][t], Plus[Times[16, Power[l, -1], Power[Plus[1, l], -1], Pi, Power[Plus[Times[2, M], Times[-1, r]], -1], Power[Plus[Times[6, M], Times[Plus[-2, l, Power[l, 2]], r]], -1], \\[ScriptCapitalE], \\[Mu], Power[Plus[Times[2, M], Times[-1, rp[t]]], -1], Power[rp[t], -4], Plus[Times[24, Power[M, 2], Power[r, 5]], Times[-20, M, Power[r, 5], rp[t]], Times[4, Power[r, 5], Power[rp[t], 2]], Times[Power[r, 2], Plus[Times[12, Power[M, 2]], Times[2, Plus[-5, l, Power[l, 2]], M, r], Times[-1, Plus[-2, l, Power[l, 2]], Power[r, 2]]], Power[rp[t], 3]]], \\[Delta][Plus[r, Times[-1, rp[t]]]], Y[Rule[\"OverStr\", \"Bar\"]][t]], Times[32, Power[l, -1], Power[Plus[1, l], -1], Pi, Power[Plus[Times[2, M], Times[-1, r]], -1], Power[r, 5], Power[Plus[Times[6, M], Times[Plus[-2, l, Power[l, 2]], r]], -1], \\[ScriptCapitalE], \\[Mu], Plus[Times[2, M], Times[-1, rp[t]]], Power[rp[t], -3], Y[Rule[\"OverStr\", \"Bar\"]][t], Derivative[1][\\[Delta]][Plus[r, Times[-1, rp[t]]]]]]], Times[-32, Power[l, -1], Power[Plus[1, l], -1], Pi, Power[Plus[Times[2, M], Times[-1, r]], -1], Power[r, 5], Power[Plus[Times[6, M], Times[Plus[-2, l, Power[l, 2]], r]], -1], \\[ScriptCapitalE], \\[Mu], Plus[Times[2, M], Times[-1, rp[t]]], Power[rp[t], -3], \\[Delta][Plus[r, Times[-1, rp[t]]]], Derivative[1][Y[Rule[\"OverStr\", \"Bar\"]]][t]], Times[Power[Plus[Times[2, M], Times[-1, r]], -1], Power[Plus[Times[6, M], Times[Plus[-2, l, Power[l, 2]], r]], -1], Plus[Times[6, Power[M, 2]], Times[3, Plus[-2, l, Power[l, 2]], M, r], Times[-1, Plus[-2, l, Power[l, 2]], Power[r, 2]]], Derivative[1, 0][XZM][t, r]], Times[r, Derivative[1, 1][XZM][t, r]]],\n\n TestID->\"(HtrAmplitude[#1, Gauge -> RWZ, Reconstruct -> True, SourceExpansion -> Full] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (HrrAmplitude[#1, Gauge -> \"RWZ\", Reconstruct -> True, SourceExpansion -> \"Full\"] & )[syms],\n\n Plus[Times[Rational[1, 2], Power[Plus[Times[2, M], Times[-1, r]], -1], Power[r, -1], Power[Plus[Times[6, M], Times[Plus[-2, l, Power[l, 2]], r]], -2], Plus[Times[72, Power[M, 3]], Times[36, Plus[-2, l, Power[l, 2]], Power[M, 2], r], Times[6, Power[Plus[-2, l, Power[l, 2]], 2], M, Power[r, 2]], Times[l, Plus[1, l], Power[Plus[-2, l, Power[l, 2]], 2], Power[r, 3]]], XZM[t, r]], Times[-16, Power[l, -1], Power[Plus[1, l], -1], Pi, Power[r, 4], Power[Plus[Times[-2, M], r], -2], Power[Plus[Times[6, M], Times[Plus[-2, l, Power[l, 2]], r]], -2], Plus[Times[108, Power[M, 2]], Times[4, Plus[-19, Times[5, l], Times[5, Power[l, 2]]], M, r], Times[Plus[12, Times[-8, l], Times[-7, Power[l, 2]], Times[2, Power[l, 3]], Power[l, 4]], Power[r, 2]]], \\[ScriptCapitalE], \\[Mu], Plus[Times[2, M], Times[-1, rp[t]]], Power[rp[t], -3], \\[Delta][Plus[r, Times[-1, rp[t]]]], Y[Rule[\"OverStr\", \"Bar\"]][t]], Times[-32, Power[l, -1], Power[Plus[1, l], -1], Pi, Power[Plus[Times[2, M], Times[-1, r]], -1], Power[r, 5], Power[Plus[Times[6, M], Times[Plus[-2, l, Power[l, 2]], r]], -1], \\[ScriptCapitalE], \\[Mu], Plus[Times[2, M], Times[-1, rp[t]]], Power[rp[t], -3], Y[Rule[\"OverStr\", \"Bar\"]][t], Derivative[1][\\[Delta]][Plus[r, Times[-1, rp[t]]]]], Times[Power[Plus[Times[2, M], Times[-1, r]], -1], Power[Plus[Times[6, M], Times[Plus[-2, l, Power[l, 2]], r]], -1], Plus[Times[-6, Power[M, 2]], Times[Plus[-2, l, Power[l, 2]], M, r], Times[-1, Plus[-2, l, Power[l, 2]], Power[r, 2]]], Derivative[0, 1][XZM][t, r]], Times[r, Derivative[0, 2][XZM][t, r]]],\n\n TestID->\"(HrrAmplitude[#1, Gauge -> RWZ, Reconstruct -> True, SourceExpansion -> Full] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (JtAmplitude[#1, Gauge -> \"Lorenz\", Weak -> True] & )[syms],\n\n Plus[Times[\\[Theta][Plus[Times[-1, r], rp[t]]], j[Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"LorenzTag\", \"MinusTag\"]]]]][t, r]], Times[\\[Theta][Plus[r, Times[-1, rp[t]]]], j[Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"LorenzTag\", \"PlusTag\"]]]]][t, r]]],\n\n TestID->\"(JtAmplitude[#1, Gauge -> Lorenz, Weak -> True] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (JrAmplitude[#1, Gauge -> \"Lorenz\", Weak -> True] & )[syms],\n\n Plus[Times[\\[Theta][Plus[Times[-1, r], rp[t]]], j[Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"LorenzTag\", \"MinusTag\"]]]]][t, r]], Times[\\[Theta][Plus[r, Times[-1, rp[t]]]], j[Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"LorenzTag\", \"PlusTag\"]]]]][t, r]]],\n\n TestID->\"(JrAmplitude[#1, Gauge -> Lorenz, Weak -> True] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (KAmplitude[#1, Gauge -> \"RWZ\", Reconstruct -> True, SourceExpansion -> \"Full\"] & )[syms],\n\n Plus[Times[Rational[1, 2], Power[r, -2], Power[Plus[Times[6, M], Times[Plus[-2, l, Power[l, 2]], r]], -1], Plus[Times[24, Power[M, 2]], Times[6, Plus[-2, l, Power[l, 2]], M, r], Times[l, Plus[-2, Times[-1, l], Times[2, Power[l, 2]], Power[l, 3]], Power[r, 2]]], XZM[t, r]], Times[32, Power[l, -1], Power[Plus[1, l], -1], Pi, Power[r, 3], Power[Plus[Times[6, M], Times[Plus[-2, l, Power[l, 2]], r]], -1], \\[ScriptCapitalE], \\[Mu], Plus[Times[2, M], Times[-1, rp[t]]], Power[rp[t], -3], \\[Delta][Plus[r, Times[-1, rp[t]]]], Y[Rule[\"OverStr\", \"Bar\"]][t]], Times[Plus[1, Times[-2, M, Power[r, -1]]], Derivative[0, 1][XZM][t, r]]],\n\n TestID->\"(KAmplitude[#1, Gauge -> RWZ, Reconstruct -> True, SourceExpansion -> Full] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (GAmplitude[#1, Gauge -> \"Lorenz\", Weak -> True] & )[syms],\n\n Plus[Times[\\[Theta][Plus[Times[-1, r], rp[t]]], \\[ScriptCapitalG][Rule[\"Tags\", List[Rule[\"Up\", List[\"LorenzTag\", \"MinusTag\"]]]]][t, r]], Times[\\[Theta][Plus[r, Times[-1, rp[t]]]], \\[ScriptCapitalG][Rule[\"Tags\", List[Rule[\"Up\", List[\"LorenzTag\", \"PlusTag\"]]]]][t, r]]],\n\n TestID->\"(GAmplitude[#1, Gauge -> Lorenz, Weak -> True] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (HtAmplitude[#1, Gauge -> \"RWZ\", Reconstruct -> True, SourceExpansion -> \"Full\"] & )[syms],\n\n Plus[Times[Plus[Rational[1, 2], Times[-1, M, Power[r, -1]]], XCPM[t, r]], Times[Rational[1, 2], Plus[Times[-2, M], r], Derivative[0, 1][XCPM][t, r]], Times[16, Power[Plus[-1, l], -1], Power[l, -1], Power[Plus[1, l], -1], Power[Plus[2, l], -1], Pi, Power[r, 2], \\[ScriptCapitalL], \\[Mu], Plus[Times[2, M], Times[-1, rp[t]]], Power[rp[t], -3], \\[Delta][Plus[r, Times[-1, rp[t]]]], X[Rule[\"OverStr\", \"Bar\"]][Rule[\"Indices\", List[Rule[\"Down\", List[\"phi\"]]]]][t]]],\n\n TestID->\"(HtAmplitude[#1, Gauge -> RWZ, Reconstruct -> True, SourceExpansion -> Full] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (HrAmplitude[#1, Gauge -> \"RWZ\", Reconstruct -> True, SourceExpansion -> \"Full\"] & )[syms],\n\n Plus[Times[-1, Power[Plus[Times[4, M], Times[-2, r]], -1], Power[r, 2], Derivative[1, 0][XCPM][t, r]], Times[-16, Power[Plus[-1, l], -1], Power[l, -1], Power[Plus[1, l], -1], Power[Plus[2, l], -1], Pi, Power[r, 2], \\[ScriptCapitalL], \\[Mu], Power[Plus[Times[2, M], Times[-1, rp[t]]], -1], Power[rp[t], -1], \\[Delta][Plus[r, Times[-1, rp[t]]]], Derivative[1][rp][t], X[Rule[\"OverStr\", \"Bar\"]][Rule[\"Indices\", List[Rule[\"Down\", List[\"phi\"]]]]][t]]],\n\n TestID->\"(HrAmplitude[#1, Gauge -> RWZ, Reconstruct -> True, SourceExpansion -> Full] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (H2Amplitude[#1, Gauge -> \"Lorenz\", Weak -> True] & )[syms],\n\n Plus[Times[\\[Theta][Plus[Times[-1, r], rp[t]]], h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"LorenzTag\", \"MinusTag\"]]]]][t, r]], Times[\\[Theta][Plus[r, Times[-1, rp[t]]]], h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"LorenzTag\", \"PlusTag\"]]]]][t, r]]],\n\n TestID->\"(H2Amplitude[#1, Gauge -> Lorenz, Weak -> True] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (MasterFunction[#1, Variable -> \"CPM1\", Weak -> True] & )[syms],\n\n Plus[Times[\\[Theta][Plus[Times[-1, r], rp[t]]], XCPM1[Rule[\"Tags\", List[Rule[\"Up\", List[\"MinusTag\"]]]]][t, r]], Times[\\[Theta][Plus[r, Times[-1, rp[t]]]], XCPM1[Rule[\"Tags\", List[Rule[\"Up\", List[\"PlusTag\"]]]]][t, r]]],\n\n TestID->\"(MasterFunction[#1, Variable -> CPM1, Weak -> True] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (MasterFunction[#1, Variable -> \"ZM1\", Weak -> True] & )[syms],\n\n Plus[Times[\\[Theta][Plus[Times[-1, r], rp[t]]], XZM1[Rule[\"Tags\", List[Rule[\"Up\", List[\"MinusTag\"]]]]][t, r]], Times[\\[Theta][Plus[r, Times[-1, rp[t]]]], XZM1[Rule[\"Tags\", List[Rule[\"Up\", List[\"PlusTag\"]]]]][t, r]]],\n\n TestID->\"(MasterFunction[#1, Variable -> ZM1, Weak -> True] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (MasterFunction[#1, Variable -> \"JT1\", Weak -> True] & )[syms],\n\n Plus[Times[\\[Theta][Plus[Times[-1, r], rp[t]]], XJT1[Rule[\"Tags\", List[Rule[\"Up\", List[\"MinusTag\"]]]]][t, r]], Times[\\[Theta][Plus[r, Times[-1, rp[t]]]], XJT1[Rule[\"Tags\", List[Rule[\"Up\", List[\"PlusTag\"]]]]][t, r]]],\n\n TestID->\"(MasterFunction[#1, Variable -> JT1, Weak -> True] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (MasterFunction[#1, Parity -> \"Odd\", MPs -> True] & )[syms],\n\n Times[2, Power[Plus[-1, l], -1], Power[Plus[2, l], -1], r, Plus[Derivative[0, 1][h[Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"RWZTag\"]]]]]][t, r], Times[-1, Derivative[1, 0][h[Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"RWZTag\"]]]]]][t, r]], Times[-2, Power[r, -1], h[Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"RWZTag\"]]]]][t, r]]]],\n\n TestID->\"(MasterFunction[#1, Parity -> Odd, MPs -> True] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (MasterFunction[#1, Parity -> \"Odd\", MPs -> True, Gauge -> \"Undefined\", Weak -> True] & )[syms],\n\n Times[2, Power[Plus[-1, l], -1], Power[Plus[2, l], -1], r, Plus[Times[\\[Theta][Plus[Times[-1, r], rp[t]]], Derivative[0, 1][h[Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"GUTag\", \"MinusTag\"]]]]]][t, r]], Times[\\[Theta][Plus[r, Times[-1, rp[t]]]], Derivative[0, 1][h[Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"GUTag\", \"PlusTag\"]]]]]][t, r]], Times[-1, Power[r, -1], Plus[Times[-1, h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"GUTag\", \"PlusTag\"]]]]][t, r], Derivative[1][rp][t], Derivative[1][\\[Theta]][Plus[r, Times[-1, rp[t]]]]], Times[h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"GUTag\", \"MinusTag\"]]]]][t, r], Derivative[1][rp][t], Derivative[1][\\[Theta]][Plus[Times[-1, r], rp[t]]]], Times[\\[Theta][Plus[Times[-1, r], rp[t]]], Derivative[1, 0][h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"GUTag\", \"MinusTag\"]]]]]][t, r]], Times[\\[Theta][Plus[r, Times[-1, rp[t]]]], Derivative[1, 0][h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"GUTag\", \"PlusTag\"]]]]]][t, r]]]], Times[-1, \\[Theta][Plus[Times[-1, r], rp[t]]], Derivative[1, 0][h[Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"GUTag\", \"MinusTag\"]]]]]][t, r]], Times[-1, \\[Theta][Plus[r, Times[-1, rp[t]]]], Derivative[1, 0][h[Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"GUTag\", \"PlusTag\"]]]]]][t, r]], Times[Rational[1, 2], Plus[Times[h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"GUTag\", \"PlusTag\"]]]]][t, r], Derivative[1][rp][t], Derivative[2][\\[Theta]][Plus[r, Times[-1, rp[t]]]]], Times[h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"GUTag\", \"MinusTag\"]]]]][t, r], Derivative[1][rp][t], Derivative[2][\\[Theta]][Plus[Times[-1, r], rp[t]]]], Times[-1, Derivative[1][rp][t], Derivative[1][\\[Theta]][Plus[Times[-1, r], rp[t]]], Derivative[0, 1][h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"GUTag\", \"MinusTag\"]]]]]][t, r]], Times[Derivative[1][rp][t], Derivative[1][\\[Theta]][Plus[r, Times[-1, rp[t]]]], Derivative[0, 1][h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"GUTag\", \"PlusTag\"]]]]]][t, r]], Times[Derivative[1][\\[Theta]][Plus[Times[-1, r], rp[t]]], Derivative[1, 0][h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"GUTag\", \"MinusTag\"]]]]]][t, r]], Times[-1, Derivative[1][\\[Theta]][Plus[r, Times[-1, rp[t]]]], Derivative[1, 0][h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"GUTag\", \"PlusTag\"]]]]]][t, r]], Times[-1, \\[Theta][Plus[Times[-1, r], rp[t]]], Derivative[1, 1][h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"GUTag\", \"MinusTag\"]]]]]][t, r]], Times[-1, \\[Theta][Plus[r, Times[-1, rp[t]]]], Derivative[1, 1][h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"GUTag\", \"PlusTag\"]]]]]][t, r]]]], Times[Rational[1, 2], Plus[Times[-1, h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"GUTag\", \"PlusTag\"]]]]][t, r], Derivative[1][rp][t], Derivative[2][\\[Theta]][Plus[r, Times[-1, rp[t]]]]], Times[-1, h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"GUTag\", \"MinusTag\"]]]]][t, r], Derivative[1][rp][t], Derivative[2][\\[Theta]][Plus[Times[-1, r], rp[t]]]], Times[Derivative[1][rp][t], Derivative[1][\\[Theta]][Plus[Times[-1, r], rp[t]]], Derivative[0, 1][h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"GUTag\", \"MinusTag\"]]]]]][t, r]], Times[-1, Derivative[1][rp][t], Derivative[1][\\[Theta]][Plus[r, Times[-1, rp[t]]]], Derivative[0, 1][h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"GUTag\", \"PlusTag\"]]]]]][t, r]], Times[-1, Derivative[1][\\[Theta]][Plus[Times[-1, r], rp[t]]], Derivative[1, 0][h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"GUTag\", \"MinusTag\"]]]]]][t, r]], Times[Derivative[1][\\[Theta]][Plus[r, Times[-1, rp[t]]]], Derivative[1, 0][h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"GUTag\", \"PlusTag\"]]]]]][t, r]], Times[\\[Theta][Plus[Times[-1, r], rp[t]]], Derivative[1, 1][h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"GUTag\", \"MinusTag\"]]]]]][t, r]], Times[\\[Theta][Plus[r, Times[-1, rp[t]]]], Derivative[1, 1][h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"GUTag\", \"PlusTag\"]]]]]][t, r]]]], Times[-1, Derivative[1][rp][t], Derivative[1][\\[Theta]][Plus[Times[-1, r], rp[t]]], h[Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"GUTag\", \"MinusTag\"]]]]][t, r]], Times[Derivative[1][rp][t], Derivative[1][\\[Theta]][Plus[r, Times[-1, rp[t]]]], h[Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"GUTag\", \"PlusTag\"]]]]][t, r]], Times[-1, Derivative[1][\\[Theta]][Plus[Times[-1, r], rp[t]]], h[Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"GUTag\", \"MinusTag\"]]]]][t, r]], Times[Derivative[1][\\[Theta]][Plus[r, Times[-1, rp[t]]]], h[Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"GUTag\", \"PlusTag\"]]]]][t, r]], Times[-2, Power[r, -1], Plus[Times[Rational[1, 2], Plus[Times[h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"GUTag\", \"PlusTag\"]]]]][t, r], Derivative[1][rp][t], Derivative[1][\\[Theta]][Plus[r, Times[-1, rp[t]]]]], Times[-1, h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"GUTag\", \"MinusTag\"]]]]][t, r], Derivative[1][rp][t], Derivative[1][\\[Theta]][Plus[Times[-1, r], rp[t]]]], Times[-1, \\[Theta][Plus[Times[-1, r], rp[t]]], Derivative[1, 0][h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"GUTag\", \"MinusTag\"]]]]]][t, r]], Times[-1, \\[Theta][Plus[r, Times[-1, rp[t]]]], Derivative[1, 0][h[Rule[\"Tags\", List[Rule[\"Down\", List[\"2Tag\"]], Rule[\"Up\", List[\"GUTag\", \"PlusTag\"]]]]]][t, r]]]], Times[\\[Theta][Plus[Times[-1, r], rp[t]]], h[Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"GUTag\", \"MinusTag\"]]]]][t, r]], Times[\\[Theta][Plus[r, Times[-1, rp[t]]]], h[Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"GUTag\", \"PlusTag\"]]]]][t, r]]]]]],\n\n TestID->\"(MasterFunction[#1, Parity -> Odd, MPs -> True, Gauge -> Undefined, Weak -> True] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (XiEvenAmplitude[#1, Weak -> True] & )[syms],\n\n Plus[Times[\\[Theta][Plus[Times[-1, r], rp[t]]], \\[Xi][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\", \"MinusTag\"]]]]][t, r]], Times[\\[Theta][Plus[r, Times[-1, rp[t]]]], \\[Xi][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\", \"PlusTag\"]]]]][t, r]]],\n\n TestID->\"(XiEvenAmplitude[#1, Weak -> True] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (XiEvenTAmplitude[#1, Weak -> True] & )[syms],\n\n Plus[Times[\\[Theta][Plus[Times[-1, r], rp[t]]], \\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\", \"MinusTag\"]]]]][t, r]], Times[\\[Theta][Plus[r, Times[-1, rp[t]]]], \\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\", \"PlusTag\"]]]]][t, r]]],\n\n TestID->\"(XiEvenTAmplitude[#1, Weak -> True] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (XiEvenRAmplitude[#1, Weak -> True] & )[syms],\n\n Plus[Times[\\[Theta][Plus[Times[-1, r], rp[t]]], \\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\", \"MinusTag\"]]]]][t, r]], Times[\\[Theta][Plus[r, Times[-1, rp[t]]]], \\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\", \"PlusTag\"]]]]][t, r]]],\n\n TestID->\"(XiEvenRAmplitude[#1, Weak -> True] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (XiOddAmplitude[#1, Weak -> True] & )[syms],\n\n Plus[Times[\\[Theta][Plus[Times[-1, r], rp[t]]], \\[Xi][Rule[\"Tags\", List[Rule[\"Up\", List[\"OddTag\", \"RWZTag\", \"LorenzTag\", \"MinusTag\"]]]]][t, r]], Times[\\[Theta][Plus[r, Times[-1, rp[t]]]], \\[Xi][Rule[\"Tags\", List[Rule[\"Up\", List[\"OddTag\", \"RWZTag\", \"LorenzTag\", \"PlusTag\"]]]]][t, r]]],\n\n TestID->\"(XiOddAmplitude[#1, Weak -> True] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (HttPush[#1, Weak -> True] & )[syms],\n\n Plus[Times[2, M, Plus[1, Times[-2, M, Power[r, -1]]], Power[r, -2], Plus[Times[\\[Theta][Plus[Times[-1, r], rp[t]]], \\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\", \"MinusTag\"]]]]][t, r]], Times[\\[Theta][Plus[r, Times[-1, rp[t]]]], \\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\", \"PlusTag\"]]]]][t, r]]]], Times[-2, Plus[Times[\\[Theta][Plus[Times[-1, r], rp[t]]], Derivative[1, 0][\\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\", \"MinusTag\"]]]]]][t, r]], Times[\\[Theta][Plus[r, Times[-1, rp[t]]]], Derivative[1, 0][\\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\", \"PlusTag\"]]]]]][t, r]], Times[Derivative[1][rp][t], Derivative[1][\\[Theta]][Plus[Times[-1, r], rp[t]]], \\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\", \"MinusTag\"]]]]][t, r]], Times[-1, Derivative[1][rp][t], Derivative[1][\\[Theta]][Plus[r, Times[-1, rp[t]]]], \\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\", \"PlusTag\"]]]]][t, r]]]]],\n\n TestID->\"(HttPush[#1, Weak -> True] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (HttPush[#1] & )[syms],\n\n Plus[Times[-2, Derivative[1, 0][\\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\"]]]]]][t, r]], Times[2, M, Plus[1, Times[-2, M, Power[r, -1]]], Power[r, -2], \\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\"]]]]][t, r]]],\n\n TestID->\"(HttPush[#1] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (HtrPush[#1, Weak -> True] & )[syms],\n\n Plus[Times[-1, \\[Theta][Plus[Times[-1, r], rp[t]]], Derivative[0, 1][\\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\", \"MinusTag\"]]]]]][t, r]], Times[-1, \\[Theta][Plus[r, Times[-1, rp[t]]]], Derivative[0, 1][\\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\", \"PlusTag\"]]]]]][t, r]], Times[-1, \\[Theta][Plus[Times[-1, r], rp[t]]], Derivative[1, 0][\\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\", \"MinusTag\"]]]]]][t, r]], Times[-1, \\[Theta][Plus[r, Times[-1, rp[t]]]], Derivative[1, 0][\\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\", \"PlusTag\"]]]]]][t, r]], Times[-1, Derivative[1][rp][t], Derivative[1][\\[Theta]][Plus[Times[-1, r], rp[t]]], \\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\", \"MinusTag\"]]]]][t, r]], Times[Derivative[1][rp][t], Derivative[1][\\[Theta]][Plus[r, Times[-1, rp[t]]]], \\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\", \"PlusTag\"]]]]][t, r]], Times[Derivative[1][\\[Theta]][Plus[Times[-1, r], rp[t]]], \\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\", \"MinusTag\"]]]]][t, r]], Times[-1, Derivative[1][\\[Theta]][Plus[r, Times[-1, rp[t]]]], \\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\", \"PlusTag\"]]]]][t, r]], Times[2, M, Power[Plus[1, Times[-2, M, Power[r, -1]]], -1], Power[r, -2], Plus[Times[\\[Theta][Plus[Times[-1, r], rp[t]]], \\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\", \"MinusTag\"]]]]][t, r]], Times[\\[Theta][Plus[r, Times[-1, rp[t]]]], \\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"t\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\", \"PlusTag\"]]]]][t, r]]]]],\n\n TestID->\"(HtrPush[#1, Weak -> True] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (HrrPush[#1] & )[syms],\n\n Plus[Times[-2, Derivative[0, 1][\\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\"]]]]]][t, r]], Times[-2, M, Power[Plus[1, Times[-2, M, Power[r, -1]]], -1], Power[r, -2], \\[Xi][Rule[\"Indices\", List[Rule[\"Down\", List[\"r\"]]]]][Rule[\"Tags\", List[Rule[\"Up\", List[\"EvenTag\", \"RWZTag\", \"LorenzTag\"]]]]][t, r]]],\n\n TestID->\"(HrrPush[#1] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (HtPush[#1] & )[syms],\n\n Times[-1, Derivative[1, 0][\\[Xi][Rule[\"Tags\", List[Rule[\"Up\", List[\"OddTag\", \"RWZTag\", \"LorenzTag\"]]]]]][t, r]],\n\n TestID->\"(HtPush[#1] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n\nTest[\n (HrPush[#1, Weak -> True] & )[syms],\n\n Plus[Times[2, Power[r, -1], Plus[Times[\\[Theta][Plus[Times[-1, r], rp[t]]], \\[Xi][Rule[\"Tags\", List[Rule[\"Up\", List[\"OddTag\", \"RWZTag\", \"LorenzTag\", \"MinusTag\"]]]]][t, r]], Times[\\[Theta][Plus[r, Times[-1, rp[t]]]], \\[Xi][Rule[\"Tags\", List[Rule[\"Up\", List[\"OddTag\", \"RWZTag\", \"LorenzTag\", \"PlusTag\"]]]]][t, r]]]], Times[-1, \\[Xi][Rule[\"Tags\", List[Rule[\"Up\", List[\"OddTag\", \"RWZTag\", \"LorenzTag\", \"PlusTag\"]]]]][t, r], Derivative[1][\\[Theta]][Plus[r, Times[-1, rp[t]]]]], Times[\\[Xi][Rule[\"Tags\", List[Rule[\"Up\", List[\"OddTag\", \"RWZTag\", \"LorenzTag\", \"MinusTag\"]]]]][t, r], Derivative[1][\\[Theta]][Plus[Times[-1, r], rp[t]]]], Times[-1, \\[Theta][Plus[Times[-1, r], rp[t]]], Derivative[0, 1][\\[Xi][Rule[\"Tags\", List[Rule[\"Up\", List[\"OddTag\", \"RWZTag\", \"LorenzTag\", \"MinusTag\"]]]]]][t, r]], Times[-1, \\[Theta][Plus[r, Times[-1, rp[t]]]], Derivative[0, 1][\\[Xi][Rule[\"Tags\", List[Rule[\"Up\", List[\"OddTag\", \"RWZTag\", \"LorenzTag\", \"PlusTag\"]]]]]][t, r]]],\n\n TestID->\"(HrPush[#1, Weak -> True] & )[syms]\",\n\n EquivalenceFunction->(If[MatchQ[Head[#1],List],Simplify[#1-#2]==Table[0,{Length@#1}],Simplify[#1-#2]== 0]&)\n]\n\n","avg_line_length":63.377443609,"max_line_length":6193,"alphanum_fraction":0.5703744128} {"size":10865,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 16;\nname = \"16v4 2 1 2 2 3 1 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-15 I y] (2 (I Sin[x])^8 Cos[x]^8) + Exp[-13 I y] (4 (I Sin[x])^7 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^7 + 2 (I Sin[x])^8 Cos[x]^8 + 5 (I Sin[x])^6 Cos[x]^10 + 5 (I Sin[x])^10 Cos[x]^6 + 4 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^5 + 1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4) + Exp[-11 I y] (48 (I Sin[x])^9 Cos[x]^7 + 48 (I Sin[x])^7 Cos[x]^9 + 44 (I Sin[x])^8 Cos[x]^8 + 26 (I Sin[x])^10 Cos[x]^6 + 26 (I Sin[x])^6 Cos[x]^10 + 8 (I Sin[x])^11 Cos[x]^5 + 8 (I Sin[x])^5 Cos[x]^11 + 1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4) + Exp[-9 I y] (116 (I Sin[x])^6 Cos[x]^10 + 116 (I Sin[x])^10 Cos[x]^6 + 143 (I Sin[x])^7 Cos[x]^9 + 143 (I Sin[x])^9 Cos[x]^7 + 71 (I Sin[x])^5 Cos[x]^11 + 71 (I Sin[x])^11 Cos[x]^5 + 158 (I Sin[x])^8 Cos[x]^8 + 35 (I Sin[x])^4 Cos[x]^12 + 35 (I Sin[x])^12 Cos[x]^4 + 10 (I Sin[x])^3 Cos[x]^13 + 10 (I Sin[x])^13 Cos[x]^3 + 1 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^2) + Exp[-7 I y] (598 (I Sin[x])^8 Cos[x]^8 + 333 (I Sin[x])^10 Cos[x]^6 + 333 (I Sin[x])^6 Cos[x]^10 + 489 (I Sin[x])^7 Cos[x]^9 + 489 (I Sin[x])^9 Cos[x]^7 + 171 (I Sin[x])^11 Cos[x]^5 + 171 (I Sin[x])^5 Cos[x]^11 + 60 (I Sin[x])^12 Cos[x]^4 + 60 (I Sin[x])^4 Cos[x]^12 + 12 (I Sin[x])^3 Cos[x]^13 + 12 (I Sin[x])^13 Cos[x]^3 + 1 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^2) + Exp[-5 I y] (434 (I Sin[x])^5 Cos[x]^11 + 434 (I Sin[x])^11 Cos[x]^5 + 1005 (I Sin[x])^7 Cos[x]^9 + 1005 (I Sin[x])^9 Cos[x]^7 + 1102 (I Sin[x])^8 Cos[x]^8 + 725 (I Sin[x])^6 Cos[x]^10 + 725 (I Sin[x])^10 Cos[x]^6 + 197 (I Sin[x])^4 Cos[x]^12 + 197 (I Sin[x])^12 Cos[x]^4 + 71 (I Sin[x])^3 Cos[x]^13 + 71 (I Sin[x])^13 Cos[x]^3 + 18 (I Sin[x])^2 Cos[x]^14 + 18 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[-3 I y] (1836 (I Sin[x])^9 Cos[x]^7 + 1836 (I Sin[x])^7 Cos[x]^9 + 617 (I Sin[x])^11 Cos[x]^5 + 617 (I Sin[x])^5 Cos[x]^11 + 2022 (I Sin[x])^8 Cos[x]^8 + 1228 (I Sin[x])^10 Cos[x]^6 + 1228 (I Sin[x])^6 Cos[x]^10 + 234 (I Sin[x])^4 Cos[x]^12 + 234 (I Sin[x])^12 Cos[x]^4 + 66 (I Sin[x])^13 Cos[x]^3 + 66 (I Sin[x])^3 Cos[x]^13 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[-1 I y] (1572 (I Sin[x])^6 Cos[x]^10 + 1572 (I Sin[x])^10 Cos[x]^6 + 444 (I Sin[x])^4 Cos[x]^12 + 444 (I Sin[x])^12 Cos[x]^4 + 2350 (I Sin[x])^8 Cos[x]^8 + 2107 (I Sin[x])^7 Cos[x]^9 + 2107 (I Sin[x])^9 Cos[x]^7 + 924 (I Sin[x])^5 Cos[x]^11 + 924 (I Sin[x])^11 Cos[x]^5 + 160 (I Sin[x])^3 Cos[x]^13 + 160 (I Sin[x])^13 Cos[x]^3 + 43 (I Sin[x])^2 Cos[x]^14 + 43 (I Sin[x])^14 Cos[x]^2 + 9 (I Sin[x])^1 Cos[x]^15 + 9 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[1 I y] (2674 (I Sin[x])^8 Cos[x]^8 + 1567 (I Sin[x])^10 Cos[x]^6 + 1567 (I Sin[x])^6 Cos[x]^10 + 2291 (I Sin[x])^7 Cos[x]^9 + 2291 (I Sin[x])^9 Cos[x]^7 + 318 (I Sin[x])^12 Cos[x]^4 + 318 (I Sin[x])^4 Cos[x]^12 + 826 (I Sin[x])^11 Cos[x]^5 + 826 (I Sin[x])^5 Cos[x]^11 + 82 (I Sin[x])^3 Cos[x]^13 + 82 (I Sin[x])^13 Cos[x]^3 + 13 (I Sin[x])^2 Cos[x]^14 + 13 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^15 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^15) + Exp[3 I y] (732 (I Sin[x])^5 Cos[x]^11 + 732 (I Sin[x])^11 Cos[x]^5 + 1669 (I Sin[x])^7 Cos[x]^9 + 1669 (I Sin[x])^9 Cos[x]^7 + 1822 (I Sin[x])^8 Cos[x]^8 + 1215 (I Sin[x])^6 Cos[x]^10 + 1215 (I Sin[x])^10 Cos[x]^6 + 116 (I Sin[x])^3 Cos[x]^13 + 116 (I Sin[x])^13 Cos[x]^3 + 331 (I Sin[x])^4 Cos[x]^12 + 331 (I Sin[x])^12 Cos[x]^4 + 28 (I Sin[x])^2 Cos[x]^14 + 28 (I Sin[x])^14 Cos[x]^2 + 3 (I Sin[x])^1 Cos[x]^15 + 3 (I Sin[x])^15 Cos[x]^1) + Exp[5 I y] (1152 (I Sin[x])^9 Cos[x]^7 + 1152 (I Sin[x])^7 Cos[x]^9 + 339 (I Sin[x])^11 Cos[x]^5 + 339 (I Sin[x])^5 Cos[x]^11 + 744 (I Sin[x])^6 Cos[x]^10 + 744 (I Sin[x])^10 Cos[x]^6 + 1280 (I Sin[x])^8 Cos[x]^8 + 105 (I Sin[x])^4 Cos[x]^12 + 105 (I Sin[x])^12 Cos[x]^4 + 21 (I Sin[x])^3 Cos[x]^13 + 21 (I Sin[x])^13 Cos[x]^3 + 2 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^14) + Exp[7 I y] (81 (I Sin[x])^4 Cos[x]^12 + 81 (I Sin[x])^12 Cos[x]^4 + 345 (I Sin[x])^6 Cos[x]^10 + 345 (I Sin[x])^10 Cos[x]^6 + 530 (I Sin[x])^8 Cos[x]^8 + 465 (I Sin[x])^7 Cos[x]^9 + 465 (I Sin[x])^9 Cos[x]^7 + 186 (I Sin[x])^5 Cos[x]^11 + 186 (I Sin[x])^11 Cos[x]^5 + 21 (I Sin[x])^3 Cos[x]^13 + 21 (I Sin[x])^13 Cos[x]^3 + 2 (I Sin[x])^2 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^2) + Exp[9 I y] (238 (I Sin[x])^8 Cos[x]^8 + 102 (I Sin[x])^10 Cos[x]^6 + 102 (I Sin[x])^6 Cos[x]^10 + 183 (I Sin[x])^7 Cos[x]^9 + 183 (I Sin[x])^9 Cos[x]^7 + 40 (I Sin[x])^5 Cos[x]^11 + 40 (I Sin[x])^11 Cos[x]^5 + 10 (I Sin[x])^12 Cos[x]^4 + 10 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^13 Cos[x]^3 + 1 (I Sin[x])^3 Cos[x]^13) + Exp[11 I y] (15 (I Sin[x])^5 Cos[x]^11 + 15 (I Sin[x])^11 Cos[x]^5 + 41 (I Sin[x])^7 Cos[x]^9 + 41 (I Sin[x])^9 Cos[x]^7 + 42 (I Sin[x])^8 Cos[x]^8 + 25 (I Sin[x])^6 Cos[x]^10 + 25 (I Sin[x])^10 Cos[x]^6 + 3 (I Sin[x])^4 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^4) + Exp[13 I y] (7 (I Sin[x])^9 Cos[x]^7 + 7 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^11 Cos[x]^5 + 1 (I Sin[x])^5 Cos[x]^11 + 6 (I Sin[x])^8 Cos[x]^8 + 4 (I Sin[x])^10 Cos[x]^6 + 4 (I Sin[x])^6 Cos[x]^10) + Exp[15 I y] (1 (I Sin[x])^6 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^6))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-15 I y] (2 (I Sin[x])^8 Cos[x]^8) + Exp[-13 I y] (4 (I Sin[x])^7 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^7 + 2 (I Sin[x])^8 Cos[x]^8 + 5 (I Sin[x])^6 Cos[x]^10 + 5 (I Sin[x])^10 Cos[x]^6 + 4 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^5 + 1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4) + Exp[-11 I y] (48 (I Sin[x])^9 Cos[x]^7 + 48 (I Sin[x])^7 Cos[x]^9 + 44 (I Sin[x])^8 Cos[x]^8 + 26 (I Sin[x])^10 Cos[x]^6 + 26 (I Sin[x])^6 Cos[x]^10 + 8 (I Sin[x])^11 Cos[x]^5 + 8 (I Sin[x])^5 Cos[x]^11 + 1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4) + Exp[-9 I y] (116 (I Sin[x])^6 Cos[x]^10 + 116 (I Sin[x])^10 Cos[x]^6 + 143 (I Sin[x])^7 Cos[x]^9 + 143 (I Sin[x])^9 Cos[x]^7 + 71 (I Sin[x])^5 Cos[x]^11 + 71 (I Sin[x])^11 Cos[x]^5 + 158 (I Sin[x])^8 Cos[x]^8 + 35 (I Sin[x])^4 Cos[x]^12 + 35 (I Sin[x])^12 Cos[x]^4 + 10 (I Sin[x])^3 Cos[x]^13 + 10 (I Sin[x])^13 Cos[x]^3 + 1 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^2) + Exp[-7 I y] (598 (I Sin[x])^8 Cos[x]^8 + 333 (I Sin[x])^10 Cos[x]^6 + 333 (I Sin[x])^6 Cos[x]^10 + 489 (I Sin[x])^7 Cos[x]^9 + 489 (I Sin[x])^9 Cos[x]^7 + 171 (I Sin[x])^11 Cos[x]^5 + 171 (I Sin[x])^5 Cos[x]^11 + 60 (I Sin[x])^12 Cos[x]^4 + 60 (I Sin[x])^4 Cos[x]^12 + 12 (I Sin[x])^3 Cos[x]^13 + 12 (I Sin[x])^13 Cos[x]^3 + 1 (I Sin[x])^2 Cos[x]^14 + 1 (I Sin[x])^14 Cos[x]^2) + Exp[-5 I y] (434 (I Sin[x])^5 Cos[x]^11 + 434 (I Sin[x])^11 Cos[x]^5 + 1005 (I Sin[x])^7 Cos[x]^9 + 1005 (I Sin[x])^9 Cos[x]^7 + 1102 (I Sin[x])^8 Cos[x]^8 + 725 (I Sin[x])^6 Cos[x]^10 + 725 (I Sin[x])^10 Cos[x]^6 + 197 (I Sin[x])^4 Cos[x]^12 + 197 (I Sin[x])^12 Cos[x]^4 + 71 (I Sin[x])^3 Cos[x]^13 + 71 (I Sin[x])^13 Cos[x]^3 + 18 (I Sin[x])^2 Cos[x]^14 + 18 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[-3 I y] (1836 (I Sin[x])^9 Cos[x]^7 + 1836 (I Sin[x])^7 Cos[x]^9 + 617 (I Sin[x])^11 Cos[x]^5 + 617 (I Sin[x])^5 Cos[x]^11 + 2022 (I Sin[x])^8 Cos[x]^8 + 1228 (I Sin[x])^10 Cos[x]^6 + 1228 (I Sin[x])^6 Cos[x]^10 + 234 (I Sin[x])^4 Cos[x]^12 + 234 (I Sin[x])^12 Cos[x]^4 + 66 (I Sin[x])^13 Cos[x]^3 + 66 (I Sin[x])^3 Cos[x]^13 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^15 + 1 (I Sin[x])^15 Cos[x]^1) + Exp[-1 I y] (1572 (I Sin[x])^6 Cos[x]^10 + 1572 (I Sin[x])^10 Cos[x]^6 + 444 (I Sin[x])^4 Cos[x]^12 + 444 (I Sin[x])^12 Cos[x]^4 + 2350 (I Sin[x])^8 Cos[x]^8 + 2107 (I Sin[x])^7 Cos[x]^9 + 2107 (I Sin[x])^9 Cos[x]^7 + 924 (I Sin[x])^5 Cos[x]^11 + 924 (I Sin[x])^11 Cos[x]^5 + 160 (I Sin[x])^3 Cos[x]^13 + 160 (I Sin[x])^13 Cos[x]^3 + 43 (I Sin[x])^2 Cos[x]^14 + 43 (I Sin[x])^14 Cos[x]^2 + 9 (I Sin[x])^1 Cos[x]^15 + 9 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[1 I y] (2674 (I Sin[x])^8 Cos[x]^8 + 1567 (I Sin[x])^10 Cos[x]^6 + 1567 (I Sin[x])^6 Cos[x]^10 + 2291 (I Sin[x])^7 Cos[x]^9 + 2291 (I Sin[x])^9 Cos[x]^7 + 318 (I Sin[x])^12 Cos[x]^4 + 318 (I Sin[x])^4 Cos[x]^12 + 826 (I Sin[x])^11 Cos[x]^5 + 826 (I Sin[x])^5 Cos[x]^11 + 82 (I Sin[x])^3 Cos[x]^13 + 82 (I Sin[x])^13 Cos[x]^3 + 13 (I Sin[x])^2 Cos[x]^14 + 13 (I Sin[x])^14 Cos[x]^2 + 1 (I Sin[x])^15 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^15) + Exp[3 I y] (732 (I Sin[x])^5 Cos[x]^11 + 732 (I Sin[x])^11 Cos[x]^5 + 1669 (I Sin[x])^7 Cos[x]^9 + 1669 (I Sin[x])^9 Cos[x]^7 + 1822 (I Sin[x])^8 Cos[x]^8 + 1215 (I Sin[x])^6 Cos[x]^10 + 1215 (I Sin[x])^10 Cos[x]^6 + 116 (I Sin[x])^3 Cos[x]^13 + 116 (I Sin[x])^13 Cos[x]^3 + 331 (I Sin[x])^4 Cos[x]^12 + 331 (I Sin[x])^12 Cos[x]^4 + 28 (I Sin[x])^2 Cos[x]^14 + 28 (I Sin[x])^14 Cos[x]^2 + 3 (I Sin[x])^1 Cos[x]^15 + 3 (I Sin[x])^15 Cos[x]^1) + Exp[5 I y] (1152 (I Sin[x])^9 Cos[x]^7 + 1152 (I Sin[x])^7 Cos[x]^9 + 339 (I Sin[x])^11 Cos[x]^5 + 339 (I Sin[x])^5 Cos[x]^11 + 744 (I Sin[x])^6 Cos[x]^10 + 744 (I Sin[x])^10 Cos[x]^6 + 1280 (I Sin[x])^8 Cos[x]^8 + 105 (I Sin[x])^4 Cos[x]^12 + 105 (I Sin[x])^12 Cos[x]^4 + 21 (I Sin[x])^3 Cos[x]^13 + 21 (I Sin[x])^13 Cos[x]^3 + 2 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^14) + Exp[7 I y] (81 (I Sin[x])^4 Cos[x]^12 + 81 (I Sin[x])^12 Cos[x]^4 + 345 (I Sin[x])^6 Cos[x]^10 + 345 (I Sin[x])^10 Cos[x]^6 + 530 (I Sin[x])^8 Cos[x]^8 + 465 (I Sin[x])^7 Cos[x]^9 + 465 (I Sin[x])^9 Cos[x]^7 + 186 (I Sin[x])^5 Cos[x]^11 + 186 (I Sin[x])^11 Cos[x]^5 + 21 (I Sin[x])^3 Cos[x]^13 + 21 (I Sin[x])^13 Cos[x]^3 + 2 (I Sin[x])^2 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^2) + Exp[9 I y] (238 (I Sin[x])^8 Cos[x]^8 + 102 (I Sin[x])^10 Cos[x]^6 + 102 (I Sin[x])^6 Cos[x]^10 + 183 (I Sin[x])^7 Cos[x]^9 + 183 (I Sin[x])^9 Cos[x]^7 + 40 (I Sin[x])^5 Cos[x]^11 + 40 (I Sin[x])^11 Cos[x]^5 + 10 (I Sin[x])^12 Cos[x]^4 + 10 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^13 Cos[x]^3 + 1 (I Sin[x])^3 Cos[x]^13) + Exp[11 I y] (15 (I Sin[x])^5 Cos[x]^11 + 15 (I Sin[x])^11 Cos[x]^5 + 41 (I Sin[x])^7 Cos[x]^9 + 41 (I Sin[x])^9 Cos[x]^7 + 42 (I Sin[x])^8 Cos[x]^8 + 25 (I Sin[x])^6 Cos[x]^10 + 25 (I Sin[x])^10 Cos[x]^6 + 3 (I Sin[x])^4 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^4) + Exp[13 I y] (7 (I Sin[x])^9 Cos[x]^7 + 7 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^11 Cos[x]^5 + 1 (I Sin[x])^5 Cos[x]^11 + 6 (I Sin[x])^8 Cos[x]^8 + 4 (I Sin[x])^10 Cos[x]^6 + 4 (I Sin[x])^6 Cos[x]^10) + Exp[15 I y] (1 (I Sin[x])^6 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^6));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":724.3333333333,"max_line_length":5210,"alphanum_fraction":0.5046479521} {"size":5979,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 12;\nname = \"12v1 1 5 4 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-11 I y] (1 (I Sin[x])^5 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^5) + Exp[-9 I y] (6 (I Sin[x])^6 Cos[x]^6 + 3 (I Sin[x])^5 Cos[x]^7 + 3 (I Sin[x])^7 Cos[x]^5 + 2 (I Sin[x])^4 Cos[x]^8 + 2 (I Sin[x])^8 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^9 + 2 (I Sin[x])^9 Cos[x]^3 + 1 (I Sin[x])^2 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^2) + Exp[-7 I y] (15 (I Sin[x])^4 Cos[x]^8 + 15 (I Sin[x])^8 Cos[x]^4 + 22 (I Sin[x])^6 Cos[x]^6 + 9 (I Sin[x])^3 Cos[x]^9 + 9 (I Sin[x])^9 Cos[x]^3 + 15 (I Sin[x])^5 Cos[x]^7 + 15 (I Sin[x])^7 Cos[x]^5 + 4 (I Sin[x])^2 Cos[x]^10 + 4 (I Sin[x])^10 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^1) + Exp[-5 I y] (59 (I Sin[x])^5 Cos[x]^7 + 59 (I Sin[x])^7 Cos[x]^5 + 46 (I Sin[x])^4 Cos[x]^8 + 46 (I Sin[x])^8 Cos[x]^4 + 52 (I Sin[x])^6 Cos[x]^6 + 24 (I Sin[x])^3 Cos[x]^9 + 24 (I Sin[x])^9 Cos[x]^3 + 8 (I Sin[x])^2 Cos[x]^10 + 8 (I Sin[x])^10 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^1) + Exp[-3 I y] (42 (I Sin[x])^3 Cos[x]^9 + 42 (I Sin[x])^9 Cos[x]^3 + 124 (I Sin[x])^5 Cos[x]^7 + 124 (I Sin[x])^7 Cos[x]^5 + 15 (I Sin[x])^2 Cos[x]^10 + 15 (I Sin[x])^10 Cos[x]^2 + 126 (I Sin[x])^6 Cos[x]^6 + 81 (I Sin[x])^4 Cos[x]^8 + 81 (I Sin[x])^8 Cos[x]^4 + 4 (I Sin[x])^1 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^1 + 1 Cos[x]^12 + 1 (I Sin[x])^12) + Exp[-1 I y] (110 (I Sin[x])^4 Cos[x]^8 + 110 (I Sin[x])^8 Cos[x]^4 + 230 (I Sin[x])^6 Cos[x]^6 + 180 (I Sin[x])^5 Cos[x]^7 + 180 (I Sin[x])^7 Cos[x]^5 + 46 (I Sin[x])^3 Cos[x]^9 + 46 (I Sin[x])^9 Cos[x]^3 + 11 (I Sin[x])^2 Cos[x]^10 + 11 (I Sin[x])^10 Cos[x]^2) + Exp[1 I y] (108 (I Sin[x])^4 Cos[x]^8 + 108 (I Sin[x])^8 Cos[x]^4 + 216 (I Sin[x])^6 Cos[x]^6 + 51 (I Sin[x])^3 Cos[x]^9 + 51 (I Sin[x])^9 Cos[x]^3 + 170 (I Sin[x])^7 Cos[x]^5 + 170 (I Sin[x])^5 Cos[x]^7 + 20 (I Sin[x])^2 Cos[x]^10 + 20 (I Sin[x])^10 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^11 + 5 (I Sin[x])^11 Cos[x]^1) + Exp[3 I y] (152 (I Sin[x])^5 Cos[x]^7 + 152 (I Sin[x])^7 Cos[x]^5 + 18 (I Sin[x])^3 Cos[x]^9 + 18 (I Sin[x])^9 Cos[x]^3 + 172 (I Sin[x])^6 Cos[x]^6 + 74 (I Sin[x])^4 Cos[x]^8 + 74 (I Sin[x])^8 Cos[x]^4) + Exp[5 I y] (59 (I Sin[x])^5 Cos[x]^7 + 59 (I Sin[x])^7 Cos[x]^5 + 46 (I Sin[x])^4 Cos[x]^8 + 46 (I Sin[x])^8 Cos[x]^4 + 54 (I Sin[x])^6 Cos[x]^6 + 26 (I Sin[x])^3 Cos[x]^9 + 26 (I Sin[x])^9 Cos[x]^3 + 7 (I Sin[x])^2 Cos[x]^10 + 7 (I Sin[x])^10 Cos[x]^2) + Exp[7 I y] (44 (I Sin[x])^6 Cos[x]^6 + 8 (I Sin[x])^4 Cos[x]^8 + 8 (I Sin[x])^8 Cos[x]^4 + 25 (I Sin[x])^7 Cos[x]^5 + 25 (I Sin[x])^5 Cos[x]^7) + Exp[9 I y] (2 (I Sin[x])^6 Cos[x]^6 + 5 (I Sin[x])^4 Cos[x]^8 + 5 (I Sin[x])^8 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^9 + 2 (I Sin[x])^9 Cos[x]^3 + 3 (I Sin[x])^5 Cos[x]^7 + 3 (I Sin[x])^7 Cos[x]^5) + Exp[11 I y] (1 (I Sin[x])^5 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^5))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-11 I y] (1 (I Sin[x])^5 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^5) + Exp[-9 I y] (6 (I Sin[x])^6 Cos[x]^6 + 3 (I Sin[x])^5 Cos[x]^7 + 3 (I Sin[x])^7 Cos[x]^5 + 2 (I Sin[x])^4 Cos[x]^8 + 2 (I Sin[x])^8 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^9 + 2 (I Sin[x])^9 Cos[x]^3 + 1 (I Sin[x])^2 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^2) + Exp[-7 I y] (15 (I Sin[x])^4 Cos[x]^8 + 15 (I Sin[x])^8 Cos[x]^4 + 22 (I Sin[x])^6 Cos[x]^6 + 9 (I Sin[x])^3 Cos[x]^9 + 9 (I Sin[x])^9 Cos[x]^3 + 15 (I Sin[x])^5 Cos[x]^7 + 15 (I Sin[x])^7 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Sin[x])^6 Cos[x]^6 + 5 (I Sin[x])^4 Cos[x]^8 + 5 (I Sin[x])^8 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^9 + 2 (I Sin[x])^9 Cos[x]^3 + 3 (I Sin[x])^5 Cos[x]^7 + 3 (I Sin[x])^7 Cos[x]^5) + Exp[11 I y] (1 (I Sin[x])^5 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^5));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":398.6,"max_line_length":2770,"alphanum_fraction":0.489713999} {"size":33179,"ext":"nb","lang":"Mathematica","max_stars_count":25.0,"content":"(* Content-type: application\/vnd.wolfram.mathematica *)\n\n(*** Wolfram Notebook File ***)\n(* http:\/\/www.wolfram.com\/nb *)\n\n(* CreatedBy='Mathematica 11.3' 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0.5]}},ExpressionUUID->\"ea7b983e-4506-441f-95f8-a862c0e5a470\"]\n}, Closed]],\n\nCell[CellGroupData[{\n\nCell[\"Gray3\", \"Subsection\",ExpressionUUID->\"15b6a24b-4d6b-48bd-aeca-87d308eb4985\"],\n\nCell[StyleData[\"ButtonGray3Normal\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->GrayLevel[\n 1\/5],ExpressionUUID->\"39c5e9da-3c70-4ae3-bb2b-3420361c879b\"],\n\nCell[StyleData[\"ButtonGray3Hover\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->GrayLevel[1\/5],\n Background->GrayLevel[1],\n FrameBoxOptions->{FrameStyle->{\n GrayLevel[\n 166\/255]}},ExpressionUUID->\"f193edae-9597-471a-b3af-fd7e39dc2784\"],\n\nCell[StyleData[\"ButtonGray3Pressed\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->GrayLevel[1\/5],\n Background->GrayLevel[229\/255],\n FrameBoxOptions->{FrameStyle->{\n GrayLevel[\n 166\/255]}},ExpressionUUID->\"b796f87e-105d-4044-b257-077048090b23\"],\n\nCell[StyleData[\"ButtonGray3Disabled\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->GrayLevel[1\/5, 0.5],\n Background->GrayLevel[229\/255, 0.5],\n FrameBoxOptions->{FrameStyle->{\n GrayLevel[\n 166\/255, 0.5]}},ExpressionUUID->\"7a44d754-a358-4083-8130-1b136829b7c6\"]\n}, Closed]],\n\nCell[CellGroupData[{\n\nCell[\"Orange1 (WANE)\", \"Subsection\",ExpressionUUID->\"ace97dbf-11a1-4778-8316-a2c7127db5d0\"],\n\nCell[StyleData[\"ButtonOrange1Normal\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->GrayLevel[1],\n Background->RGBColor[\n 0.9568627450980391, 0.36470588235294116`, \n 0.1568627450980392],ExpressionUUID->\"e67c8449-d0c2-4fce-bf5e-c66f50a1b8f9\"],\n\nCell[StyleData[\"ButtonOrange1Hover\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->GrayLevel[1],\n Background->RGBColor[\n 0.9450980392156862, 0.4784313725490196, \n 0.21568627450980393`],ExpressionUUID->\"f573e281-9367-47df-b46c-\\\ndcc0f763e54c\"],\n\nCell[StyleData[\"ButtonOrange1Pressed\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->GrayLevel[1],\n Background->RGBColor[\n 0.7725490196078432, 0.0392156862745098, \n 0.],ExpressionUUID->\"ac9997c6-9839-491c-83c6-1cb2db3a46ca\"],\n\nCell[StyleData[\"ButtonOrange1Disabled\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->GrayLevel[1, 0.5],\n Background->RGBColor[\n 0.9568627450980391, 0.36470588235294116`, 0.1568627450980392, \n 0.5],ExpressionUUID->\"3f08c1bb-5a9b-47f0-aa9f-53790879b9d0\"]\n}, Closed]],\n\nCell[CellGroupData[{\n\nCell[\"Orange2 (WANE)\", \"Subsection\",ExpressionUUID->\"7298227e-2e3a-4d4c-93c1-cb61604d4cb1\"],\n\nCell[StyleData[\"ButtonOrange2Normal\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->RGBColor[\n 0.9568627450980391, 0.36470588235294116`, 0.1568627450980392],\n Background->GrayLevel[1],\n FrameBoxOptions->{\n FrameStyle->RGBColor[\n 0.9568627450980391, 0.36470588235294116`, \n 0.1568627450980392]},ExpressionUUID->\"87a48f8c-e7f7-4ccd-a27d-\\\naf2248ca596e\"],\n\nCell[StyleData[\"ButtonOrange2Hover\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->GrayLevel[1],\n Background->RGBColor[\n 0.9450980392156862, 0.4784313725490196, \n 0.21568627450980393`],ExpressionUUID->\"b520fc9b-c89d-438a-ac41-\\\n4a00162c3a86\"],\n\nCell[StyleData[\"ButtonOrange2Pressed\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->GrayLevel[1],\n Background->RGBColor[\n 0.7725490196078432, 0.0392156862745098, \n 0.],ExpressionUUID->\"cba9d1a2-a85b-4150-9453-8c71b68b5dd4\"],\n\nCell[StyleData[\"ButtonOrange2Disabled\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->RGBColor[\n 0.9568627450980391, 0.36470588235294116`, 0.1568627450980392, 0.5],\n Background->GrayLevel[1, 0.5],\n FrameBoxOptions->{\n FrameStyle->RGBColor[\n 0.9568627450980391, 0.36470588235294116`, 0.1568627450980392, \n 0.5]},ExpressionUUID->\"0c50140d-20db-4926-9d52-6b8ce2011a81\"]\n}, Closed]],\n\nCell[CellGroupData[{\n\nCell[\"Orange3 (WPL)\", \"Subsection\",ExpressionUUID->\"463e8e41-fef6-4b1d-9c7b-4020d2f85d24\"],\n\nCell[StyleData[\"ButtonOrange3Normal\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->GrayLevel[1],\n Background->RGBColor[\n 0.9490196078431372, 0.39215686274509803`, \n 0.027450980392156862`],ExpressionUUID->\"c7adebf4-3691-447a-8767-\\\nc28336428e8f\"],\n\nCell[StyleData[\"ButtonOrange3Hover\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->GrayLevel[1],\n Background->RGBColor[\n 0.9568627450980391, 0.6588235294117647, \n 0.09803921568627451],ExpressionUUID->\"043e0ec0-9198-4ec3-8c89-\\\nab7d399212ac\"],\n\nCell[StyleData[\"ButtonOrange3Pressed\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->GrayLevel[1],\n Background->RGBColor[\n 0.9490196078431372, 0.5411764705882353, \n 0.06666666666666667],ExpressionUUID->\"a372525f-6ec8-4aeb-a9e7-\\\n8aa36b3e536c\"],\n\nCell[StyleData[\"ButtonOrange3Disabled\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->GrayLevel[1, 0.5],\n Background->RGBColor[\n 0.9490196078431372, 0.39215686274509803`, 0.027450980392156862`, \n 0.5],ExpressionUUID->\"9ba7d69d-1454-4237-8330-af4478dbc31c\"]\n}, Closed]],\n\nCell[CellGroupData[{\n\nCell[\"Orange4 (WPL)\", \"Subsection\",ExpressionUUID->\"ba557c0e-a816-4539-88a0-68d7198046e9\"],\n\nCell[StyleData[\"ButtonOrange4Normal\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->RGBColor[\n 0.9490196078431372, 0.39215686274509803`, 0.027450980392156862`],\n Background->GrayLevel[1],\n FrameBoxOptions->{\n FrameStyle->RGBColor[\n 0.9490196078431372, 0.39215686274509803`, \n 0.027450980392156862`]},ExpressionUUID->\"bd319ed4-2a30-4157-9421-\\\n90402ef9d6bd\"],\n\nCell[StyleData[\"ButtonOrange4Hover\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->GrayLevel[1],\n Background->RGBColor[\n 0.9568627450980391, 0.6588235294117647, \n 0.09803921568627451],ExpressionUUID->\"545719d9-e0e3-4b19-bc7d-\\\n73aab89222a1\"],\n\nCell[StyleData[\"ButtonOrange4Pressed\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->GrayLevel[1],\n Background->RGBColor[\n 0.9490196078431372, 0.5411764705882353, \n 0.06666666666666667],ExpressionUUID->\"19984a28-3b3c-4bf4-849c-\\\n6aab2bd8ed86\"],\n\nCell[StyleData[\"ButtonOrange4Disabled\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->RGBColor[\n 0.9490196078431372, 0.39215686274509803`, 0.027450980392156862`, 0.5],\n Background->GrayLevel[1, 0.5],\n FrameBoxOptions->{\n FrameStyle->RGBColor[\n 0.9490196078431372, 0.39215686274509803`, 0.027450980392156862`, \n 0.5]},ExpressionUUID->\"73159c18-e4b0-4bbc-83ac-5f676a4138bc\"]\n}, Closed]],\n\nCell[CellGroupData[{\n\nCell[\"Blue1 (WFP)\", \"Subsection\",ExpressionUUID->\"8296c02e-7954-4697-b4c7-a2703b41b29a\"],\n\nCell[StyleData[\"ButtonBlue1Normal\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->GrayLevel[1],\n Background->RGBColor[\n 0.1764705882352941, 0.4588235294117647, \n 0.7294117647058823],ExpressionUUID->\"6fb47a98-5fff-4f88-88e4-5d7dcdfc93a3\"],\n\nCell[StyleData[\"ButtonBlue1Hover\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->GrayLevel[1],\n Background->RGBColor[\n 0.24313725490196078`, 0.6, \n 0.9372549019607843],ExpressionUUID->\"acb0a1db-9c5b-4742-8afb-56b5c4a0962c\"],\n\nCell[StyleData[\"ButtonBlue1Pressed\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->GrayLevel[1],\n Background->RGBColor[\n 0.1411764705882353, 0.403921568627451, \n 0.6392156862745098],ExpressionUUID->\"7a83efb1-283f-4c9e-9a6c-5e9fe7c8c9c4\"],\n\nCell[StyleData[\"ButtonBlue1Disabled\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->GrayLevel[1, 0.5],\n Background->RGBColor[\n 0.1764705882352941, 0.4588235294117647, 0.7294117647058823, \n 0.5],ExpressionUUID->\"c851e27e-ed12-441f-9e09-f0d30c2a7358\"]\n}, Closed]],\n\nCell[CellGroupData[{\n\nCell[\"Blue2 (WFP)\", \"Subsection\",ExpressionUUID->\"5bdfbb8e-8d7e-4fe3-bb46-5b097e98389c\"],\n\nCell[StyleData[\"ButtonBlue2Normal\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->RGBColor[\n 0.1764705882352941, 0.4588235294117647, 0.7294117647058823],\n Background->GrayLevel[1],\n FrameBoxOptions->{\n FrameStyle->RGBColor[\n 0.1764705882352941, 0.4588235294117647, \n 0.7294117647058823]},ExpressionUUID->\"572ec6ff-fbeb-4f77-926a-\\\n4854120f08e0\"],\n\nCell[StyleData[\"ButtonBlue2Hover\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->GrayLevel[1],\n Background->RGBColor[\n 0.24313725490196078`, 0.6, \n 0.9372549019607843],ExpressionUUID->\"9d21b129-df60-488d-862b-9414cd07213c\"],\n\nCell[StyleData[\"ButtonBlue2Pressed\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->GrayLevel[1],\n Background->RGBColor[\n 0.1411764705882353, 0.403921568627451, \n 0.6392156862745098],ExpressionUUID->\"09360da9-7449-4bb6-86be-2634bba504b9\"],\n\nCell[StyleData[\"ButtonBlue2Disabled\", StyleDefinitions -> StyleData[\n \"ButtonCommonOptions\"]],\n FontColor->RGBColor[\n 0.1764705882352941, 0.4588235294117647, 0.7294117647058823, 0.5],\n Background->GrayLevel[1, 0.5],\n FrameBoxOptions->{\n FrameStyle->RGBColor[\n 0.1764705882352941, 0.4588235294117647, 0.7294117647058823, \n 0.5]},ExpressionUUID->\"c8648a90-1a8d-4c64-9183-f409872357f0\"]\n}, Closed]]\n}, Closed]]\n},\nAutoGeneratedPackage->None,\nWindowSize->{744, 606},\nWindowMargins->{{Automatic, 31.5}, {Automatic, 64.5}},\nTrackCellChangeTimes->False,\nMenuSortingValue->None,\nFrontEndVersion->\"13.0 for Microsoft Windows (64-bit) (October 6, 2021)\",\nStyleDefinitions->\"StylesheetFormatting.nb\",\nExpressionUUID->\"07804495-8e76-4625-b801-79b88f901116\"\n]\n(* End of Notebook Content *)\n\n(* Internal cache information *)\n(*CellTagsOutline\nCellTagsIndex->{}\n*)\n(*CellTagsIndex\nCellTagsIndex->{}\n*)\n(*NotebookFileOutline\nNotebook[{\nCell[574, 21, 104, 0, 30, 49, 0, \"StyleData\", \"StyleDefinitions\", \"\",ExpressionUUID->\"8dcf90df-6dd6-46d8-9698-98f27dd5e0b3\"],\nCell[CellGroupData[{\nCell[703, 25, 845, 28, 48, 27, 0, \"StyleData\", \"Notebook\", \"All\",ExpressionUUID->\"6b81a65b-4d44-4680-b1ef-3571a7d7c709\",\n Magnification->1],\nCell[1551, 55, 120, 2, 38, 31, 0, \"StyleData\", \"All\", \"Working\",ExpressionUUID->\"9717c4d9-b089-4abe-ad14-49bd001c6182\"]\n}, Closed]],\nCell[CellGroupData[{\nCell[1708, 62, 267, 4, 36, \"Section\",ExpressionUUID->\"cd4fec6c-0791-4ace-9979-bfcb0c8a18e2\"],\nCell[CellGroupData[{\nCell[2000, 70, 94, 0, 33, \"Subsection\",ExpressionUUID->\"2b771ef4-65b9-43c7-897a-e15718c2e9d0\"],\nCell[2097, 72, 297, 9, 43, 40, 0, \"StyleData\", \"CodeFormatterTextBase\", \"All\",ExpressionUUID->\"8700ceea-ef28-46eb-ac23-eb5c5a24efca\"],\nCell[2397, 83, 195, 5, 43, 34, 0, \"StyleData\", \"DialogTextBasic\", \"All\",ExpressionUUID->\"6a3b5061-da2f-45b5-9c9d-851c6636a051\"],\nCell[2595, 90, 450, 14, 43, 87, 1, \"StyleData\", \"DialogTextCommon\", \"All\",ExpressionUUID->\"994b15a8-948f-4c9a-ae1a-848a42b4bc81\"],\nCell[3048, 106, 155, 2, 39, 85, 1, \"StyleData\", \"DialogSubtext\", \"All\",ExpressionUUID->\"4fd96e8d-67e8-44d2-bcbf-82b7ca6cd786\"],\nCell[3206, 110, 177, 3, 39, 91, 1, \"StyleData\", \"DialogSubtextAlternate\", \"All\",ExpressionUUID->\"143fa03e-441f-44f2-8b3e-0469a6a08a60\"],\nCell[3386, 115, 178, 3, 39, 88, 1, \"StyleData\", \"DialogSubtextSubtle\", \"All\",ExpressionUUID->\"c6cd631e-3b26-434e-9dbc-81fb934f0160\"],\nCell[3567, 120, 211, 4, 43, 82, 1, \"StyleData\", \"DialogLink\", \"All\",ExpressionUUID->\"23f36ec8-5747-43ae-bb6b-bb40279b1864\"]\n}, Closed]],\nCell[CellGroupData[{\nCell[3815, 129, 96, 0, 33, \"Subsection\",ExpressionUUID->\"3a7e7fea-938d-4477-9c81-12f38855cad8\"],\nCell[3914, 131, 221, 5, 71, 84, 1, \"StyleData\", \"DialogHeader\", \"All\",ExpressionUUID->\"67e4366a-6b88-41dc-a95e-47713aa5ce0a\"],\nCell[4138, 138, 179, 3, 71, 89, 1, \"StyleData\", \"DialogHeaderAlternate\", \"All\",ExpressionUUID->\"b978187f-92ac-44c8-a54d-057b8039b6d5\"],\nCell[4320, 143, 176, 3, 71, 86, 1, \"StyleData\", \"DialogHeaderSubtle\", \"All\",ExpressionUUID->\"c69a446c-5ed9-415c-a38c-9ab41d8e7b71\"],\nCell[4499, 148, 277, 7, 75, 83, 1, \"StyleData\", \"DialogTitle\", \"All\",ExpressionUUID->\"8c3c787d-9845-4f22-9fba-7a52d4d02b60\"],\nCell[4779, 157, 179, 3, 67, 86, 1, \"StyleData\", \"DialogTitleSubtitle\", \"All\",ExpressionUUID->\"27a80a40-5103-4397-a038-2099f37a643b\"],\nCell[4961, 162, 226, 5, 41, 86, 1, \"StyleData\", \"DialogSubtitle\", \"All\",ExpressionUUID->\"f90c06f2-4ba3-47f9-b4a9-c055b4f1a6f8\"],\nCell[5190, 169, 351, 9, 2, 34, 0, \"StyleData\", \"DialogDelimiter\", \"All\",ExpressionUUID->\"71f9e3c2-aec1-49db-8555-4328cfbb289f\"],\nCell[5544, 180, 176, 3, 83, 82, 1, \"StyleData\", \"DialogBody\", \"All\",ExpressionUUID->\"3085a681-a9c4-4cc3-bb2f-074b92f11c07\"],\nCell[5723, 185, 171, 3, 81, 85, 1, \"StyleData\", \"DialogBodyAlternate\", \"All\",ExpressionUUID->\"b0d26588-8430-4075-85c0-983061f90c42\"],\nCell[5897, 190, 172, 3, 81, 82, 1, \"StyleData\", \"DialogBodySubtle\", \"All\",ExpressionUUID->\"bd2569ef-0dfc-4ad4-a164-64a55a49b88b\"],\nCell[6072, 195, 178, 3, 63, 84, 1, \"StyleData\", \"DialogFooter\", \"All\",ExpressionUUID->\"89c6daa5-c5d9-4c5c-a399-68912de67317\"]\n}, Closed]]\n}, Closed]],\nCell[CellGroupData[{\nCell[6299, 204, 87, 0, 36, \"Section\",ExpressionUUID->\"771ef523-fa0c-4ff0-bfda-4665382d0e44\"],\nCell[6389, 206, 216, 4, 43, 92, 1, \"StyleData\", \"InputTextPlaceholder\", \"All\",ExpressionUUID->\"fa66fb21-5923-4f0e-a351-049f86b3ec5b\"],\nCell[6608, 212, 188, 4, 44, 87, 1, \"StyleData\", \"InputTextActive\", \"All\",ExpressionUUID->\"7bccd9d9-2cbd-4299-8b7a-c1fff6e9f358\"],\nCell[6799, 218, 188, 4, 42, 83, 1, \"StyleData\", \"InputLabels\", \"All\",ExpressionUUID->\"0a9a1dd2-37e7-44ae-b195-289bc781df64\"],\nCell[6990, 224, 190, 4, 39, 85, 1, \"StyleData\", \"InputSubLabel\", \"All\",ExpressionUUID->\"02b67c7f-2eb4-4ec7-9d5f-cf49df9c382e\"],\nCell[7183, 230, 205, 5, 39, 82, 1, \"StyleData\", \"InputError\", \"All\",ExpressionUUID->\"bd2f5fec-815f-42e0-a4b3-3823078924e6\"]\n}, Closed]],\nCell[CellGroupData[{\nCell[7425, 240, 81, 0, 36, \"Section\",ExpressionUUID->\"021ca7b8-5627-4bbd-baa6-b65c5fed3d8e\"],\nCell[7509, 242, 229, 5, 40, 38, 0, \"StyleData\", \"ButtonCommonOptions\", \"All\",ExpressionUUID->\"5cd4919a-dc61-4a55-b218-3d6a9eeed628\"],\nCell[CellGroupData[{\nCell[7763, 251, 86, 0, 33, \"Subsection\",ExpressionUUID->\"ad10d9b3-726c-4e3e-ad0a-0479e17dfb9e\"],\nCell[7852, 253, 214, 4, 56, 91, 1, \"StyleData\", \"ButtonRed1Normal\", \"All\",ExpressionUUID->\"d7af7694-6e12-49b3-bcf3-257bf531de3d\"],\nCell[8069, 259, 212, 4, 56, 90, 1, \"StyleData\", \"ButtonRed1Hover\", \"All\",ExpressionUUID->\"429b2fd6-b93e-4f1b-a1c3-0acb3b279fb0\"],\nCell[8284, 265, 217, 4, 56, 92, 1, \"StyleData\", \"ButtonRed1Pressed\", \"All\",ExpressionUUID->\"3f7208e8-8fa9-4f17-a1b6-5a6bde53ded2\"],\nCell[8504, 271, 226, 4, 56, 93, 1, \"StyleData\", \"ButtonRed1Disabled\", \"All\",ExpressionUUID->\"6576727e-2b00-4ad8-a3f4-3441082ace7b\"]\n}, Closed]],\nCell[CellGroupData[{\nCell[8767, 280, 86, 0, 33, \"Subsection\",ExpressionUUID->\"ec2eaa00-134c-44aa-943b-69bbd1c7e979\"],\nCell[8856, 282, 274, 6, 38, 91, 1, \"StyleData\", \"ButtonRed2Normal\", \"All\",ExpressionUUID->\"6343b1da-efbb-4afe-8c88-33e2ddca5966\"],\nCell[9133, 290, 212, 4, 54, 90, 1, \"StyleData\", \"ButtonRed2Hover\", \"All\",ExpressionUUID->\"47bf1440-1225-4ff9-b25c-a0a680d6ca7b\"],\nCell[9348, 296, 217, 4, 54, 92, 1, \"StyleData\", \"ButtonRed2Pressed\", \"All\",ExpressionUUID->\"90e201ed-056e-4ad5-a797-5d00286566eb\"],\nCell[9568, 302, 295, 7, 38, 93, 1, \"StyleData\", \"ButtonRed2Disabled\", \"All\",ExpressionUUID->\"6c0b370d-084a-4821-93c0-3feda581a203\"]\n}, Closed]],\nCell[CellGroupData[{\nCell[9900, 314, 82, 0, 33, \"Subsection\",ExpressionUUID->\"d3ef4094-fb30-4755-82c1-036173ba3dfb\"],\nCell[9985, 316, 213, 4, 54, 92, 1, \"StyleData\", \"ButtonGray1Normal\", \"All\",ExpressionUUID->\"27f615f7-4ebb-4513-ab59-159457ab7d1f\"],\nCell[10201, 322, 269, 6, 54, 91, 1, \"StyleData\", \"ButtonGray1Hover\", \"All\",ExpressionUUID->\"89329681-8590-4d6c-8d4b-f090df795b8c\"],\nCell[10473, 330, 210, 4, 54, 93, 1, \"StyleData\", \"ButtonGray1Pressed\", \"All\",ExpressionUUID->\"8f475de5-caa9-488f-a6fd-6a51328ede3f\"],\nCell[10686, 336, 225, 4, 54, 94, 1, \"StyleData\", \"ButtonGray1Disabled\", \"All\",ExpressionUUID->\"b1c7ce4c-8320-4c9f-97da-4f84dc6be322\"]\n}, Closed]],\nCell[CellGroupData[{\nCell[10948, 345, 82, 0, 33, \"Subsection\",ExpressionUUID->\"4ae0f02f-3a2f-4e3f-9dde-5b2fe3756073\"],\nCell[11033, 347, 268, 6, 38, 92, 1, \"StyleData\", \"ButtonGray2Normal\", \"All\",ExpressionUUID->\"cfd15806-4098-4e08-bb0d-b1bde6ee89bd\"],\nCell[11304, 355, 269, 6, 54, 91, 1, \"StyleData\", \"ButtonGray2Hover\", \"All\",ExpressionUUID->\"e1b3a57e-80e4-4e2d-8019-b0f7b7419a07\"],\nCell[11576, 363, 210, 4, 54, 93, 1, \"StyleData\", \"ButtonGray2Pressed\", \"All\",ExpressionUUID->\"5ca0b38f-1ece-40af-90f8-0a666a0e543a\"],\nCell[11789, 369, 285, 6, 38, 94, 1, \"StyleData\", \"ButtonGray2Disabled\", \"All\",ExpressionUUID->\"ea7b983e-4506-441f-95f8-a862c0e5a470\"]\n}, Closed]],\nCell[CellGroupData[{\nCell[12111, 380, 82, 0, 33, \"Subsection\",ExpressionUUID->\"15b6a24b-4d6b-48bd-aeca-87d308eb4985\"],\nCell[12196, 382, 178, 3, 38, 92, 1, \"StyleData\", \"ButtonGray3Normal\", \"All\",ExpressionUUID->\"39c5e9da-3c70-4ae3-bb2b-3420361c879b\"],\nCell[12377, 387, 263, 6, 38, 91, 1, \"StyleData\", \"ButtonGray3Hover\", \"All\",ExpressionUUID->\"f193edae-9597-471a-b3af-fd7e39dc2784\"],\nCell[12643, 395, 271, 6, 54, 93, 1, \"StyleData\", \"ButtonGray3Pressed\", \"All\",ExpressionUUID->\"b796f87e-105d-4044-b257-077048090b23\"],\nCell[12917, 403, 287, 6, 54, 94, 1, \"StyleData\", \"ButtonGray3Disabled\", \"All\",ExpressionUUID->\"7a44d754-a358-4083-8130-1b136829b7c6\"]\n}, Closed]],\nCell[CellGroupData[{\nCell[13241, 414, 91, 0, 33, \"Subsection\",ExpressionUUID->\"ace97dbf-11a1-4778-8316-a2c7127db5d0\"],\nCell[13335, 416, 267, 5, 54, 94, 1, \"StyleData\", \"ButtonOrange1Normal\", \"All\",ExpressionUUID->\"e67c8449-d0c2-4fce-bf5e-c66f50a1b8f9\"],\nCell[13605, 423, 268, 6, 54, 93, 1, \"StyleData\", \"ButtonOrange1Hover\", \"All\",ExpressionUUID->\"f573e281-9367-47df-b46c-dcc0f763e54c\"],\nCell[13876, 431, 250, 5, 54, 95, 1, \"StyleData\", \"ButtonOrange1Pressed\", \"All\",ExpressionUUID->\"ac9997c6-9839-491c-83c6-1cb2db3a46ca\"],\nCell[14129, 438, 279, 5, 54, 96, 1, \"StyleData\", \"ButtonOrange1Disabled\", \"All\",ExpressionUUID->\"3f08c1bb-5a9b-47f0-aa9f-53790879b9d0\"]\n}, Closed]],\nCell[CellGroupData[{\nCell[14445, 448, 91, 0, 33, \"Subsection\",ExpressionUUID->\"7298227e-2e3a-4d4c-93c1-cb61604d4cb1\"],\nCell[14539, 450, 378, 9, 38, 94, 1, \"StyleData\", \"ButtonOrange2Normal\", \"All\",ExpressionUUID->\"87a48f8c-e7f7-4ccd-a27d-af2248ca596e\"],\nCell[14920, 461, 268, 6, 54, 93, 1, \"StyleData\", \"ButtonOrange2Hover\", \"All\",ExpressionUUID->\"b520fc9b-c89d-438a-ac41-4a00162c3a86\"],\nCell[15191, 469, 250, 5, 54, 95, 1, \"StyleData\", \"ButtonOrange2Pressed\", \"All\",ExpressionUUID->\"cba9d1a2-a85b-4150-9453-8c71b68b5dd4\"],\nCell[15444, 476, 393, 8, 38, 96, 1, \"StyleData\", \"ButtonOrange2Disabled\", \"All\",ExpressionUUID->\"0c50140d-20db-4926-9d52-6b8ce2011a81\"]\n}, Closed]],\nCell[CellGroupData[{\nCell[15874, 489, 90, 0, 33, \"Subsection\",ExpressionUUID->\"463e8e41-fef6-4b1d-9c7b-4020d2f85d24\"],\nCell[15967, 491, 272, 6, 54, 94, 1, \"StyleData\", \"ButtonOrange3Normal\", \"All\",ExpressionUUID->\"c7adebf4-3691-447a-8767-c28336428e8f\"],\nCell[16242, 499, 267, 6, 54, 93, 1, \"StyleData\", \"ButtonOrange3Hover\", \"All\",ExpressionUUID->\"043e0ec0-9198-4ec3-8c89-ab7d399212ac\"],\nCell[16512, 507, 269, 6, 54, 95, 1, \"StyleData\", \"ButtonOrange3Pressed\", \"All\",ExpressionUUID->\"a372525f-6ec8-4aeb-a9e7-8aa36b3e536c\"],\nCell[16784, 515, 282, 5, 54, 96, 1, \"StyleData\", \"ButtonOrange3Disabled\", \"All\",ExpressionUUID->\"9ba7d69d-1454-4237-8330-af4478dbc31c\"]\n}, Closed]],\nCell[CellGroupData[{\nCell[17103, 525, 90, 0, 33, \"Subsection\",ExpressionUUID->\"ba557c0e-a816-4539-88a0-68d7198046e9\"],\nCell[17196, 527, 384, 9, 38, 94, 1, \"StyleData\", \"ButtonOrange4Normal\", \"All\",ExpressionUUID->\"bd319ed4-2a30-4157-9421-90402ef9d6bd\"],\nCell[17583, 538, 267, 6, 54, 93, 1, \"StyleData\", \"ButtonOrange4Hover\", \"All\",ExpressionUUID->\"545719d9-e0e3-4b19-bc7d-73aab89222a1\"],\nCell[17853, 546, 269, 6, 54, 95, 1, \"StyleData\", \"ButtonOrange4Pressed\", \"All\",ExpressionUUID->\"19984a28-3b3c-4bf4-849c-6aab2bd8ed86\"],\nCell[18125, 554, 399, 8, 38, 96, 1, \"StyleData\", \"ButtonOrange4Disabled\", \"All\",ExpressionUUID->\"73159c18-e4b0-4bbc-83ac-5f676a4138bc\"]\n}, Closed]],\nCell[CellGroupData[{\nCell[18561, 567, 88, 0, 33, \"Subsection\",ExpressionUUID->\"8296c02e-7954-4697-b4c7-a2703b41b29a\"],\nCell[18652, 569, 263, 5, 54, 92, 1, \"StyleData\", \"ButtonBlue1Normal\", \"All\",ExpressionUUID->\"6fb47a98-5fff-4f88-88e4-5d7dcdfc93a3\"],\nCell[18918, 576, 249, 5, 54, 91, 1, \"StyleData\", \"ButtonBlue1Hover\", \"All\",ExpressionUUID->\"acb0a1db-9c5b-4742-8afb-56b5c4a0962c\"],\nCell[19170, 583, 263, 5, 54, 93, 1, \"StyleData\", \"ButtonBlue1Pressed\", \"All\",ExpressionUUID->\"7a83efb1-283f-4c9e-9a6c-5e9fe7c8c9c4\"],\nCell[19436, 590, 275, 5, 54, 94, 1, \"StyleData\", \"ButtonBlue1Disabled\", \"All\",ExpressionUUID->\"c851e27e-ed12-441f-9e09-f0d30c2a7358\"]\n}, Closed]],\nCell[CellGroupData[{\nCell[19748, 600, 88, 0, 33, \"Subsection\",ExpressionUUID->\"5bdfbb8e-8d7e-4fe3-bb46-5b097e98389c\"],\nCell[19839, 602, 372, 9, 38, 92, 1, \"StyleData\", \"ButtonBlue2Normal\", \"All\",ExpressionUUID->\"572ec6ff-fbeb-4f77-926a-4854120f08e0\"],\nCell[20214, 613, 249, 5, 54, 91, 1, \"StyleData\", \"ButtonBlue2Hover\", \"All\",ExpressionUUID->\"9d21b129-df60-488d-862b-9414cd07213c\"],\nCell[20466, 620, 263, 5, 54, 93, 1, \"StyleData\", \"ButtonBlue2Pressed\", \"All\",ExpressionUUID->\"09360da9-7449-4bb6-86be-2634bba504b9\"],\nCell[20732, 627, 387, 8, 38, 94, 1, \"StyleData\", \"ButtonBlue2Disabled\", \"All\",ExpressionUUID->\"c8648a90-1a8d-4c64-9183-f409872357f0\"]\n}, Closed]]\n}, Closed]]\n}\n]\n*)\n\n","avg_line_length":42.2124681934,"max_line_length":136,"alphanum_fraction":0.7438741373} {"size":3661,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 9;\nname = \"9v5 1 1 2\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-8 I y] (1 (I Sin[x])^3 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^3) + Exp[-7 I y] (3 (I Sin[x])^2 Cos[x]^7 + 3 (I Sin[x])^7 Cos[x]^2 + 2 (I Sin[x])^5 Cos[x]^4 + 2 (I Sin[x])^4 Cos[x]^5 + 2 (I Sin[x])^1 Cos[x]^8 + 2 (I Sin[x])^8 Cos[x]^1 + 1 (I Sin[x])^3 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^3) + Exp[-6 I y] (5 (I Sin[x])^2 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^2 + 14 (I Sin[x])^4 Cos[x]^5 + 14 (I Sin[x])^5 Cos[x]^4 + 9 (I Sin[x])^3 Cos[x]^6 + 9 (I Sin[x])^6 Cos[x]^3) + Exp[-5 I y] (22 (I Sin[x])^3 Cos[x]^6 + 22 (I Sin[x])^6 Cos[x]^3 + 21 (I Sin[x])^4 Cos[x]^5 + 21 (I Sin[x])^5 Cos[x]^4 + 2 (I Sin[x])^1 Cos[x]^8 + 2 (I Sin[x])^8 Cos[x]^1 + 1 Cos[x]^9 + 1 (I Sin[x])^9 + 10 (I Sin[x])^2 Cos[x]^7 + 10 (I Sin[x])^7 Cos[x]^2) + Exp[-4 I y] (2 (I Sin[x])^1 Cos[x]^8 + 2 (I Sin[x])^8 Cos[x]^1 + 42 (I Sin[x])^5 Cos[x]^4 + 42 (I Sin[x])^4 Cos[x]^5 + 22 (I Sin[x])^3 Cos[x]^6 + 22 (I Sin[x])^6 Cos[x]^3 + 4 (I Sin[x])^2 Cos[x]^7 + 4 (I Sin[x])^7 Cos[x]^2) + Exp[-3 I y] (29 (I Sin[x])^4 Cos[x]^5 + 29 (I Sin[x])^5 Cos[x]^4 + 16 (I Sin[x])^3 Cos[x]^6 + 16 (I Sin[x])^6 Cos[x]^3 + 8 (I Sin[x])^2 Cos[x]^7 + 8 (I Sin[x])^7 Cos[x]^2 + 3 (I Sin[x])^1 Cos[x]^8 + 3 (I Sin[x])^8 Cos[x]^1) + Exp[-2 I y] (5 (I Sin[x])^2 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^2 + 14 (I Sin[x])^4 Cos[x]^5 + 14 (I Sin[x])^5 Cos[x]^4 + 9 (I Sin[x])^6 Cos[x]^3 + 9 (I Sin[x])^3 Cos[x]^6) + Exp[-1 I y] (4 (I Sin[x])^5 Cos[x]^4 + 4 (I Sin[x])^4 Cos[x]^5 + 1 (I Sin[x])^2 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^2 + 3 (I Sin[x])^6 Cos[x]^3 + 3 (I Sin[x])^3 Cos[x]^6) + Exp[0 I y] (1 (I Sin[x])^3 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^3))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-8 I y] (1 (I Sin[x])^3 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^3) + Exp[-7 I y] (3 (I Sin[x])^2 Cos[x]^7 + 3 (I Sin[x])^7 Cos[x]^2 + 2 (I Sin[x])^5 Cos[x]^4 + 2 (I Sin[x])^4 Cos[x]^5 + 2 (I Sin[x])^1 Cos[x]^8 + 2 (I Sin[x])^8 Cos[x]^1 + 1 (I Sin[x])^3 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^3) + Exp[-6 I y] (5 (I Sin[x])^2 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^2 + 14 (I Sin[x])^4 Cos[x]^5 + 14 (I Sin[x])^5 Cos[x]^4 + 9 (I Sin[x])^3 Cos[x]^6 + 9 (I Sin[x])^6 Cos[x]^3) + Exp[-5 I y] (22 (I Sin[x])^3 Cos[x]^6 + 22 (I Sin[x])^6 Cos[x]^3 + 21 (I Sin[x])^4 Cos[x]^5 + 21 (I Sin[x])^5 Cos[x]^4 + 2 (I Sin[x])^1 Cos[x]^8 + 2 (I Sin[x])^8 Cos[x]^1 + 1 Cos[x]^9 + 1 (I Sin[x])^9 + 10 (I Sin[x])^2 Cos[x]^7 + 10 (I Sin[x])^7 Cos[x]^2) + Exp[-4 I y] (2 (I Sin[x])^1 Cos[x]^8 + 2 (I Sin[x])^8 Cos[x]^1 + 42 (I Sin[x])^5 Cos[x]^4 + 42 (I Sin[x])^4 Cos[x]^5 + 22 (I Sin[x])^3 Cos[x]^6 + 22 (I Sin[x])^6 Cos[x]^3 + 4 (I Sin[x])^2 Cos[x]^7 + 4 (I Sin[x])^7 Cos[x]^2) + Exp[-3 I y] (29 (I Sin[x])^4 Cos[x]^5 + 29 (I Sin[x])^5 Cos[x]^4 + 16 (I Sin[x])^3 Cos[x]^6 + 16 (I Sin[x])^6 Cos[x]^3 + 8 (I Sin[x])^2 Cos[x]^7 + 8 (I Sin[x])^7 Cos[x]^2 + 3 (I Sin[x])^1 Cos[x]^8 + 3 (I Sin[x])^8 Cos[x]^1) + Exp[-2 I y] (5 (I Sin[x])^2 Cos[x]^7 + 5 (I Sin[x])^7 Cos[x]^2 + 14 (I Sin[x])^4 Cos[x]^5 + 14 (I Sin[x])^5 Cos[x]^4 + 9 (I Sin[x])^6 Cos[x]^3 + 9 (I Sin[x])^3 Cos[x]^6) + Exp[-1 I y] (4 (I Sin[x])^5 Cos[x]^4 + 4 (I Sin[x])^4 Cos[x]^5 + 1 (I Sin[x])^2 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^2 + 3 (I Sin[x])^6 Cos[x]^3 + 3 (I Sin[x])^3 Cos[x]^6) + Exp[0 I y] (1 (I Sin[x])^3 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^3));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":244.0666666667,"max_line_length":1613,"alphanum_fraction":0.4832013111} {"size":9281,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"$Conjugate[x_] := x \/. Complex[a_, b_] :> a - I b;\nfunction[x_, y_] := $Conjugate[Exp[-16 I y] (1 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^7) + Exp[-12 I y] (30 (I Sin[x])^6 Cos[x]^10 + 30 (I Sin[x])^10 Cos[x]^6 + 48 (I Sin[x])^8 Cos[x]^8 + 33 (I Sin[x])^7 Cos[x]^9 + 33 (I Sin[x])^9 Cos[x]^7 + 21 (I Sin[x])^5 Cos[x]^11 + 21 (I Sin[x])^11 Cos[x]^5 + 10 (I Sin[x])^4 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3) + Exp[-8 I y] (636 (I Sin[x])^7 Cos[x]^9 + 636 (I Sin[x])^9 Cos[x]^7 + 257 (I Sin[x])^5 Cos[x]^11 + 257 (I Sin[x])^11 Cos[x]^5 + 463 (I Sin[x])^6 Cos[x]^10 + 463 (I Sin[x])^10 Cos[x]^6 + 648 (I Sin[x])^8 Cos[x]^8 + 104 (I Sin[x])^4 Cos[x]^12 + 104 (I Sin[x])^12 Cos[x]^4 + 31 (I Sin[x])^3 Cos[x]^13 + 31 (I Sin[x])^13 Cos[x]^3 + 5 (I Sin[x])^2 Cos[x]^14 + 5 (I Sin[x])^14 Cos[x]^2) + Exp[-4 I y] (1941 (I Sin[x])^6 Cos[x]^10 + 1941 (I Sin[x])^10 Cos[x]^6 + 440 (I Sin[x])^4 Cos[x]^12 + 440 (I Sin[x])^12 Cos[x]^4 + 3244 (I Sin[x])^8 Cos[x]^8 + 1057 (I Sin[x])^5 Cos[x]^11 + 1057 (I Sin[x])^11 Cos[x]^5 + 2783 (I Sin[x])^7 Cos[x]^9 + 2783 (I Sin[x])^9 Cos[x]^7 + 132 (I Sin[x])^3 Cos[x]^13 + 132 (I Sin[x])^13 Cos[x]^3 + 29 (I Sin[x])^2 Cos[x]^14 + 29 (I Sin[x])^14 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[0 I y] (1678 (I Sin[x])^5 Cos[x]^11 + 1678 (I Sin[x])^11 Cos[x]^5 + 4558 (I Sin[x])^7 Cos[x]^9 + 4558 (I Sin[x])^9 Cos[x]^7 + 226 (I Sin[x])^3 Cos[x]^13 + 226 (I Sin[x])^13 Cos[x]^3 + 3125 (I Sin[x])^6 Cos[x]^10 + 3125 (I Sin[x])^10 Cos[x]^6 + 5042 (I Sin[x])^8 Cos[x]^8 + 702 (I Sin[x])^4 Cos[x]^12 + 702 (I Sin[x])^12 Cos[x]^4 + 51 (I Sin[x])^2 Cos[x]^14 + 51 (I Sin[x])^14 Cos[x]^2 + 8 (I Sin[x])^1 Cos[x]^15 + 8 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[4 I y] (452 (I Sin[x])^4 Cos[x]^12 + 452 (I Sin[x])^12 Cos[x]^4 + 3156 (I Sin[x])^8 Cos[x]^8 + 1971 (I Sin[x])^6 Cos[x]^10 + 1971 (I Sin[x])^10 Cos[x]^6 + 2747 (I Sin[x])^7 Cos[x]^9 + 2747 (I Sin[x])^9 Cos[x]^7 + 1087 (I Sin[x])^5 Cos[x]^11 + 1087 (I Sin[x])^11 Cos[x]^5 + 138 (I Sin[x])^3 Cos[x]^13 + 138 (I Sin[x])^13 Cos[x]^3 + 31 (I Sin[x])^2 Cos[x]^14 + 31 (I Sin[x])^14 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[8 I y] (257 (I Sin[x])^5 Cos[x]^11 + 257 (I Sin[x])^11 Cos[x]^5 + 636 (I Sin[x])^7 Cos[x]^9 + 636 (I Sin[x])^9 Cos[x]^7 + 31 (I Sin[x])^3 Cos[x]^13 + 31 (I Sin[x])^13 Cos[x]^3 + 448 (I Sin[x])^6 Cos[x]^10 + 448 (I Sin[x])^10 Cos[x]^6 + 110 (I Sin[x])^4 Cos[x]^12 + 110 (I Sin[x])^12 Cos[x]^4 + 668 (I Sin[x])^8 Cos[x]^8 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2) + Exp[12 I y] (30 (I Sin[x])^6 Cos[x]^10 + 30 (I Sin[x])^10 Cos[x]^6 + 64 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^4 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^4 + 45 (I Sin[x])^7 Cos[x]^9 + 45 (I Sin[x])^9 Cos[x]^7 + 11 (I Sin[x])^5 Cos[x]^11 + 11 (I Sin[x])^11 Cos[x]^5) + Exp[16 I y] (1 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^7)]*\n(Exp[-16 I y] (1 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^7) + Exp[-12 I y] (30 (I Sin[x])^6 Cos[x]^10 + 30 (I Sin[x])^10 Cos[x]^6 + 48 (I Sin[x])^8 Cos[x]^8 + 33 (I Sin[x])^7 Cos[x]^9 + 33 (I Sin[x])^9 Cos[x]^7 + 21 (I Sin[x])^5 Cos[x]^11 + 21 (I Sin[x])^11 Cos[x]^5 + 10 (I Sin[x])^4 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3) + Exp[-8 I y] (636 (I Sin[x])^7 Cos[x]^9 + 636 (I Sin[x])^9 Cos[x]^7 + 257 (I Sin[x])^5 Cos[x]^11 + 257 (I Sin[x])^11 Cos[x]^5 + 463 (I Sin[x])^6 Cos[x]^10 + 463 (I Sin[x])^10 Cos[x]^6 + 648 (I Sin[x])^8 Cos[x]^8 + 104 (I Sin[x])^4 Cos[x]^12 + 104 (I Sin[x])^12 Cos[x]^4 + 31 (I Sin[x])^3 Cos[x]^13 + 31 (I Sin[x])^13 Cos[x]^3 + 5 (I Sin[x])^2 Cos[x]^14 + 5 (I Sin[x])^14 Cos[x]^2) + Exp[-4 I y] (1941 (I Sin[x])^6 Cos[x]^10 + 1941 (I Sin[x])^10 Cos[x]^6 + 440 (I Sin[x])^4 Cos[x]^12 + 440 (I Sin[x])^12 Cos[x]^4 + 3244 (I Sin[x])^8 Cos[x]^8 + 1057 (I Sin[x])^5 Cos[x]^11 + 1057 (I Sin[x])^11 Cos[x]^5 + 2783 (I Sin[x])^7 Cos[x]^9 + 2783 (I Sin[x])^9 Cos[x]^7 + 132 (I Sin[x])^3 Cos[x]^13 + 132 (I Sin[x])^13 Cos[x]^3 + 29 (I Sin[x])^2 Cos[x]^14 + 29 (I Sin[x])^14 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[0 I y] (1678 (I Sin[x])^5 Cos[x]^11 + 1678 (I Sin[x])^11 Cos[x]^5 + 4558 (I Sin[x])^7 Cos[x]^9 + 4558 (I Sin[x])^9 Cos[x]^7 + 226 (I Sin[x])^3 Cos[x]^13 + 226 (I Sin[x])^13 Cos[x]^3 + 3125 (I Sin[x])^6 Cos[x]^10 + 3125 (I Sin[x])^10 Cos[x]^6 + 5042 (I Sin[x])^8 Cos[x]^8 + 702 (I Sin[x])^4 Cos[x]^12 + 702 (I Sin[x])^12 Cos[x]^4 + 51 (I Sin[x])^2 Cos[x]^14 + 51 (I Sin[x])^14 Cos[x]^2 + 8 (I Sin[x])^1 Cos[x]^15 + 8 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[4 I y] (452 (I Sin[x])^4 Cos[x]^12 + 452 (I Sin[x])^12 Cos[x]^4 + 3156 (I Sin[x])^8 Cos[x]^8 + 1971 (I Sin[x])^6 Cos[x]^10 + 1971 (I Sin[x])^10 Cos[x]^6 + 2747 (I Sin[x])^7 Cos[x]^9 + 2747 (I Sin[x])^9 Cos[x]^7 + 1087 (I Sin[x])^5 Cos[x]^11 + 1087 (I Sin[x])^11 Cos[x]^5 + 138 (I Sin[x])^3 Cos[x]^13 + 138 (I Sin[x])^13 Cos[x]^3 + 31 (I Sin[x])^2 Cos[x]^14 + 31 (I Sin[x])^14 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[8 I y] (257 (I Sin[x])^5 Cos[x]^11 + 257 (I Sin[x])^11 Cos[x]^5 + 636 (I Sin[x])^7 Cos[x]^9 + 636 (I Sin[x])^9 Cos[x]^7 + 31 (I Sin[x])^3 Cos[x]^13 + 31 (I Sin[x])^13 Cos[x]^3 + 448 (I Sin[x])^6 Cos[x]^10 + 448 (I Sin[x])^10 Cos[x]^6 + 110 (I Sin[x])^4 Cos[x]^12 + 110 (I Sin[x])^12 Cos[x]^4 + 668 (I Sin[x])^8 Cos[x]^8 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2) + Exp[12 I y] (30 (I Sin[x])^6 Cos[x]^10 + 30 (I Sin[x])^10 Cos[x]^6 + 64 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^4 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^4 + 45 (I Sin[x])^7 Cos[x]^9 + 45 (I Sin[x])^9 Cos[x]^7 + 11 (I Sin[x])^5 Cos[x]^11 + 11 (I Sin[x])^11 Cos[x]^5) + Exp[16 I y] (1 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^7))\n\namplitude[x_,y_] := Exp[-16 I y] (1 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^7) + Exp[-12 I y] (30 (I Sin[x])^6 Cos[x]^10 + 30 (I Sin[x])^10 Cos[x]^6 + 48 (I Sin[x])^8 Cos[x]^8 + 33 (I Sin[x])^7 Cos[x]^9 + 33 (I Sin[x])^9 Cos[x]^7 + 21 (I Sin[x])^5 Cos[x]^11 + 21 (I Sin[x])^11 Cos[x]^5 + 10 (I Sin[x])^4 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3) + Exp[-8 I y] (636 (I Sin[x])^7 Cos[x]^9 + 636 (I Sin[x])^9 Cos[x]^7 + 257 (I Sin[x])^5 Cos[x]^11 + 257 (I Sin[x])^11 Cos[x]^5 + 463 (I Sin[x])^6 Cos[x]^10 + 463 (I Sin[x])^10 Cos[x]^6 + 648 (I Sin[x])^8 Cos[x]^8 + 104 (I Sin[x])^4 Cos[x]^12 + 104 (I Sin[x])^12 Cos[x]^4 + 31 (I Sin[x])^3 Cos[x]^13 + 31 (I Sin[x])^13 Cos[x]^3 + 5 (I Sin[x])^2 Cos[x]^14 + 5 (I Sin[x])^14 Cos[x]^2) + Exp[-4 I y] (1941 (I Sin[x])^6 Cos[x]^10 + 1941 (I Sin[x])^10 Cos[x]^6 + 440 (I Sin[x])^4 Cos[x]^12 + 440 (I Sin[x])^12 Cos[x]^4 + 3244 (I Sin[x])^8 Cos[x]^8 + 1057 (I Sin[x])^5 Cos[x]^11 + 1057 (I Sin[x])^11 Cos[x]^5 + 2783 (I Sin[x])^7 Cos[x]^9 + 2783 (I Sin[x])^9 Cos[x]^7 + 132 (I Sin[x])^3 Cos[x]^13 + 132 (I Sin[x])^13 Cos[x]^3 + 29 (I Sin[x])^2 Cos[x]^14 + 29 (I Sin[x])^14 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[0 I y] (1678 (I Sin[x])^5 Cos[x]^11 + 1678 (I Sin[x])^11 Cos[x]^5 + 4558 (I Sin[x])^7 Cos[x]^9 + 4558 (I Sin[x])^9 Cos[x]^7 + 226 (I Sin[x])^3 Cos[x]^13 + 226 (I Sin[x])^13 Cos[x]^3 + 3125 (I Sin[x])^6 Cos[x]^10 + 3125 (I Sin[x])^10 Cos[x]^6 + 5042 (I Sin[x])^8 Cos[x]^8 + 702 (I Sin[x])^4 Cos[x]^12 + 702 (I Sin[x])^12 Cos[x]^4 + 51 (I Sin[x])^2 Cos[x]^14 + 51 (I Sin[x])^14 Cos[x]^2 + 8 (I Sin[x])^1 Cos[x]^15 + 8 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[4 I y] (452 (I Sin[x])^4 Cos[x]^12 + 452 (I Sin[x])^12 Cos[x]^4 + 3156 (I Sin[x])^8 Cos[x]^8 + 1971 (I Sin[x])^6 Cos[x]^10 + 1971 (I Sin[x])^10 Cos[x]^6 + 2747 (I Sin[x])^7 Cos[x]^9 + 2747 (I Sin[x])^9 Cos[x]^7 + 1087 (I Sin[x])^5 Cos[x]^11 + 1087 (I Sin[x])^11 Cos[x]^5 + 138 (I Sin[x])^3 Cos[x]^13 + 138 (I Sin[x])^13 Cos[x]^3 + 31 (I Sin[x])^2 Cos[x]^14 + 31 (I Sin[x])^14 Cos[x]^2 + 4 (I Sin[x])^1 Cos[x]^15 + 4 (I Sin[x])^15 Cos[x]^1) + Exp[8 I y] (257 (I Sin[x])^5 Cos[x]^11 + 257 (I Sin[x])^11 Cos[x]^5 + 636 (I Sin[x])^7 Cos[x]^9 + 636 (I Sin[x])^9 Cos[x]^7 + 31 (I Sin[x])^3 Cos[x]^13 + 31 (I Sin[x])^13 Cos[x]^3 + 448 (I Sin[x])^6 Cos[x]^10 + 448 (I Sin[x])^10 Cos[x]^6 + 110 (I Sin[x])^4 Cos[x]^12 + 110 (I Sin[x])^12 Cos[x]^4 + 668 (I Sin[x])^8 Cos[x]^8 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2) + Exp[12 I y] (30 (I Sin[x])^6 Cos[x]^10 + 30 (I Sin[x])^10 Cos[x]^6 + 64 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^4 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^4 + 45 (I Sin[x])^7 Cos[x]^9 + 45 (I Sin[x])^9 Cos[x]^7 + 11 (I Sin[x])^5 Cos[x]^11 + 11 (I Sin[x])^11 Cos[x]^5) + Exp[16 I y] (1 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^7)\n\namount = 16;\nname = \"16v4 1 2 1 1 4 2 1\";\nstates = 64;\n\n\nk = 0.1;\n\n\nmax = function[0, 0];\nx = 0;\ny = 0;\n\n\nFor[\u03b2 = 0 , \u03b2 <= Pi\/2, \u03b2 = \u03b2 + k,\n \tFor[\u03b3 = 0 , \u03b3 <= Pi\/2 - \u03b2, \u03b3 = \u03b3 + k,\n \t\n \t\tmax2 = function[\u03b2, \u03b3];\n \t\tIf[max2 > max, {x = \u03b2, y = \u03b3}];\n \t\tmax = Max[max, max2];\n \t]\n ]\n\nresult = NMaximize[{Re[states*function[a, b]\/(2^amount)], x - k < a < x + k, y - k < b < y + k}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 3}];\n\nPrint[name, \": \", result]\n\nf = function[c, d]; n = Pi;\nPlot3D[f,{c,0,n},{d,0,n}, PlotRange -> All]\n\nContourPlot[function[x, y], {x, 0, n}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":250.8378378378,"max_line_length":2876,"alphanum_fraction":0.5039327659} {"size":8029,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 14;\nname = \"14v1 3 1 2 6 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-13 I y] (1 (I Sin[x])^6 Cos[x]^8 + 1 (I Sin[x])^8 Cos[x]^6) + Exp[-11 I y] (4 (I Sin[x])^5 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^5 + 4 (I Sin[x])^7 Cos[x]^7 + 3 (I Sin[x])^6 Cos[x]^8 + 3 (I Sin[x])^8 Cos[x]^6 + 3 (I Sin[x])^10 Cos[x]^4 + 3 (I Sin[x])^4 Cos[x]^10 + 1 (I Sin[x])^11 Cos[x]^3 + 1 (I Sin[x])^3 Cos[x]^11) + Exp[-9 I y] (26 (I Sin[x])^7 Cos[x]^7 + 21 (I Sin[x])^5 Cos[x]^9 + 21 (I Sin[x])^9 Cos[x]^5 + 19 (I Sin[x])^8 Cos[x]^6 + 19 (I Sin[x])^6 Cos[x]^8 + 15 (I Sin[x])^4 Cos[x]^10 + 15 (I Sin[x])^10 Cos[x]^4 + 8 (I Sin[x])^3 Cos[x]^11 + 8 (I Sin[x])^11 Cos[x]^3 + 2 (I Sin[x])^12 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^12) + Exp[-7 I y] (100 (I Sin[x])^6 Cos[x]^8 + 100 (I Sin[x])^8 Cos[x]^6 + 100 (I Sin[x])^7 Cos[x]^7 + 72 (I Sin[x])^9 Cos[x]^5 + 72 (I Sin[x])^5 Cos[x]^9 + 40 (I Sin[x])^10 Cos[x]^4 + 40 (I Sin[x])^4 Cos[x]^10 + 17 (I Sin[x])^11 Cos[x]^3 + 17 (I Sin[x])^3 Cos[x]^11 + 6 (I Sin[x])^12 Cos[x]^2 + 6 (I Sin[x])^2 Cos[x]^12 + 1 (I Sin[x])^1 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^1) + Exp[-5 I y] (253 (I Sin[x])^8 Cos[x]^6 + 253 (I Sin[x])^6 Cos[x]^8 + 102 (I Sin[x])^4 Cos[x]^10 + 102 (I Sin[x])^10 Cos[x]^4 + 179 (I Sin[x])^9 Cos[x]^5 + 179 (I Sin[x])^5 Cos[x]^9 + 38 (I Sin[x])^3 Cos[x]^11 + 38 (I Sin[x])^11 Cos[x]^3 + 10 (I Sin[x])^2 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^1 + 262 (I Sin[x])^7 Cos[x]^7) + Exp[-3 I y] (536 (I Sin[x])^7 Cos[x]^7 + 303 (I Sin[x])^9 Cos[x]^5 + 303 (I Sin[x])^5 Cos[x]^9 + 447 (I Sin[x])^8 Cos[x]^6 + 447 (I Sin[x])^6 Cos[x]^8 + 164 (I Sin[x])^10 Cos[x]^4 + 164 (I Sin[x])^4 Cos[x]^10 + 74 (I Sin[x])^11 Cos[x]^3 + 74 (I Sin[x])^3 Cos[x]^11 + 24 (I Sin[x])^2 Cos[x]^12 + 24 (I Sin[x])^12 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^13 + 6 (I Sin[x])^13 Cos[x]^1 + 1 Cos[x]^14 + 1 (I Sin[x])^14) + Exp[-1 I y] (426 (I Sin[x])^9 Cos[x]^5 + 426 (I Sin[x])^5 Cos[x]^9 + 64 (I Sin[x])^3 Cos[x]^11 + 64 (I Sin[x])^11 Cos[x]^3 + 194 (I Sin[x])^10 Cos[x]^4 + 194 (I Sin[x])^4 Cos[x]^10 + 12 (I Sin[x])^2 Cos[x]^12 + 12 (I Sin[x])^12 Cos[x]^2 + 756 (I Sin[x])^7 Cos[x]^7 + 642 (I Sin[x])^8 Cos[x]^6 + 642 (I Sin[x])^6 Cos[x]^8) + Exp[1 I y] (592 (I Sin[x])^8 Cos[x]^6 + 592 (I Sin[x])^6 Cos[x]^8 + 628 (I Sin[x])^7 Cos[x]^7 + 429 (I Sin[x])^9 Cos[x]^5 + 429 (I Sin[x])^5 Cos[x]^9 + 246 (I Sin[x])^10 Cos[x]^4 + 246 (I Sin[x])^4 Cos[x]^10 + 100 (I Sin[x])^3 Cos[x]^11 + 100 (I Sin[x])^11 Cos[x]^3 + 30 (I Sin[x])^2 Cos[x]^12 + 30 (I Sin[x])^12 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^13 + 5 (I Sin[x])^13 Cos[x]^1) + Exp[3 I y] (535 (I Sin[x])^8 Cos[x]^6 + 535 (I Sin[x])^6 Cos[x]^8 + 116 (I Sin[x])^4 Cos[x]^10 + 116 (I Sin[x])^10 Cos[x]^4 + 298 (I Sin[x])^9 Cos[x]^5 + 298 (I Sin[x])^5 Cos[x]^9 + 22 (I Sin[x])^3 Cos[x]^11 + 22 (I Sin[x])^11 Cos[x]^3 + 632 (I Sin[x])^7 Cos[x]^7) + Exp[5 I y] (292 (I Sin[x])^7 Cos[x]^7 + 182 (I Sin[x])^9 Cos[x]^5 + 182 (I Sin[x])^5 Cos[x]^9 + 249 (I Sin[x])^8 Cos[x]^6 + 249 (I Sin[x])^6 Cos[x]^8 + 94 (I Sin[x])^4 Cos[x]^10 + 94 (I Sin[x])^10 Cos[x]^4 + 37 (I Sin[x])^3 Cos[x]^11 + 37 (I Sin[x])^11 Cos[x]^3 + 7 (I Sin[x])^2 Cos[x]^12 + 7 (I Sin[x])^12 Cos[x]^2) + Exp[7 I y] (65 (I Sin[x])^9 Cos[x]^5 + 65 (I Sin[x])^5 Cos[x]^9 + 162 (I Sin[x])^7 Cos[x]^7 + 127 (I Sin[x])^8 Cos[x]^6 + 127 (I Sin[x])^6 Cos[x]^8 + 13 (I Sin[x])^4 Cos[x]^10 + 13 (I Sin[x])^10 Cos[x]^4) + Exp[9 I y] (28 (I Sin[x])^6 Cos[x]^8 + 28 (I Sin[x])^8 Cos[x]^6 + 14 (I Sin[x])^4 Cos[x]^10 + 14 (I Sin[x])^10 Cos[x]^4 + 24 (I Sin[x])^7 Cos[x]^7 + 21 (I Sin[x])^5 Cos[x]^9 + 21 (I Sin[x])^9 Cos[x]^5 + 3 (I Sin[x])^3 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^3) + Exp[11 I y] (7 (I Sin[x])^8 Cos[x]^6 + 7 (I Sin[x])^6 Cos[x]^8 + 10 (I Sin[x])^7 Cos[x]^7 + 1 (I Sin[x])^5 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^5) + Exp[13 I y] (1 (I Sin[x])^5 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^5))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-13 I y] (1 (I Sin[x])^6 Cos[x]^8 + 1 (I Sin[x])^8 Cos[x]^6) + Exp[-11 I y] (4 (I Sin[x])^5 Cos[x]^9 + 4 (I Sin[x])^9 Cos[x]^5 + 4 (I Sin[x])^7 Cos[x]^7 + 3 (I Sin[x])^6 Cos[x]^8 + 3 (I Sin[x])^8 Cos[x]^6 + 3 (I Sin[x])^10 Cos[x]^4 + 3 (I Sin[x])^4 Cos[x]^10 + 1 (I Sin[x])^11 Cos[x]^3 + 1 (I Sin[x])^3 Cos[x]^11) + Exp[-9 I y] (26 (I Sin[x])^7 Cos[x]^7 + 21 (I Sin[x])^5 Cos[x]^9 + 21 (I Sin[x])^9 Cos[x]^5 + 19 (I Sin[x])^8 Cos[x]^6 + 19 (I Sin[x])^6 Cos[x]^8 + 15 (I Sin[x])^4 Cos[x]^10 + 15 (I Sin[x])^10 Cos[x]^4 + 8 (I Sin[x])^3 Cos[x]^11 + 8 (I Sin[x])^11 Cos[x]^3 + 2 (I Sin[x])^12 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^12) + Exp[-7 I y] (100 (I Sin[x])^6 Cos[x]^8 + 100 (I Sin[x])^8 Cos[x]^6 + 100 (I Sin[x])^7 Cos[x]^7 + 72 (I Sin[x])^9 Cos[x]^5 + 72 (I Sin[x])^5 Cos[x]^9 + 40 (I Sin[x])^10 Cos[x]^4 + 40 (I Sin[x])^4 Cos[x]^10 + 17 (I Sin[x])^11 Cos[x]^3 + 17 (I Sin[x])^3 Cos[x]^11 + 6 (I Sin[x])^12 Cos[x]^2 + 6 (I Sin[x])^2 Cos[x]^12 + 1 (I Sin[x])^1 Cos[x]^13 + 1 (I Sin[x])^13 Cos[x]^1) + Exp[-5 I y] (253 (I Sin[x])^8 Cos[x]^6 + 253 (I Sin[x])^6 Cos[x]^8 + 102 (I Sin[x])^4 Cos[x]^10 + 102 (I Sin[x])^10 Cos[x]^4 + 179 (I Sin[x])^9 Cos[x]^5 + 179 (I Sin[x])^5 Cos[x]^9 + 38 (I Sin[x])^3 Cos[x]^11 + 38 (I Sin[x])^11 Cos[x]^3 + 10 (I Sin[x])^2 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^1 + 262 (I Sin[x])^7 Cos[x]^7) + Exp[-3 I y] (536 (I Sin[x])^7 Cos[x]^7 + 303 (I Sin[x])^9 Cos[x]^5 + 303 (I Sin[x])^5 Cos[x]^9 + 447 (I Sin[x])^8 Cos[x]^6 + 447 (I Sin[x])^6 Cos[x]^8 + 164 (I Sin[x])^10 Cos[x]^4 + 164 (I Sin[x])^4 Cos[x]^10 + 74 (I Sin[x])^11 Cos[x]^3 + 74 (I Sin[x])^3 Cos[x]^11 + 24 (I Sin[x])^2 Cos[x]^12 + 24 (I Sin[x])^12 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^13 + 6 (I Sin[x])^13 Cos[x]^1 + 1 Cos[x]^14 + 1 (I Sin[x])^14) + Exp[-1 I y] (426 (I Sin[x])^9 Cos[x]^5 + 426 (I Sin[x])^5 Cos[x]^9 + 64 (I Sin[x])^3 Cos[x]^11 + 64 (I Sin[x])^11 Cos[x]^3 + 194 (I Sin[x])^10 Cos[x]^4 + 194 (I Sin[x])^4 Cos[x]^10 + 12 (I Sin[x])^2 Cos[x]^12 + 12 (I Sin[x])^12 Cos[x]^2 + 756 (I Sin[x])^7 Cos[x]^7 + 642 (I Sin[x])^8 Cos[x]^6 + 642 (I Sin[x])^6 Cos[x]^8) + Exp[1 I y] (592 (I Sin[x])^8 Cos[x]^6 + 592 (I Sin[x])^6 Cos[x]^8 + 628 (I Sin[x])^7 Cos[x]^7 + 429 (I Sin[x])^9 Cos[x]^5 + 429 (I Sin[x])^5 Cos[x]^9 + 246 (I Sin[x])^10 Cos[x]^4 + 246 (I Sin[x])^4 Cos[x]^10 + 100 (I Sin[x])^3 Cos[x]^11 + 100 (I Sin[x])^11 Cos[x]^3 + 30 (I Sin[x])^2 Cos[x]^12 + 30 (I Sin[x])^12 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^13 + 5 (I Sin[x])^13 Cos[x]^1) + Exp[3 I y] (535 (I Sin[x])^8 Cos[x]^6 + 535 (I Sin[x])^6 Cos[x]^8 + 116 (I Sin[x])^4 Cos[x]^10 + 116 (I Sin[x])^10 Cos[x]^4 + 298 (I Sin[x])^9 Cos[x]^5 + 298 (I Sin[x])^5 Cos[x]^9 + 22 (I Sin[x])^3 Cos[x]^11 + 22 (I Sin[x])^11 Cos[x]^3 + 632 (I Sin[x])^7 Cos[x]^7) + Exp[5 I y] (292 (I Sin[x])^7 Cos[x]^7 + 182 (I Sin[x])^9 Cos[x]^5 + 182 (I Sin[x])^5 Cos[x]^9 + 249 (I Sin[x])^8 Cos[x]^6 + 249 (I Sin[x])^6 Cos[x]^8 + 94 (I Sin[x])^4 Cos[x]^10 + 94 (I Sin[x])^10 Cos[x]^4 + 37 (I Sin[x])^3 Cos[x]^11 + 37 (I Sin[x])^11 Cos[x]^3 + 7 (I Sin[x])^2 Cos[x]^12 + 7 (I Sin[x])^12 Cos[x]^2) + Exp[7 I y] (65 (I Sin[x])^9 Cos[x]^5 + 65 (I Sin[x])^5 Cos[x]^9 + 162 (I Sin[x])^7 Cos[x]^7 + 127 (I Sin[x])^8 Cos[x]^6 + 127 (I Sin[x])^6 Cos[x]^8 + 13 (I Sin[x])^4 Cos[x]^10 + 13 (I Sin[x])^10 Cos[x]^4) + Exp[9 I y] (28 (I Sin[x])^6 Cos[x]^8 + 28 (I Sin[x])^8 Cos[x]^6 + 14 (I Sin[x])^4 Cos[x]^10 + 14 (I Sin[x])^10 Cos[x]^4 + 24 (I Sin[x])^7 Cos[x]^7 + 21 (I Sin[x])^5 Cos[x]^9 + 21 (I Sin[x])^9 Cos[x]^5 + 3 (I Sin[x])^3 Cos[x]^11 + 3 (I Sin[x])^11 Cos[x]^3) + Exp[11 I y] (7 (I Sin[x])^8 Cos[x]^6 + 7 (I Sin[x])^6 Cos[x]^8 + 10 (I Sin[x])^7 Cos[x]^7 + 1 (I Sin[x])^5 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^5) + Exp[13 I y] (1 (I Sin[x])^5 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^5));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":535.2666666667,"max_line_length":3794,"alphanum_fraction":0.497571304} {"size":5369,"ext":"nb","lang":"Mathematica","max_stars_count":4.0,"content":"Notebook[{\nCell[\" \", \"SymbolColorBar\",\n CellMargins->{{Inherited, Inherited}, {-5, \n 0}},ExpressionUUID->\"06c65bbe-ffa5-4651-bfe1-997cca9307d5\"],\n\nCell[TextData[{\n ButtonBox[\"BlackHoleAnalysis\",\n BaseStyle->{\"Link\", \"LinkTrail\"},\n ButtonData->\"paclet:BlackHoleAnalysis\/guide\/BlackHoleAnalysis\"],\n StyleBox[\" > \", \"LinkTrailSeparator\"],\n ButtonBox[\"BlackHoleAnalysis`Symbols\",\n BaseStyle->{\"Link\", \"LinkTrail\"},\n ButtonData->\"paclet:BlackHoleAnalysis\/guide\/BlackHoleAnalysis`Symbols\"],\n StyleBox[\" > \", \"LinkTrailSeparator\"],\n ButtonBox[\"YPhiPhiSymbol\",\n BaseStyle->{\"Link\", \"LinkTrail\"},\n ButtonData->\"paclet:BlackHoleAnalysis\/ref\/YPhiPhiSymbol\"]\n}], \"LinkTrail\",ExpressionUUID->\"37b86cff-412c-4b97-a85a-235d610660de\"],\n\nCell[CellGroupData[{\n\nCell[\"YPhiPhiSymbol\", \\\n\"ObjectName\",ExpressionUUID->\"ec2bcf98-3a12-4567-af97-e96ee1d3b6d2\"],\n\nCell[BoxData[GridBox[{\n {\"\", Cell[TextData[{\n Cell[BoxData[\n RowBox[{\n ButtonBox[\"YPhiPhiSymbol\",\n BaseStyle->\"Link\",\n ButtonData->\"paclet:BlackHoleAnalysis\/ref\/YPhiPhiSymbol\"], \"[\", \n \"]\"}]], \"InlineFormula\",ExpressionUUID->\n \"75d9f7ce-2872-42bc-9a3f-a566bec03151\"],\n \"\\[LineSeparator]returns the (formatted) symbol for vector spherical \\\nharmonic Y_lm_PhiPhi.\"\n }],ExpressionUUID->\"ea17d975-d2b9-43af-bb86-c1d677131d3d\"]}\n }]], \"Usage\",ExpressionUUID->\"09d95534-722d-48c9-a9fa-2cc56b7d7b32\"]\n}, Open ]],\n\nCell[CellGroupData[{\n\nCell[\"\", \"NotesSection\",\n WholeCellGroupOpener->True,\n CellGroupingRules->{\"SectionGrouping\", 50},\n CellFrameLabels->{{\n FEPrivate`If[\n FEPrivate`Or[\n FEPrivate`SameQ[FEPrivate`$ProductVersion, \"6.0\"], \n FEPrivate`SameQ[FEPrivate`$ProductVersion, \"7.0\"], \n FEPrivate`SameQ[FEPrivate`$ProductVersion, \"8.0\"]], \n Cell[\n TextData[\n Cell[\n BoxData[\n ButtonBox[\n FrameBox[\n StyleBox[\n RowBox[{\"MORE\", \" \", \"INFORMATION\"}], \"NotesFrameText\"], \n StripOnInput -> False], Appearance -> {Automatic, None}, BaseStyle -> \n None, ButtonFunction :> (FrontEndExecute[{\n FrontEnd`SelectionMove[\n FrontEnd`SelectedNotebook[], All, ButtonCell], \n FrontEndToken[\"OpenCloseGroup\"], \n FrontEnd`SelectionMove[\n FrontEnd`SelectedNotebook[], After, CellContents]}]& ), \n Evaluator -> None, Method -> \"Preemptive\"]]]], \"NotesSection\"], \n TextData[\n ButtonBox[\n Cell[\n TextData[{\n Cell[\n BoxData[\n TemplateBox[{24}, \"Spacer1\"]]], \"Details and Options\"}], \n \"NotesSection\"], Appearance -> {Automatic, None}, BaseStyle -> None, \n ButtonFunction :> (FrontEndExecute[{\n FrontEnd`SelectionMove[\n FrontEnd`SelectedNotebook[], All, ButtonCell], \n FrontEndToken[\"OpenCloseGroup\"], \n FrontEnd`SelectionMove[\n FrontEnd`SelectedNotebook[], After, CellContents]}]& ), Evaluator -> \n None, Method -> \"Preemptive\"]]], None}, {None, None}},\n CellFrameLabelMargins->\n 0,ExpressionUUID->\"95441585-69be-4015-813f-266d1cadcb63\"],\n\nCell[\"The following options can be given: \", \\\n\"Notes\",ExpressionUUID->\"8e90f5b4-e880-43c7-91b9-9b92b899885b\"],\n\nCell[BoxData[GridBox[{\n {Cell[\" \", \"TableRowIcon\",ExpressionUUID->\n \"ca0cc0e6-d25c-4a5f-acee-bcf070e59663\"], \"Conjugate\", \"False\", Cell[\"\\<\\\nSepcifies whether to return the symbol for the complex conjugate of the \\\nharmonic\\\n\\>\", \"TableText\",ExpressionUUID->\"e2492c5e-eeba-426c-afc4-a73088c4b055\"]}\n },\n GridBoxAlignment->{\n \"Columns\" -> {Left, Left, {Left}}, \"ColumnsIndexed\" -> {}, \n \"Rows\" -> {{Baseline}}, \"RowsIndexed\" -> {}}]], \"3ColumnTableMod\",\n GridBoxOptions->{\n GridBoxBackground->{\n \"Columns\" -> {{None}}, \"ColumnsIndexed\" -> {}, \"Rows\" -> {{None}}, \n \"RowsIndexed\" -> {}},\n GridBoxDividers->{\n \"Rows\" -> {{\n True, True}}}},ExpressionUUID->\"ef61612c-e0fd-4fac-a9c2-bf08d375631d\"]\n}, Open ]],\n\nCell[CellGroupData[{\n\nCell[\" \", \"FooterCell\",ExpressionUUID->\"8bbbc2b2-e72e-420c-9baa-ed101170559b\"],\n\nCell[BoxData[\"\"],ExpressionUUID->\"ec8fec32-ab78-4d17-88d4-170d3d37be69\"]\n}, Open ]]\n},\nSaveable->False,\nScreenStyleEnvironment->\"Working\",\nWindowSize->{725, 750},\nWindowMargins->{{0, Automatic}, {Automatic, 0}},\nWindowTitle->\"YPhiPhiSymbol\",\nVisible->True,\nPrivateNotebookOptions->{\"FileOutlineCache\"->False},\nTaggingRules->{\n \"ModificationHighlight\" -> False, \n \"Metadata\" -> {\n \"context\" -> \"BlackHoleAnalysis`\", \n \"keywords\" -> {\"YPhiPhiSymbol\", \"YPHIPHISYMBOL\", \"yphiphisymbol\"}, \n \"index\" -> True, \"label\" -> \n \"BlackHoleAnalysis\/BlackHoleAnalysis`Symbols Symbol\", \"language\" -> \"en\", \n \"paclet\" -> \"BlackHoleAnalysis`Symbols\", \"status\" -> \"None\", \"summary\" -> \n \"YPhiPhiSymbol[] returns the (formatted) symbol for vector spherical \\\nharmonic Y_lm_PhiPhi.\", \n \"synonyms\" -> {\"YPhiPhiSymbol\", \"YPHIPHISYMBOL\", \"yphiphisymbol\"}, \n \"title\" -> \"YPhiPhiSymbol\", \"windowTitle\" -> \"YPhiPhiSymbol\", \"type\" -> \n \"Symbol\", \"uri\" -> \"BlackHoleAnalysis\/ref\/YPhiPhiSymbol\", \n \"WorkflowDockedCell\" -> \"\"}, \"SearchTextTranslated\" -> \"\", \"LinkTrails\" -> \n \"\", \"NewStyles\" -> False},\nTrackCellChangeTimes->False,\nFrontEndVersion->\"11.3 for Mac OS X x86 (32-bit, 64-bit Kernel) (March 5, \\\n2018)\",\nStyleDefinitions->FrontEnd`FileName[{\"Wolfram\"}, \"Reference.nb\", \n CharacterEncoding -> \"UTF-8\"]\n]\n\n","avg_line_length":37.5454545455,"max_line_length":81,"alphanum_fraction":0.6535667722} {"size":10483,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 16;\nname = \"16v1 4 3 1 1 5 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^10 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^10) + Exp[-13 I y] (2 (I Sin[x])^11 Cos[x]^5 + 2 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^10 Cos[x]^6 + 4 (I Sin[x])^6 Cos[x]^10 + 6 (I Sin[x])^9 Cos[x]^7 + 6 (I Sin[x])^7 Cos[x]^9 + 6 (I Sin[x])^8 Cos[x]^8) + Exp[-11 I y] (37 (I Sin[x])^9 Cos[x]^7 + 37 (I Sin[x])^7 Cos[x]^9 + 38 (I Sin[x])^8 Cos[x]^8 + 22 (I Sin[x])^6 Cos[x]^10 + 22 (I Sin[x])^10 Cos[x]^6 + 17 (I Sin[x])^11 Cos[x]^5 + 17 (I Sin[x])^5 Cos[x]^11 + 8 (I Sin[x])^12 Cos[x]^4 + 8 (I Sin[x])^4 Cos[x]^12 + 2 (I Sin[x])^13 Cos[x]^3 + 2 (I Sin[x])^3 Cos[x]^13) + Exp[-9 I y] (107 (I Sin[x])^10 Cos[x]^6 + 107 (I Sin[x])^6 Cos[x]^10 + 135 (I Sin[x])^9 Cos[x]^7 + 135 (I Sin[x])^7 Cos[x]^9 + 152 (I Sin[x])^8 Cos[x]^8 + 44 (I Sin[x])^4 Cos[x]^12 + 44 (I Sin[x])^12 Cos[x]^4 + 71 (I Sin[x])^5 Cos[x]^11 + 71 (I Sin[x])^11 Cos[x]^5 + 18 (I Sin[x])^3 Cos[x]^13 + 18 (I Sin[x])^13 Cos[x]^3 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2) + Exp[-7 I y] (488 (I Sin[x])^8 Cos[x]^8 + 431 (I Sin[x])^7 Cos[x]^9 + 431 (I Sin[x])^9 Cos[x]^7 + 341 (I Sin[x])^10 Cos[x]^6 + 341 (I Sin[x])^6 Cos[x]^10 + 202 (I Sin[x])^11 Cos[x]^5 + 202 (I Sin[x])^5 Cos[x]^11 + 96 (I Sin[x])^12 Cos[x]^4 + 96 (I Sin[x])^4 Cos[x]^12 + 37 (I Sin[x])^13 Cos[x]^3 + 37 (I Sin[x])^3 Cos[x]^13 + 12 (I Sin[x])^14 Cos[x]^2 + 12 (I Sin[x])^2 Cos[x]^14 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[-5 I y] (981 (I Sin[x])^9 Cos[x]^7 + 981 (I Sin[x])^7 Cos[x]^9 + 469 (I Sin[x])^5 Cos[x]^11 + 469 (I Sin[x])^11 Cos[x]^5 + 1050 (I Sin[x])^8 Cos[x]^8 + 750 (I Sin[x])^6 Cos[x]^10 + 750 (I Sin[x])^10 Cos[x]^6 + 206 (I Sin[x])^4 Cos[x]^12 + 206 (I Sin[x])^12 Cos[x]^4 + 60 (I Sin[x])^3 Cos[x]^13 + 60 (I Sin[x])^13 Cos[x]^3 + 10 (I Sin[x])^2 Cos[x]^14 + 10 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[-3 I y] (1668 (I Sin[x])^7 Cos[x]^9 + 1668 (I Sin[x])^9 Cos[x]^7 + 1804 (I Sin[x])^8 Cos[x]^8 + 1204 (I Sin[x])^10 Cos[x]^6 + 1204 (I Sin[x])^6 Cos[x]^10 + 714 (I Sin[x])^11 Cos[x]^5 + 714 (I Sin[x])^5 Cos[x]^11 + 344 (I Sin[x])^12 Cos[x]^4 + 344 (I Sin[x])^4 Cos[x]^12 + 132 (I Sin[x])^13 Cos[x]^3 + 132 (I Sin[x])^3 Cos[x]^13 + 34 (I Sin[x])^2 Cos[x]^14 + 34 (I Sin[x])^14 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^15 + 6 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[-1 I y] (1605 (I Sin[x])^10 Cos[x]^6 + 1605 (I Sin[x])^6 Cos[x]^10 + 2660 (I Sin[x])^8 Cos[x]^8 + 286 (I Sin[x])^4 Cos[x]^12 + 286 (I Sin[x])^12 Cos[x]^4 + 2330 (I Sin[x])^7 Cos[x]^9 + 2330 (I Sin[x])^9 Cos[x]^7 + 800 (I Sin[x])^5 Cos[x]^11 + 800 (I Sin[x])^11 Cos[x]^5 + 70 (I Sin[x])^3 Cos[x]^13 + 70 (I Sin[x])^13 Cos[x]^3 + 14 (I Sin[x])^2 Cos[x]^14 + 14 (I Sin[x])^14 Cos[x]^2) + Exp[1 I y] (1545 (I Sin[x])^6 Cos[x]^10 + 1545 (I Sin[x])^10 Cos[x]^6 + 2476 (I Sin[x])^8 Cos[x]^8 + 2152 (I Sin[x])^9 Cos[x]^7 + 2152 (I Sin[x])^7 Cos[x]^9 + 904 (I Sin[x])^11 Cos[x]^5 + 904 (I Sin[x])^5 Cos[x]^11 + 418 (I Sin[x])^12 Cos[x]^4 + 418 (I Sin[x])^4 Cos[x]^12 + 138 (I Sin[x])^3 Cos[x]^13 + 138 (I Sin[x])^13 Cos[x]^3 + 34 (I Sin[x])^2 Cos[x]^14 + 34 (I Sin[x])^14 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^15 + 6 (I Sin[x])^15 Cos[x]^1) + Exp[3 I y] (518 (I Sin[x])^11 Cos[x]^5 + 518 (I Sin[x])^5 Cos[x]^11 + 1968 (I Sin[x])^7 Cos[x]^9 + 1968 (I Sin[x])^9 Cos[x]^7 + 34 (I Sin[x])^3 Cos[x]^13 + 34 (I Sin[x])^13 Cos[x]^3 + 2278 (I Sin[x])^8 Cos[x]^8 + 158 (I Sin[x])^4 Cos[x]^12 + 158 (I Sin[x])^12 Cos[x]^4 + 1188 (I Sin[x])^10 Cos[x]^6 + 1188 (I Sin[x])^6 Cos[x]^10) + Exp[5 I y] (997 (I Sin[x])^7 Cos[x]^9 + 997 (I Sin[x])^9 Cos[x]^7 + 455 (I Sin[x])^11 Cos[x]^5 + 455 (I Sin[x])^5 Cos[x]^11 + 774 (I Sin[x])^10 Cos[x]^6 + 774 (I Sin[x])^6 Cos[x]^10 + 1030 (I Sin[x])^8 Cos[x]^8 + 190 (I Sin[x])^4 Cos[x]^12 + 190 (I Sin[x])^12 Cos[x]^4 + 60 (I Sin[x])^3 Cos[x]^13 + 60 (I Sin[x])^13 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2) + Exp[7 I y] (34 (I Sin[x])^12 Cos[x]^4 + 34 (I Sin[x])^4 Cos[x]^12 + 684 (I Sin[x])^8 Cos[x]^8 + 317 (I Sin[x])^10 Cos[x]^6 + 317 (I Sin[x])^6 Cos[x]^10 + 543 (I Sin[x])^7 Cos[x]^9 + 543 (I Sin[x])^9 Cos[x]^7 + 129 (I Sin[x])^5 Cos[x]^11 + 129 (I Sin[x])^11 Cos[x]^5) + Exp[9 I y] (115 (I Sin[x])^6 Cos[x]^10 + 115 (I Sin[x])^10 Cos[x]^6 + 164 (I Sin[x])^8 Cos[x]^8 + 145 (I Sin[x])^9 Cos[x]^7 + 145 (I Sin[x])^7 Cos[x]^9 + 70 (I Sin[x])^5 Cos[x]^11 + 70 (I Sin[x])^11 Cos[x]^5 + 34 (I Sin[x])^4 Cos[x]^12 + 34 (I Sin[x])^12 Cos[x]^4 + 9 (I Sin[x])^3 Cos[x]^13 + 9 (I Sin[x])^13 Cos[x]^3) + Exp[11 I y] (13 (I Sin[x])^11 Cos[x]^5 + 13 (I Sin[x])^5 Cos[x]^11 + 43 (I Sin[x])^9 Cos[x]^7 + 43 (I Sin[x])^7 Cos[x]^9 + 32 (I Sin[x])^6 Cos[x]^10 + 32 (I Sin[x])^10 Cos[x]^6 + 34 (I Sin[x])^8 Cos[x]^8) + Exp[13 I y] (4 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^9 Cos[x]^7 + 4 (I Sin[x])^7 Cos[x]^9 + 6 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^4 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^6) + Exp[15 I y] (1 (I Sin[x])^10 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^10))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^10 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^10) + Exp[-13 I y] (2 (I Sin[x])^11 Cos[x]^5 + 2 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^10 Cos[x]^6 + 4 (I Sin[x])^6 Cos[x]^10 + 6 (I Sin[x])^9 Cos[x]^7 + 6 (I Sin[x])^7 Cos[x]^9 + 6 (I Sin[x])^8 Cos[x]^8) + Exp[-11 I y] (37 (I Sin[x])^9 Cos[x]^7 + 37 (I Sin[x])^7 Cos[x]^9 + 38 (I Sin[x])^8 Cos[x]^8 + 22 (I Sin[x])^6 Cos[x]^10 + 22 (I Sin[x])^10 Cos[x]^6 + 17 (I Sin[x])^11 Cos[x]^5 + 17 (I Sin[x])^5 Cos[x]^11 + 8 (I Sin[x])^12 Cos[x]^4 + 8 (I Sin[x])^4 Cos[x]^12 + 2 (I Sin[x])^13 Cos[x]^3 + 2 (I Sin[x])^3 Cos[x]^13) + Exp[-9 I y] (107 (I Sin[x])^10 Cos[x]^6 + 107 (I Sin[x])^6 Cos[x]^10 + 135 (I Sin[x])^9 Cos[x]^7 + 135 (I Sin[x])^7 Cos[x]^9 + 152 (I Sin[x])^8 Cos[x]^8 + 44 (I Sin[x])^4 Cos[x]^12 + 44 (I Sin[x])^12 Cos[x]^4 + 71 (I Sin[x])^5 Cos[x]^11 + 71 (I Sin[x])^11 Cos[x]^5 + 18 (I Sin[x])^3 Cos[x]^13 + 18 (I Sin[x])^13 Cos[x]^3 + 4 (I Sin[x])^2 Cos[x]^14 + 4 (I Sin[x])^14 Cos[x]^2) + Exp[-7 I y] (488 (I Sin[x])^8 Cos[x]^8 + 431 (I Sin[x])^7 Cos[x]^9 + 431 (I Sin[x])^9 Cos[x]^7 + 341 (I Sin[x])^10 Cos[x]^6 + 341 (I Sin[x])^6 Cos[x]^10 + 202 (I Sin[x])^11 Cos[x]^5 + 202 (I Sin[x])^5 Cos[x]^11 + 96 (I Sin[x])^12 Cos[x]^4 + 96 (I Sin[x])^4 Cos[x]^12 + 37 (I Sin[x])^13 Cos[x]^3 + 37 (I Sin[x])^3 Cos[x]^13 + 12 (I Sin[x])^14 Cos[x]^2 + 12 (I Sin[x])^2 Cos[x]^14 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[-5 I y] (981 (I Sin[x])^9 Cos[x]^7 + 981 (I Sin[x])^7 Cos[x]^9 + 469 (I Sin[x])^5 Cos[x]^11 + 469 (I Sin[x])^11 Cos[x]^5 + 1050 (I Sin[x])^8 Cos[x]^8 + 750 (I Sin[x])^6 Cos[x]^10 + 750 (I Sin[x])^10 Cos[x]^6 + 206 (I Sin[x])^4 Cos[x]^12 + 206 (I Sin[x])^12 Cos[x]^4 + 60 (I Sin[x])^3 Cos[x]^13 + 60 (I Sin[x])^13 Cos[x]^3 + 10 (I Sin[x])^2 Cos[x]^14 + 10 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[-3 I y] (1668 (I Sin[x])^7 Cos[x]^9 + 1668 (I Sin[x])^9 Cos[x]^7 + 1804 (I Sin[x])^8 Cos[x]^8 + 1204 (I Sin[x])^10 Cos[x]^6 + 1204 (I Sin[x])^6 Cos[x]^10 + 714 (I Sin[x])^11 Cos[x]^5 + 714 (I Sin[x])^5 Cos[x]^11 + 344 (I Sin[x])^12 Cos[x]^4 + 344 (I Sin[x])^4 Cos[x]^12 + 132 (I Sin[x])^13 Cos[x]^3 + 132 (I Sin[x])^3 Cos[x]^13 + 34 (I Sin[x])^2 Cos[x]^14 + 34 (I Sin[x])^14 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^15 + 6 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[-1 I y] (1605 (I Sin[x])^10 Cos[x]^6 + 1605 (I Sin[x])^6 Cos[x]^10 + 2660 (I Sin[x])^8 Cos[x]^8 + 286 (I Sin[x])^4 Cos[x]^12 + 286 (I Sin[x])^12 Cos[x]^4 + 2330 (I Sin[x])^7 Cos[x]^9 + 2330 (I Sin[x])^9 Cos[x]^7 + 800 (I Sin[x])^5 Cos[x]^11 + 800 (I Sin[x])^11 Cos[x]^5 + 70 (I Sin[x])^3 Cos[x]^13 + 70 (I Sin[x])^13 Cos[x]^3 + 14 (I Sin[x])^2 Cos[x]^14 + 14 (I Sin[x])^14 Cos[x]^2) + Exp[1 I y] (1545 (I Sin[x])^6 Cos[x]^10 + 1545 (I Sin[x])^10 Cos[x]^6 + 2476 (I Sin[x])^8 Cos[x]^8 + 2152 (I Sin[x])^9 Cos[x]^7 + 2152 (I Sin[x])^7 Cos[x]^9 + 904 (I Sin[x])^11 Cos[x]^5 + 904 (I Sin[x])^5 Cos[x]^11 + 418 (I Sin[x])^12 Cos[x]^4 + 418 (I Sin[x])^4 Cos[x]^12 + 138 (I Sin[x])^3 Cos[x]^13 + 138 (I Sin[x])^13 Cos[x]^3 + 34 (I Sin[x])^2 Cos[x]^14 + 34 (I Sin[x])^14 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^15 + 6 (I Sin[x])^15 Cos[x]^1) + Exp[3 I y] (518 (I Sin[x])^11 Cos[x]^5 + 518 (I Sin[x])^5 Cos[x]^11 + 1968 (I Sin[x])^7 Cos[x]^9 + 1968 (I Sin[x])^9 Cos[x]^7 + 34 (I Sin[x])^3 Cos[x]^13 + 34 (I Sin[x])^13 Cos[x]^3 + 2278 (I Sin[x])^8 Cos[x]^8 + 158 (I Sin[x])^4 Cos[x]^12 + 158 (I Sin[x])^12 Cos[x]^4 + 1188 (I Sin[x])^10 Cos[x]^6 + 1188 (I Sin[x])^6 Cos[x]^10) + Exp[5 I y] (997 (I Sin[x])^7 Cos[x]^9 + 997 (I Sin[x])^9 Cos[x]^7 + 455 (I Sin[x])^11 Cos[x]^5 + 455 (I Sin[x])^5 Cos[x]^11 + 774 (I Sin[x])^10 Cos[x]^6 + 774 (I Sin[x])^6 Cos[x]^10 + 1030 (I Sin[x])^8 Cos[x]^8 + 190 (I Sin[x])^4 Cos[x]^12 + 190 (I Sin[x])^12 Cos[x]^4 + 60 (I Sin[x])^3 Cos[x]^13 + 60 (I Sin[x])^13 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2) + Exp[7 I y] (34 (I Sin[x])^12 Cos[x]^4 + 34 (I Sin[x])^4 Cos[x]^12 + 684 (I Sin[x])^8 Cos[x]^8 + 317 (I Sin[x])^10 Cos[x]^6 + 317 (I Sin[x])^6 Cos[x]^10 + 543 (I Sin[x])^7 Cos[x]^9 + 543 (I Sin[x])^9 Cos[x]^7 + 129 (I Sin[x])^5 Cos[x]^11 + 129 (I Sin[x])^11 Cos[x]^5) + Exp[9 I y] (115 (I Sin[x])^6 Cos[x]^10 + 115 (I Sin[x])^10 Cos[x]^6 + 164 (I Sin[x])^8 Cos[x]^8 + 145 (I Sin[x])^9 Cos[x]^7 + 145 (I Sin[x])^7 Cos[x]^9 + 70 (I Sin[x])^5 Cos[x]^11 + 70 (I Sin[x])^11 Cos[x]^5 + 34 (I Sin[x])^4 Cos[x]^12 + 34 (I Sin[x])^12 Cos[x]^4 + 9 (I Sin[x])^3 Cos[x]^13 + 9 (I Sin[x])^13 Cos[x]^3) + Exp[11 I y] (13 (I Sin[x])^11 Cos[x]^5 + 13 (I Sin[x])^5 Cos[x]^11 + 43 (I Sin[x])^9 Cos[x]^7 + 43 (I Sin[x])^7 Cos[x]^9 + 32 (I Sin[x])^6 Cos[x]^10 + 32 (I Sin[x])^10 Cos[x]^6 + 34 (I Sin[x])^8 Cos[x]^8) + Exp[13 I y] (4 (I Sin[x])^5 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^5 + 4 (I Sin[x])^9 Cos[x]^7 + 4 (I Sin[x])^7 Cos[x]^9 + 6 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^4 Cos[x]^12 + 2 (I Sin[x])^12 Cos[x]^4 + 2 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^10 Cos[x]^6) + Exp[15 I y] (1 (I Sin[x])^10 Cos[x]^6 + 1 (I Sin[x])^6 Cos[x]^10));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":698.8666666667,"max_line_length":5020,"alphanum_fraction":0.5053896785} {"size":367,"ext":"cdf","lang":"Mathematica","max_stars_count":2.0,"content":"\/* Quartus II 64-Bit Version 13.1.0 Build 162 10\/23\/2013 SJ Web Edition *\/\r\nJedecChain;\r\n\tFileRevision(JESD32A);\r\n\tDefaultMfr(6E);\r\n\r\n\tP ActionCode(Cfg)\r\n\t\tDevice PartName(EP3C16Q240) Path(\"C:\/Users\/Andy\/Downloads\/dist_board\/trig2_board_firmware\/output_files\/\") File(\"coincidence.sof\") MfrSpec(OpMask(1));\r\n\r\nChainEnd;\r\n\r\nAlteraBegin;\r\n\tChainType(JTAG);\r\nAlteraEnd;\r\n","avg_line_length":26.2142857143,"max_line_length":152,"alphanum_fraction":0.7356948229} {"size":10827,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 16;\nname = \"16v1 1 3 2 1 1 6 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^5 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^5) + Exp[-13 I y] (1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4 + 5 (I Sin[x])^10 Cos[x]^6 + 5 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^5 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^5 + 5 (I Sin[x])^7 Cos[x]^9 + 5 (I Sin[x])^9 Cos[x]^7 + 4 (I Sin[x])^8 Cos[x]^8) + Exp[-11 I y] (33 (I Sin[x])^6 Cos[x]^10 + 33 (I Sin[x])^10 Cos[x]^6 + 10 (I Sin[x])^4 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^4 + 29 (I Sin[x])^7 Cos[x]^9 + 29 (I Sin[x])^9 Cos[x]^7 + 18 (I Sin[x])^5 Cos[x]^11 + 18 (I Sin[x])^11 Cos[x]^5 + 26 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3) + Exp[-9 I y] (76 (I Sin[x])^5 Cos[x]^11 + 76 (I Sin[x])^11 Cos[x]^5 + 142 (I Sin[x])^9 Cos[x]^7 + 142 (I Sin[x])^7 Cos[x]^9 + 106 (I Sin[x])^6 Cos[x]^10 + 106 (I Sin[x])^10 Cos[x]^6 + 160 (I Sin[x])^8 Cos[x]^8 + 36 (I Sin[x])^12 Cos[x]^4 + 36 (I Sin[x])^4 Cos[x]^12 + 13 (I Sin[x])^13 Cos[x]^3 + 13 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^2 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^2) + Exp[-7 I y] (465 (I Sin[x])^7 Cos[x]^9 + 465 (I Sin[x])^9 Cos[x]^7 + 200 (I Sin[x])^5 Cos[x]^11 + 200 (I Sin[x])^11 Cos[x]^5 + 516 (I Sin[x])^8 Cos[x]^8 + 323 (I Sin[x])^6 Cos[x]^10 + 323 (I Sin[x])^10 Cos[x]^6 + 28 (I Sin[x])^3 Cos[x]^13 + 28 (I Sin[x])^13 Cos[x]^3 + 86 (I Sin[x])^4 Cos[x]^12 + 86 (I Sin[x])^12 Cos[x]^4 + 5 (I Sin[x])^2 Cos[x]^14 + 5 (I Sin[x])^14 Cos[x]^2) + Exp[-5 I y] (751 (I Sin[x])^6 Cos[x]^10 + 751 (I Sin[x])^10 Cos[x]^6 + 1108 (I Sin[x])^8 Cos[x]^8 + 1011 (I Sin[x])^7 Cos[x]^9 + 1011 (I Sin[x])^9 Cos[x]^7 + 413 (I Sin[x])^11 Cos[x]^5 + 413 (I Sin[x])^5 Cos[x]^11 + 189 (I Sin[x])^12 Cos[x]^4 + 189 (I Sin[x])^4 Cos[x]^12 + 64 (I Sin[x])^13 Cos[x]^3 + 64 (I Sin[x])^3 Cos[x]^13 + 18 (I Sin[x])^14 Cos[x]^2 + 18 (I Sin[x])^2 Cos[x]^14 + 3 (I Sin[x])^1 Cos[x]^15 + 3 (I Sin[x])^15 Cos[x]^1) + Exp[-3 I y] (2002 (I Sin[x])^8 Cos[x]^8 + 254 (I Sin[x])^4 Cos[x]^12 + 254 (I Sin[x])^12 Cos[x]^4 + 1253 (I Sin[x])^6 Cos[x]^10 + 1253 (I Sin[x])^10 Cos[x]^6 + 1766 (I Sin[x])^9 Cos[x]^7 + 1766 (I Sin[x])^7 Cos[x]^9 + 651 (I Sin[x])^5 Cos[x]^11 + 651 (I Sin[x])^11 Cos[x]^5 + 66 (I Sin[x])^3 Cos[x]^13 + 66 (I Sin[x])^13 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[-1 I y] (2195 (I Sin[x])^7 Cos[x]^9 + 2195 (I Sin[x])^9 Cos[x]^7 + 890 (I Sin[x])^5 Cos[x]^11 + 890 (I Sin[x])^11 Cos[x]^5 + 1525 (I Sin[x])^6 Cos[x]^10 + 1525 (I Sin[x])^10 Cos[x]^6 + 2478 (I Sin[x])^8 Cos[x]^8 + 400 (I Sin[x])^12 Cos[x]^4 + 400 (I Sin[x])^4 Cos[x]^12 + 144 (I Sin[x])^13 Cos[x]^3 + 144 (I Sin[x])^3 Cos[x]^13 + 35 (I Sin[x])^2 Cos[x]^14 + 35 (I Sin[x])^14 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^15 + 6 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[1 I y] (2410 (I Sin[x])^7 Cos[x]^9 + 2410 (I Sin[x])^9 Cos[x]^7 + 757 (I Sin[x])^5 Cos[x]^11 + 757 (I Sin[x])^11 Cos[x]^5 + 68 (I Sin[x])^3 Cos[x]^13 + 68 (I Sin[x])^13 Cos[x]^3 + 1557 (I Sin[x])^10 Cos[x]^6 + 1557 (I Sin[x])^6 Cos[x]^10 + 264 (I Sin[x])^4 Cos[x]^12 + 264 (I Sin[x])^12 Cos[x]^4 + 11 (I Sin[x])^2 Cos[x]^14 + 11 (I Sin[x])^14 Cos[x]^2 + 2736 (I Sin[x])^8 Cos[x]^8) + Exp[3 I y] (1784 (I Sin[x])^8 Cos[x]^8 + 1249 (I Sin[x])^10 Cos[x]^6 + 1249 (I Sin[x])^6 Cos[x]^10 + 349 (I Sin[x])^4 Cos[x]^12 + 349 (I Sin[x])^12 Cos[x]^4 + 739 (I Sin[x])^5 Cos[x]^11 + 739 (I Sin[x])^11 Cos[x]^5 + 1624 (I Sin[x])^9 Cos[x]^7 + 1624 (I Sin[x])^7 Cos[x]^9 + 117 (I Sin[x])^3 Cos[x]^13 + 117 (I Sin[x])^13 Cos[x]^3 + 30 (I Sin[x])^2 Cos[x]^14 + 30 (I Sin[x])^14 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^15 + 5 (I Sin[x])^15 Cos[x]^1) + Exp[5 I y] (715 (I Sin[x])^6 Cos[x]^10 + 715 (I Sin[x])^10 Cos[x]^6 + 1386 (I Sin[x])^8 Cos[x]^8 + 104 (I Sin[x])^4 Cos[x]^12 + 104 (I Sin[x])^12 Cos[x]^4 + 1149 (I Sin[x])^9 Cos[x]^7 + 1149 (I Sin[x])^7 Cos[x]^9 + 324 (I Sin[x])^5 Cos[x]^11 + 324 (I Sin[x])^11 Cos[x]^5 + 18 (I Sin[x])^3 Cos[x]^13 + 18 (I Sin[x])^13 Cos[x]^3) + Exp[7 I y] (432 (I Sin[x])^7 Cos[x]^9 + 432 (I Sin[x])^9 Cos[x]^7 + 224 (I Sin[x])^5 Cos[x]^11 + 224 (I Sin[x])^11 Cos[x]^5 + 341 (I Sin[x])^6 Cos[x]^10 + 341 (I Sin[x])^10 Cos[x]^6 + 440 (I Sin[x])^8 Cos[x]^8 + 104 (I Sin[x])^4 Cos[x]^12 + 104 (I Sin[x])^12 Cos[x]^4 + 37 (I Sin[x])^3 Cos[x]^13 + 37 (I Sin[x])^13 Cos[x]^3 + 7 (I Sin[x])^2 Cos[x]^14 + 7 (I Sin[x])^14 Cos[x]^2) + Exp[9 I y] (181 (I Sin[x])^7 Cos[x]^9 + 181 (I Sin[x])^9 Cos[x]^7 + 50 (I Sin[x])^5 Cos[x]^11 + 50 (I Sin[x])^11 Cos[x]^5 + 120 (I Sin[x])^10 Cos[x]^6 + 120 (I Sin[x])^6 Cos[x]^10 + 10 (I Sin[x])^4 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^4 + 188 (I Sin[x])^8 Cos[x]^8) + Exp[11 I y] (32 (I Sin[x])^8 Cos[x]^8 + 27 (I Sin[x])^10 Cos[x]^6 + 27 (I Sin[x])^6 Cos[x]^10 + 13 (I Sin[x])^4 Cos[x]^12 + 13 (I Sin[x])^12 Cos[x]^4 + 24 (I Sin[x])^7 Cos[x]^9 + 24 (I Sin[x])^9 Cos[x]^7 + 22 (I Sin[x])^5 Cos[x]^11 + 22 (I Sin[x])^11 Cos[x]^5 + 3 (I Sin[x])^3 Cos[x]^13 + 3 (I Sin[x])^13 Cos[x]^3) + Exp[13 I y] (10 (I Sin[x])^8 Cos[x]^8 + 3 (I Sin[x])^6 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^6 + 6 (I Sin[x])^9 Cos[x]^7 + 6 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^5 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^5) + Exp[15 I y] (1 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^7))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-15 I y] (1 (I Sin[x])^5 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^5) + Exp[-13 I y] (1 (I Sin[x])^4 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^4 + 5 (I Sin[x])^10 Cos[x]^6 + 5 (I Sin[x])^6 Cos[x]^10 + 2 (I Sin[x])^5 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^5 + 5 (I Sin[x])^7 Cos[x]^9 + 5 (I Sin[x])^9 Cos[x]^7 + 4 (I Sin[x])^8 Cos[x]^8) + Exp[-11 I y] (33 (I Sin[x])^6 Cos[x]^10 + 33 (I Sin[x])^10 Cos[x]^6 + 10 (I Sin[x])^4 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^4 + 29 (I Sin[x])^7 Cos[x]^9 + 29 (I Sin[x])^9 Cos[x]^7 + 18 (I Sin[x])^5 Cos[x]^11 + 18 (I Sin[x])^11 Cos[x]^5 + 26 (I Sin[x])^8 Cos[x]^8 + 2 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^13 Cos[x]^3) + Exp[-9 I y] (76 (I Sin[x])^5 Cos[x]^11 + 76 (I Sin[x])^11 Cos[x]^5 + 142 (I Sin[x])^9 Cos[x]^7 + 142 (I Sin[x])^7 Cos[x]^9 + 106 (I Sin[x])^6 Cos[x]^10 + 106 (I Sin[x])^10 Cos[x]^6 + 160 (I Sin[x])^8 Cos[x]^8 + 36 (I Sin[x])^12 Cos[x]^4 + 36 (I Sin[x])^4 Cos[x]^12 + 13 (I Sin[x])^13 Cos[x]^3 + 13 (I Sin[x])^3 Cos[x]^13 + 2 (I Sin[x])^2 Cos[x]^14 + 2 (I Sin[x])^14 Cos[x]^2) + Exp[-7 I y] (465 (I Sin[x])^7 Cos[x]^9 + 465 (I Sin[x])^9 Cos[x]^7 + 200 (I Sin[x])^5 Cos[x]^11 + 200 (I Sin[x])^11 Cos[x]^5 + 516 (I Sin[x])^8 Cos[x]^8 + 323 (I Sin[x])^6 Cos[x]^10 + 323 (I Sin[x])^10 Cos[x]^6 + 28 (I Sin[x])^3 Cos[x]^13 + 28 (I Sin[x])^13 Cos[x]^3 + 86 (I Sin[x])^4 Cos[x]^12 + 86 (I Sin[x])^12 Cos[x]^4 + 5 (I Sin[x])^2 Cos[x]^14 + 5 (I Sin[x])^14 Cos[x]^2) + Exp[-5 I y] (751 (I Sin[x])^6 Cos[x]^10 + 751 (I Sin[x])^10 Cos[x]^6 + 1108 (I Sin[x])^8 Cos[x]^8 + 1011 (I Sin[x])^7 Cos[x]^9 + 1011 (I Sin[x])^9 Cos[x]^7 + 413 (I Sin[x])^11 Cos[x]^5 + 413 (I Sin[x])^5 Cos[x]^11 + 189 (I Sin[x])^12 Cos[x]^4 + 189 (I Sin[x])^4 Cos[x]^12 + 64 (I Sin[x])^13 Cos[x]^3 + 64 (I Sin[x])^3 Cos[x]^13 + 18 (I Sin[x])^14 Cos[x]^2 + 18 (I Sin[x])^2 Cos[x]^14 + 3 (I Sin[x])^1 Cos[x]^15 + 3 (I Sin[x])^15 Cos[x]^1) + Exp[-3 I y] (2002 (I Sin[x])^8 Cos[x]^8 + 254 (I Sin[x])^4 Cos[x]^12 + 254 (I Sin[x])^12 Cos[x]^4 + 1253 (I Sin[x])^6 Cos[x]^10 + 1253 (I Sin[x])^10 Cos[x]^6 + 1766 (I Sin[x])^9 Cos[x]^7 + 1766 (I Sin[x])^7 Cos[x]^9 + 651 (I Sin[x])^5 Cos[x]^11 + 651 (I Sin[x])^11 Cos[x]^5 + 66 (I Sin[x])^3 Cos[x]^13 + 66 (I Sin[x])^13 Cos[x]^3 + 12 (I Sin[x])^2 Cos[x]^14 + 12 (I Sin[x])^14 Cos[x]^2 + 2 (I Sin[x])^1 Cos[x]^15 + 2 (I Sin[x])^15 Cos[x]^1) + Exp[-1 I y] (2195 (I Sin[x])^7 Cos[x]^9 + 2195 (I Sin[x])^9 Cos[x]^7 + 890 (I Sin[x])^5 Cos[x]^11 + 890 (I Sin[x])^11 Cos[x]^5 + 1525 (I Sin[x])^6 Cos[x]^10 + 1525 (I Sin[x])^10 Cos[x]^6 + 2478 (I Sin[x])^8 Cos[x]^8 + 400 (I Sin[x])^12 Cos[x]^4 + 400 (I Sin[x])^4 Cos[x]^12 + 144 (I Sin[x])^13 Cos[x]^3 + 144 (I Sin[x])^3 Cos[x]^13 + 35 (I Sin[x])^2 Cos[x]^14 + 35 (I Sin[x])^14 Cos[x]^2 + 6 (I Sin[x])^1 Cos[x]^15 + 6 (I Sin[x])^15 Cos[x]^1 + 1 Cos[x]^16 + 1 (I Sin[x])^16) + Exp[1 I y] (2410 (I Sin[x])^7 Cos[x]^9 + 2410 (I Sin[x])^9 Cos[x]^7 + 757 (I Sin[x])^5 Cos[x]^11 + 757 (I Sin[x])^11 Cos[x]^5 + 68 (I Sin[x])^3 Cos[x]^13 + 68 (I Sin[x])^13 Cos[x]^3 + 1557 (I Sin[x])^10 Cos[x]^6 + 1557 (I Sin[x])^6 Cos[x]^10 + 264 (I Sin[x])^4 Cos[x]^12 + 264 (I Sin[x])^12 Cos[x]^4 + 11 (I Sin[x])^2 Cos[x]^14 + 11 (I Sin[x])^14 Cos[x]^2 + 2736 (I Sin[x])^8 Cos[x]^8) + Exp[3 I y] (1784 (I Sin[x])^8 Cos[x]^8 + 1249 (I Sin[x])^10 Cos[x]^6 + 1249 (I Sin[x])^6 Cos[x]^10 + 349 (I Sin[x])^4 Cos[x]^12 + 349 (I Sin[x])^12 Cos[x]^4 + 739 (I Sin[x])^5 Cos[x]^11 + 739 (I Sin[x])^11 Cos[x]^5 + 1624 (I Sin[x])^9 Cos[x]^7 + 1624 (I Sin[x])^7 Cos[x]^9 + 117 (I Sin[x])^3 Cos[x]^13 + 117 (I Sin[x])^13 Cos[x]^3 + 30 (I Sin[x])^2 Cos[x]^14 + 30 (I Sin[x])^14 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^15 + 5 (I Sin[x])^15 Cos[x]^1) + Exp[5 I y] (715 (I Sin[x])^6 Cos[x]^10 + 715 (I Sin[x])^10 Cos[x]^6 + 1386 (I Sin[x])^8 Cos[x]^8 + 104 (I Sin[x])^4 Cos[x]^12 + 104 (I Sin[x])^12 Cos[x]^4 + 1149 (I Sin[x])^9 Cos[x]^7 + 1149 (I Sin[x])^7 Cos[x]^9 + 324 (I Sin[x])^5 Cos[x]^11 + 324 (I Sin[x])^11 Cos[x]^5 + 18 (I Sin[x])^3 Cos[x]^13 + 18 (I Sin[x])^13 Cos[x]^3) + Exp[7 I y] (432 (I Sin[x])^7 Cos[x]^9 + 432 (I Sin[x])^9 Cos[x]^7 + 224 (I Sin[x])^5 Cos[x]^11 + 224 (I Sin[x])^11 Cos[x]^5 + 341 (I Sin[x])^6 Cos[x]^10 + 341 (I Sin[x])^10 Cos[x]^6 + 440 (I Sin[x])^8 Cos[x]^8 + 104 (I Sin[x])^4 Cos[x]^12 + 104 (I Sin[x])^12 Cos[x]^4 + 37 (I Sin[x])^3 Cos[x]^13 + 37 (I Sin[x])^13 Cos[x]^3 + 7 (I Sin[x])^2 Cos[x]^14 + 7 (I Sin[x])^14 Cos[x]^2) + Exp[9 I y] (181 (I Sin[x])^7 Cos[x]^9 + 181 (I Sin[x])^9 Cos[x]^7 + 50 (I Sin[x])^5 Cos[x]^11 + 50 (I Sin[x])^11 Cos[x]^5 + 120 (I Sin[x])^10 Cos[x]^6 + 120 (I Sin[x])^6 Cos[x]^10 + 10 (I Sin[x])^4 Cos[x]^12 + 10 (I Sin[x])^12 Cos[x]^4 + 188 (I Sin[x])^8 Cos[x]^8) + Exp[11 I y] (32 (I Sin[x])^8 Cos[x]^8 + 27 (I Sin[x])^10 Cos[x]^6 + 27 (I Sin[x])^6 Cos[x]^10 + 13 (I Sin[x])^4 Cos[x]^12 + 13 (I Sin[x])^12 Cos[x]^4 + 24 (I Sin[x])^7 Cos[x]^9 + 24 (I Sin[x])^9 Cos[x]^7 + 22 (I Sin[x])^5 Cos[x]^11 + 22 (I Sin[x])^11 Cos[x]^5 + 3 (I Sin[x])^3 Cos[x]^13 + 3 (I Sin[x])^13 Cos[x]^3) + Exp[13 I y] (10 (I Sin[x])^8 Cos[x]^8 + 3 (I Sin[x])^6 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^6 + 6 (I Sin[x])^9 Cos[x]^7 + 6 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^5 Cos[x]^11 + 1 (I Sin[x])^11 Cos[x]^5) + Exp[15 I y] (1 (I Sin[x])^7 Cos[x]^9 + 1 (I Sin[x])^9 Cos[x]^7));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":721.8,"max_line_length":5191,"alphanum_fraction":0.5054955205} {"size":7406,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"(***********************************************************************\r\n\r\n Mathematica-Compatible Notebook\r\n\r\nThis notebook can be used on any computer system with Mathematica 4.0,\r\nMathReader 4.0, or any compatible application. The data for the notebook \r\nstarts with the line containing stars above.\r\n\r\nTo get the notebook into a Mathematica-compatible application, do one of \r\nthe following:\r\n\r\n* Save the data starting with the line of stars above into a file\r\n with a name ending in .nb, then open the file inside the application;\r\n\r\n* Copy the data starting with the line of stars above to the\r\n clipboard, then use the Paste menu command inside the application.\r\n\r\nData for notebooks contains only printable 7-bit ASCII and can be\r\nsent directly in email or through ftp in text mode. 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If you edit this Notebook file directly, not using\r\nMathematica, you must remove the line containing CacheID at the top of \r\nthe file. The cache data will then be recreated when you save this file \r\nfrom within Mathematica.\r\n***********************************************************************)\r\n\r\n(*CellTagsOutline\r\nCellTagsIndex->{}\r\n*)\r\n\r\n(*CellTagsIndex\r\nCellTagsIndex->{}\r\n*)\r\n\r\n(*NotebookFileOutline\r\nNotebook[{\r\nCell[1717, 49, 325, 6, 130, \"Input\"],\r\n\r\nCell[CellGroupData[{\r\nCell[2067, 59, 53, 1, 30, \"Input\"],\r\nCell[2123, 62, 73, 1, 29, \"Output\"]\r\n}, Open ]],\r\n\r\nCell[CellGroupData[{\r\nCell[2233, 68, 75, 1, 30, \"Input\"],\r\nCell[2311, 71, 161, 3, 24, \"Message\"],\r\nCell[2475, 76, 76, 1, 29, \"Output\"]\r\n}, Open ]],\r\n\r\nCell[CellGroupData[{\r\nCell[2588, 82, 165, 3, 30, \"Input\"],\r\nCell[2756, 87, 132, 2, 42, \"Output\"]\r\n}, Open ]],\r\n\r\nCell[CellGroupData[{\r\nCell[2925, 94, 139, 2, 30, \"Input\"],\r\nCell[3067, 98, 86, 1, 24, \"Message\"],\r\nCell[3156, 101, 86, 1, 24, \"Message\"],\r\nCell[3245, 104, 86, 1, 24, \"Message\"],\r\nCell[3334, 107, 165, 3, 24, \"Message\"],\r\nCell[3502, 112, 1029, 26, 48, \"Output\"]\r\n}, Open ]],\r\n\r\nCell[CellGroupData[{\r\nCell[4568, 143, 71, 1, 30, \"Input\"],\r\nCell[4642, 146, 103, 2, 29, \"Output\"]\r\n}, Open ]],\r\n\r\nCell[CellGroupData[{\r\nCell[4782, 153, 106, 2, 30, \"Input\"],\r\nCell[4891, 157, 513, 7, 83, \"Output\"]\r\n}, Open ]]\r\n}\r\n]\r\n*)\r\n\r\n\r\n\r\n\r\n(***********************************************************************\r\nEnd of Mathematica Notebook file.\r\n***********************************************************************)\r\n\r\n","avg_line_length":30.9874476987,"max_line_length":80,"alphanum_fraction":0.4914933837} {"size":7479,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 13;\nname = \"13v4 3 1 1 1 1 1 1\";\nnstates = 4;\n\namplitude[x_,y_] := (Exp[-12 I y] (1 (I Sin[x])^6 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^6) + Exp[-10 I y] (5 (I Sin[x])^5 Cos[x]^8 + 5 (I Sin[x])^8 Cos[x]^5 + 4 (I Sin[x])^6 Cos[x]^7 + 4 (I Sin[x])^7 Cos[x]^6 + 2 (I Sin[x])^4 Cos[x]^9 + 2 (I Sin[x])^9 Cos[x]^4 + 1 (I Sin[x])^3 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^3) + Exp[-8 I y] (31 (I Sin[x])^7 Cos[x]^6 + 31 (I Sin[x])^6 Cos[x]^7 + 21 (I Sin[x])^5 Cos[x]^8 + 21 (I Sin[x])^8 Cos[x]^5 + 11 (I Sin[x])^9 Cos[x]^4 + 11 (I Sin[x])^4 Cos[x]^9 + 3 (I Sin[x])^3 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^3) + Exp[-6 I y] (49 (I Sin[x])^4 Cos[x]^9 + 49 (I Sin[x])^9 Cos[x]^4 + 64 (I Sin[x])^5 Cos[x]^8 + 64 (I Sin[x])^8 Cos[x]^5 + 80 (I Sin[x])^6 Cos[x]^7 + 80 (I Sin[x])^7 Cos[x]^6 + 21 (I Sin[x])^3 Cos[x]^10 + 21 (I Sin[x])^10 Cos[x]^3 + 6 (I Sin[x])^2 Cos[x]^11 + 6 (I Sin[x])^11 Cos[x]^2) + Exp[-4 I y] (170 (I Sin[x])^8 Cos[x]^5 + 170 (I Sin[x])^5 Cos[x]^8 + 220 (I Sin[x])^6 Cos[x]^7 + 220 (I Sin[x])^7 Cos[x]^6 + 78 (I Sin[x])^4 Cos[x]^9 + 78 (I Sin[x])^9 Cos[x]^4 + 23 (I Sin[x])^10 Cos[x]^3 + 23 (I Sin[x])^3 Cos[x]^10 + 4 (I Sin[x])^2 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^2) + Exp[-2 I y] (62 (I Sin[x])^3 Cos[x]^10 + 62 (I Sin[x])^10 Cos[x]^3 + 322 (I Sin[x])^6 Cos[x]^7 + 322 (I Sin[x])^7 Cos[x]^6 + 250 (I Sin[x])^5 Cos[x]^8 + 250 (I Sin[x])^8 Cos[x]^5 + 135 (I Sin[x])^4 Cos[x]^9 + 135 (I Sin[x])^9 Cos[x]^4 + 18 (I Sin[x])^2 Cos[x]^11 + 18 (I Sin[x])^11 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^12 + 5 (I Sin[x])^12 Cos[x]^1) + Exp[0 I y] (141 (I Sin[x])^9 Cos[x]^4 + 141 (I Sin[x])^4 Cos[x]^9 + 446 (I Sin[x])^7 Cos[x]^6 + 446 (I Sin[x])^6 Cos[x]^7 + 282 (I Sin[x])^5 Cos[x]^8 + 282 (I Sin[x])^8 Cos[x]^5 + 45 (I Sin[x])^3 Cos[x]^10 + 45 (I Sin[x])^10 Cos[x]^3 + 9 (I Sin[x])^2 Cos[x]^11 + 9 (I Sin[x])^11 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^1) + Exp[2 I y] (22 (I Sin[x])^2 Cos[x]^11 + 22 (I Sin[x])^11 Cos[x]^2 + 314 (I Sin[x])^7 Cos[x]^6 + 314 (I Sin[x])^6 Cos[x]^7 + 241 (I Sin[x])^5 Cos[x]^8 + 241 (I Sin[x])^8 Cos[x]^5 + 149 (I Sin[x])^4 Cos[x]^9 + 149 (I Sin[x])^9 Cos[x]^4 + 62 (I Sin[x])^3 Cos[x]^10 + 62 (I Sin[x])^10 Cos[x]^3 + 3 (I Sin[x])^1 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^1 + 1 Cos[x]^13 + 1 (I Sin[x])^13) + Exp[4 I y] (168 (I Sin[x])^8 Cos[x]^5 + 168 (I Sin[x])^5 Cos[x]^8 + 209 (I Sin[x])^6 Cos[x]^7 + 209 (I Sin[x])^7 Cos[x]^6 + 79 (I Sin[x])^4 Cos[x]^9 + 79 (I Sin[x])^9 Cos[x]^4 + 7 (I Sin[x])^2 Cos[x]^11 + 7 (I Sin[x])^11 Cos[x]^2 + 31 (I Sin[x])^3 Cos[x]^10 + 31 (I Sin[x])^10 Cos[x]^3 + 1 (I Sin[x])^12 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^12) + Exp[6 I y] (3 (I Sin[x])^1 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^1 + 65 (I Sin[x])^8 Cos[x]^5 + 65 (I Sin[x])^5 Cos[x]^8 + 27 (I Sin[x])^3 Cos[x]^10 + 27 (I Sin[x])^10 Cos[x]^3 + 70 (I Sin[x])^6 Cos[x]^7 + 70 (I Sin[x])^7 Cos[x]^6 + 47 (I Sin[x])^4 Cos[x]^9 + 47 (I Sin[x])^9 Cos[x]^4 + 8 (I Sin[x])^2 Cos[x]^11 + 8 (I Sin[x])^11 Cos[x]^2) + Exp[8 I y] (21 (I Sin[x])^9 Cos[x]^4 + 21 (I Sin[x])^4 Cos[x]^9 + 17 (I Sin[x])^7 Cos[x]^6 + 17 (I Sin[x])^6 Cos[x]^7 + 19 (I Sin[x])^5 Cos[x]^8 + 19 (I Sin[x])^8 Cos[x]^5 + 7 (I Sin[x])^3 Cos[x]^10 + 7 (I Sin[x])^10 Cos[x]^3 + 2 (I Sin[x])^11 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^11) + Exp[10 I y] (2 (I Sin[x])^2 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^2 + 3 (I Sin[x])^9 Cos[x]^4 + 3 (I Sin[x])^4 Cos[x]^9 + 2 (I Sin[x])^7 Cos[x]^6 + 2 (I Sin[x])^6 Cos[x]^7 + 2 (I Sin[x])^5 Cos[x]^8 + 2 (I Sin[x])^8 Cos[x]^5 + 3 (I Sin[x])^3 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^3) + Exp[12 I y] (1 (I Sin[x])^10 Cos[x]^3 + 1 (I Sin[x])^3 Cos[x]^10))\/Sqrt[2^nqubits];\namplitude2[x_,y_] := (Exp[-12 I y] (1 (I Sin[x])^6 Cos[x]^7 + 1 (I Sin[x])^7 Cos[x]^6) + Exp[-10 I y] (5 (I Sin[x])^5 Cos[x]^8 + 5 (I Sin[x])^8 Cos[x]^5 + 4 (I Sin[x])^6 Cos[x]^7 + 4 (I Sin[x])^7 Cos[x]^6 + 2 (I Sin[x])^4 Cos[x]^9 + 2 (I Sin[x])^9 Cos[x]^4 + 1 (I Sin[x])^3 Cos[x]^10 + 1 (I Sin[x])^10 Cos[x]^3) + Exp[-8 I y] (31 (I Sin[x])^7 Cos[x]^6 + 31 (I Sin[x])^6 Cos[x]^7 + 21 (I Sin[x])^5 Cos[x]^8 + 21 (I Sin[x])^8 Cos[x]^5 + 11 (I Sin[x])^9 Cos[x]^4 + 11 (I Sin[x])^4 Cos[x]^9 + 3 (I Sin[x])^3 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^3) + Exp[-6 I y] (49 (I Sin[x])^4 Cos[x]^9 + 49 (I Sin[x])^9 Cos[x]^4 + 64 (I Sin[x])^5 Cos[x]^8 + 64 (I Sin[x])^8 Cos[x]^5 + 80 (I Sin[x])^6 Cos[x]^7 + 80 (I Sin[x])^7 Cos[x]^6 + 21 (I Sin[x])^3 Cos[x]^10 + 21 (I Sin[x])^10 Cos[x]^3 + 6 (I Sin[x])^2 Cos[x]^11 + 6 (I Sin[x])^11 Cos[x]^2) + Exp[-4 I y] (170 (I Sin[x])^8 Cos[x]^5 + 170 (I Sin[x])^5 Cos[x]^8 + 220 (I Sin[x])^6 Cos[x]^7 + 220 (I Sin[x])^7 Cos[x]^6 + 78 (I Sin[x])^4 Cos[x]^9 + 78 (I Sin[x])^9 Cos[x]^4 + 23 (I Sin[x])^10 Cos[x]^3 + 23 (I Sin[x])^3 Cos[x]^10 + 4 (I Sin[x])^2 Cos[x]^11 + 4 (I Sin[x])^11 Cos[x]^2) + Exp[-2 I y] (62 (I Sin[x])^3 Cos[x]^10 + 62 (I Sin[x])^10 Cos[x]^3 + 322 (I Sin[x])^6 Cos[x]^7 + 322 (I Sin[x])^7 Cos[x]^6 + 250 (I Sin[x])^5 Cos[x]^8 + 250 (I Sin[x])^8 Cos[x]^5 + 135 (I Sin[x])^4 Cos[x]^9 + 135 (I Sin[x])^9 Cos[x]^4 + 18 (I Sin[x])^2 Cos[x]^11 + 18 (I Sin[x])^11 Cos[x]^2 + 5 (I Sin[x])^1 Cos[x]^12 + 5 (I Sin[x])^12 Cos[x]^1) + Exp[0 I y] (141 (I Sin[x])^9 Cos[x]^4 + 141 (I Sin[x])^4 Cos[x]^9 + 446 (I Sin[x])^7 Cos[x]^6 + 446 (I Sin[x])^6 Cos[x]^7 + 282 (I Sin[x])^5 Cos[x]^8 + 282 (I Sin[x])^8 Cos[x]^5 + 45 (I Sin[x])^3 Cos[x]^10 + 45 (I Sin[x])^10 Cos[x]^3 + 9 (I Sin[x])^2 Cos[x]^11 + 9 (I Sin[x])^11 Cos[x]^2 + 1 (I Sin[x])^1 Cos[x]^12 + 1 (I Sin[x])^12 Cos[x]^1) + Exp[2 I y] (22 (I Sin[x])^2 Cos[x]^11 + 22 (I Sin[x])^11 Cos[x]^2 + 314 (I Sin[x])^7 Cos[x]^6 + 314 (I Sin[x])^6 Cos[x]^7 + 241 (I Sin[x])^5 Cos[x]^8 + 241 (I Sin[x])^8 Cos[x]^5 + 149 (I Sin[x])^4 Cos[x]^9 + 149 (I Sin[x])^9 Cos[x]^4 + 62 (I Sin[x])^3 Cos[x]^10 + 62 (I Sin[x])^10 Cos[x]^3 + 3 (I Sin[x])^1 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^1 + 1 Cos[x]^13 + 1 (I Sin[x])^13) + Exp[4 I y] (168 (I Sin[x])^8 Cos[x]^5 + 168 (I Sin[x])^5 Cos[x]^8 + 209 (I Sin[x])^6 Cos[x]^7 + 209 (I Sin[x])^7 Cos[x]^6 + 79 (I Sin[x])^4 Cos[x]^9 + 79 (I Sin[x])^9 Cos[x]^4 + 7 (I Sin[x])^2 Cos[x]^11 + 7 (I Sin[x])^11 Cos[x]^2 + 31 (I Sin[x])^3 Cos[x]^10 + 31 (I Sin[x])^10 Cos[x]^3 + 1 (I Sin[x])^12 Cos[x]^1 + 1 (I Sin[x])^1 Cos[x]^12) + Exp[6 I y] (3 (I Sin[x])^1 Cos[x]^12 + 3 (I Sin[x])^12 Cos[x]^1 + 65 (I Sin[x])^8 Cos[x]^5 + 65 (I Sin[x])^5 Cos[x]^8 + 27 (I Sin[x])^3 Cos[x]^10 + 27 (I Sin[x])^10 Cos[x]^3 + 70 (I Sin[x])^6 Cos[x]^7 + 70 (I Sin[x])^7 Cos[x]^6 + 47 (I Sin[x])^4 Cos[x]^9 + 47 (I Sin[x])^9 Cos[x]^4 + 8 (I Sin[x])^2 Cos[x]^11 + 8 (I Sin[x])^11 Cos[x]^2) + Exp[8 I y] (21 (I Sin[x])^9 Cos[x]^4 + 21 (I Sin[x])^4 Cos[x]^9 + 17 (I Sin[x])^7 Cos[x]^6 + 17 (I Sin[x])^6 Cos[x]^7 + 19 (I Sin[x])^5 Cos[x]^8 + 19 (I Sin[x])^8 Cos[x]^5 + 7 (I Sin[x])^3 Cos[x]^10 + 7 (I Sin[x])^10 Cos[x]^3 + 2 (I Sin[x])^11 Cos[x]^2 + 2 (I Sin[x])^2 Cos[x]^11) + Exp[10 I y] (2 (I Sin[x])^2 Cos[x]^11 + 2 (I Sin[x])^11 Cos[x]^2 + 3 (I Sin[x])^9 Cos[x]^4 + 3 (I Sin[x])^4 Cos[x]^9 + 2 (I Sin[x])^7 Cos[x]^6 + 2 (I Sin[x])^6 Cos[x]^7 + 2 (I Sin[x])^5 Cos[x]^8 + 2 (I Sin[x])^8 Cos[x]^5 + 3 (I Sin[x])^3 Cos[x]^10 + 3 (I Sin[x])^10 Cos[x]^3) + Exp[12 I y] (1 (I Sin[x])^10 Cos[x]^3 + 1 (I Sin[x])^3 Cos[x]^10));\nprobability[x_, y_] := Abs[amplitude[x, y]]^2;\n\nresult = NMaximize[{nstates*probability[a, b], 0 < a < Pi\/2, 0 < b < Pi}, {a, b}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nf = probability[c, d]; n = Pi;\nPlot3D[f, {c, 0, n\/2}, {d, -n, n}, PlotRange -> All]\nContourPlot[probability[x, y], {x, 0, n\/2}, {y, 0, n}, PlotLegends -> Automatic, Contours -> 30]\n","avg_line_length":498.6,"max_line_length":3517,"alphanum_fraction":0.4924455141} {"size":15147,"ext":"nb","lang":"Mathematica","max_stars_count":null,"content":"nqubits = 15;\nname = \"15v1\";\nnstates = 30;\n\namplitude[x1_,y1_,x2_,y2_] := (Exp[-105.0 I y2]*(Exp[-105.0 I y1] (1 Cos[x1]^15 + 1 (-I Sin[x1])^15) + Exp[-77.0 I y1] (15 (-I Sin[x1])^1 Cos[x1]^14 + 15 (-I Sin[x1])^14 Cos[x1]^1) + Exp[-53.0 I y1] (105 (-I Sin[x1])^2 Cos[x1]^13 + 105 (-I Sin[x1])^13 Cos[x1]^2) + Exp[-33.0 I y1] (455 (-I Sin[x1])^3 Cos[x1]^12 + 455 (-I Sin[x1])^12 Cos[x1]^3) + Exp[-17.0 I y1] (1365 (-I Sin[x1])^4 Cos[x1]^11 + 1365 (-I Sin[x1])^11 Cos[x1]^4) + Exp[-5.0 I y1] (3003 (-I Sin[x1])^5 Cos[x1]^10 + 3003 (-I Sin[x1])^10 Cos[x1]^5) + Exp[3.0 I y1] (5005 (-I Sin[x1])^6 Cos[x1]^9 + 5005 (-I Sin[x1])^9 Cos[x1]^6) + Exp[7.0 I y1] (6435 (-I Sin[x1])^7 Cos[x1]^8 + 6435 (-I Sin[x1])^8 Cos[x1]^7))*(1 (-I Sin[x2])^1 Cos[x2]^14 + 1 (-I Sin[x2])^14 Cos[x2]^1) + Exp[-77.0 I y2]*(Exp[-105.0 I y1] (1 (-I Sin[x1])^1 Cos[x1]^14 + 1 (-I Sin[x1])^14 Cos[x1]^1) + Exp[-77.0 I y1] (1 Cos[x1]^15 + 1 (-I Sin[x1])^15 + 14 (-I Sin[x1])^2 Cos[x1]^13 + 14 (-I Sin[x1])^13 Cos[x1]^2) + Exp[-53.0 I y1] (14 (-I Sin[x1])^1 Cos[x1]^14 + 14 (-I Sin[x1])^14 Cos[x1]^1 + 91 (-I Sin[x1])^3 Cos[x1]^12 + 91 (-I Sin[x1])^12 Cos[x1]^3) + Exp[-33.0 I y1] (91 (-I Sin[x1])^2 Cos[x1]^13 + 91 (-I Sin[x1])^13 Cos[x1]^2 + 364 (-I Sin[x1])^4 Cos[x1]^11 + 364 (-I Sin[x1])^11 Cos[x1]^4) + Exp[-17.0 I y1] (364 (-I Sin[x1])^3 Cos[x1]^12 + 364 (-I Sin[x1])^12 Cos[x1]^3 + 1001 (-I Sin[x1])^5 Cos[x1]^10 + 1001 (-I Sin[x1])^10 Cos[x1]^5) + Exp[-5.0 I y1] (1001 (-I Sin[x1])^4 Cos[x1]^11 + 1001 (-I Sin[x1])^11 Cos[x1]^4 + 2002 (-I Sin[x1])^6 Cos[x1]^9 + 2002 (-I Sin[x1])^9 Cos[x1]^6) + Exp[3.0 I y1] (2002 (-I Sin[x1])^5 Cos[x1]^10 + 2002 (-I Sin[x1])^10 Cos[x1]^5 + 3003 (-I Sin[x1])^7 Cos[x1]^8 + 3003 (-I Sin[x1])^8 Cos[x1]^7) + Exp[7.0 I y1] (3003 (-I Sin[x1])^6 Cos[x1]^9 + 3003 (-I Sin[x1])^9 Cos[x1]^6 + 3432 (-I Sin[x1])^8 Cos[x1]^7 + 3432 (-I Sin[x1])^7 Cos[x1]^8))*(1 Cos[x2]^15 + 1 (-I Sin[x2])^15 + 14 (-I Sin[x2])^2 Cos[x2]^13 + 14 (-I Sin[x2])^13 Cos[x2]^2) + Exp[-53.0 I y2]*(Exp[-105.0 I y1] (1 (-I Sin[x1])^2 Cos[x1]^13 + 1 (-I Sin[x1])^13 Cos[x1]^2) + Exp[-77.0 I y1] (2 (-I Sin[x1])^1 Cos[x1]^14 + 2 (-I Sin[x1])^14 Cos[x1]^1 + 13 (-I Sin[x1])^3 Cos[x1]^12 + 13 (-I Sin[x1])^12 Cos[x1]^3) + Exp[-53.0 I y1] (1 Cos[x1]^15 + 1 (-I Sin[x1])^15 + 26 (-I Sin[x1])^2 Cos[x1]^13 + 26 (-I Sin[x1])^13 Cos[x1]^2 + 78 (-I Sin[x1])^4 Cos[x1]^11 + 78 (-I Sin[x1])^11 Cos[x1]^4) + Exp[-33.0 I y1] (13 (-I Sin[x1])^1 Cos[x1]^14 + 13 (-I Sin[x1])^14 Cos[x1]^1 + 156 (-I Sin[x1])^3 Cos[x1]^12 + 156 (-I Sin[x1])^12 Cos[x1]^3 + 286 (-I Sin[x1])^5 Cos[x1]^10 + 286 (-I Sin[x1])^10 Cos[x1]^5) + Exp[-17.0 I y1] (78 (-I Sin[x1])^2 Cos[x1]^13 + 78 (-I Sin[x1])^13 Cos[x1]^2 + 572 (-I Sin[x1])^4 Cos[x1]^11 + 572 (-I Sin[x1])^11 Cos[x1]^4 + 715 (-I Sin[x1])^6 Cos[x1]^9 + 715 (-I Sin[x1])^9 Cos[x1]^6) + Exp[-5.0 I y1] (286 (-I Sin[x1])^3 Cos[x1]^12 + 286 (-I Sin[x1])^12 Cos[x1]^3 + 1430 (-I Sin[x1])^5 Cos[x1]^10 + 1430 (-I Sin[x1])^10 Cos[x1]^5 + 1287 (-I Sin[x1])^7 Cos[x1]^8 + 1287 (-I Sin[x1])^8 Cos[x1]^7) + Exp[3.0 I y1] (715 (-I Sin[x1])^4 Cos[x1]^11 + 715 (-I Sin[x1])^11 Cos[x1]^4 + 2574 (-I Sin[x1])^6 Cos[x1]^9 + 2574 (-I Sin[x1])^9 Cos[x1]^6 + 1716 (-I Sin[x1])^8 Cos[x1]^7 + 1716 (-I Sin[x1])^7 Cos[x1]^8) + Exp[7.0 I y1] (1287 (-I Sin[x1])^5 Cos[x1]^10 + 1287 (-I Sin[x1])^10 Cos[x1]^5 + 3432 (-I Sin[x1])^7 Cos[x1]^8 + 3432 (-I Sin[x1])^8 Cos[x1]^7 + 1716 (-I Sin[x1])^6 Cos[x1]^9 + 1716 (-I Sin[x1])^9 Cos[x1]^6))*(14 (-I Sin[x2])^1 Cos[x2]^14 + 14 (-I Sin[x2])^14 Cos[x2]^1 + 91 (-I Sin[x2])^3 Cos[x2]^12 + 91 (-I Sin[x2])^12 Cos[x2]^3) + Exp[-33.0 I y2]*(Exp[-105.0 I y1] (1 (-I Sin[x1])^3 Cos[x1]^12 + 1 (-I Sin[x1])^12 Cos[x1]^3) + Exp[-77.0 I y1] (3 (-I Sin[x1])^2 Cos[x1]^13 + 3 (-I Sin[x1])^13 Cos[x1]^2 + 12 (-I Sin[x1])^4 Cos[x1]^11 + 12 (-I Sin[x1])^11 Cos[x1]^4) + Exp[-53.0 I y1] (3 (-I Sin[x1])^1 Cos[x1]^14 + 3 (-I Sin[x1])^14 Cos[x1]^1 + 36 (-I Sin[x1])^3 Cos[x1]^12 + 36 (-I Sin[x1])^12 Cos[x1]^3 + 66 (-I Sin[x1])^5 Cos[x1]^10 + 66 (-I Sin[x1])^10 Cos[x1]^5) + Exp[-33.0 I y1] (1 Cos[x1]^15 + 1 (-I Sin[x1])^15 + 36 (-I Sin[x1])^2 Cos[x1]^13 + 36 (-I Sin[x1])^13 Cos[x1]^2 + 198 (-I Sin[x1])^4 Cos[x1]^11 + 198 (-I Sin[x1])^11 Cos[x1]^4 + 220 (-I Sin[x1])^6 Cos[x1]^9 + 220 (-I Sin[x1])^9 Cos[x1]^6) + Exp[-17.0 I y1] (12 (-I Sin[x1])^1 Cos[x1]^14 + 12 (-I Sin[x1])^14 Cos[x1]^1 + 198 (-I Sin[x1])^3 Cos[x1]^12 + 198 (-I Sin[x1])^12 Cos[x1]^3 + 660 (-I Sin[x1])^5 Cos[x1]^10 + 660 (-I Sin[x1])^10 Cos[x1]^5 + 495 (-I Sin[x1])^7 Cos[x1]^8 + 495 (-I Sin[x1])^8 Cos[x1]^7) + Exp[-5.0 I y1] (66 (-I Sin[x1])^2 Cos[x1]^13 + 66 (-I Sin[x1])^13 Cos[x1]^2 + 660 (-I Sin[x1])^4 Cos[x1]^11 + 660 (-I Sin[x1])^11 Cos[x1]^4 + 1485 (-I Sin[x1])^6 Cos[x1]^9 + 1485 (-I Sin[x1])^9 Cos[x1]^6 + 792 (-I Sin[x1])^8 Cos[x1]^7 + 792 (-I Sin[x1])^7 Cos[x1]^8) + Exp[3.0 I y1] (220 (-I Sin[x1])^3 Cos[x1]^12 + 220 (-I Sin[x1])^12 Cos[x1]^3 + 1485 (-I Sin[x1])^5 Cos[x1]^10 + 1485 (-I Sin[x1])^10 Cos[x1]^5 + 2376 (-I Sin[x1])^7 Cos[x1]^8 + 2376 (-I Sin[x1])^8 Cos[x1]^7 + 924 (-I Sin[x1])^9 Cos[x1]^6 + 924 (-I Sin[x1])^6 Cos[x1]^9) + Exp[7.0 I y1] (495 (-I Sin[x1])^4 Cos[x1]^11 + 495 (-I Sin[x1])^11 Cos[x1]^4 + 2376 (-I Sin[x1])^6 Cos[x1]^9 + 2376 (-I Sin[x1])^9 Cos[x1]^6 + 792 (-I Sin[x1])^5 Cos[x1]^10 + 792 (-I Sin[x1])^10 Cos[x1]^5 + 2772 (-I Sin[x1])^8 Cos[x1]^7 + 2772 (-I Sin[x1])^7 Cos[x1]^8))*(91 (-I Sin[x2])^2 Cos[x2]^13 + 91 (-I Sin[x2])^13 Cos[x2]^2 + 364 (-I Sin[x2])^4 Cos[x2]^11 + 364 (-I Sin[x2])^11 Cos[x2]^4) + Exp[-17.0 I y2]*(Exp[-105.0 I y1] (1 (-I Sin[x1])^4 Cos[x1]^11 + 1 (-I Sin[x1])^11 Cos[x1]^4) + Exp[-77.0 I y1] (4 (-I Sin[x1])^3 Cos[x1]^12 + 4 (-I Sin[x1])^12 Cos[x1]^3 + 11 (-I Sin[x1])^5 Cos[x1]^10 + 11 (-I Sin[x1])^10 Cos[x1]^5) + Exp[-53.0 I y1] (6 (-I Sin[x1])^2 Cos[x1]^13 + 6 (-I Sin[x1])^13 Cos[x1]^2 + 44 (-I Sin[x1])^4 Cos[x1]^11 + 44 (-I Sin[x1])^11 Cos[x1]^4 + 55 (-I Sin[x1])^6 Cos[x1]^9 + 55 (-I Sin[x1])^9 Cos[x1]^6) + Exp[-33.0 I y1] (4 (-I Sin[x1])^1 Cos[x1]^14 + 4 (-I Sin[x1])^14 Cos[x1]^1 + 66 (-I Sin[x1])^3 Cos[x1]^12 + 66 (-I Sin[x1])^12 Cos[x1]^3 + 220 (-I Sin[x1])^5 Cos[x1]^10 + 220 (-I Sin[x1])^10 Cos[x1]^5 + 165 (-I Sin[x1])^7 Cos[x1]^8 + 165 (-I Sin[x1])^8 Cos[x1]^7) + Exp[-17.0 I y1] (1 Cos[x1]^15 + 1 (-I Sin[x1])^15 + 44 (-I Sin[x1])^2 Cos[x1]^13 + 44 (-I Sin[x1])^13 Cos[x1]^2 + 330 (-I Sin[x1])^4 Cos[x1]^11 + 330 (-I Sin[x1])^11 Cos[x1]^4 + 660 (-I Sin[x1])^6 Cos[x1]^9 + 660 (-I Sin[x1])^9 Cos[x1]^6 + 330 (-I Sin[x1])^8 Cos[x1]^7 + 330 (-I Sin[x1])^7 Cos[x1]^8) + Exp[-5.0 I y1] (11 (-I Sin[x1])^1 Cos[x1]^14 + 11 (-I Sin[x1])^14 Cos[x1]^1 + 220 (-I Sin[x1])^3 Cos[x1]^12 + 220 (-I Sin[x1])^12 Cos[x1]^3 + 990 (-I Sin[x1])^5 Cos[x1]^10 + 990 (-I Sin[x1])^10 Cos[x1]^5 + 1320 (-I Sin[x1])^7 Cos[x1]^8 + 1320 (-I Sin[x1])^8 Cos[x1]^7 + 462 (-I Sin[x1])^9 Cos[x1]^6 + 462 (-I Sin[x1])^6 Cos[x1]^9) + Exp[3.0 I y1] (55 (-I Sin[x1])^2 Cos[x1]^13 + 55 (-I Sin[x1])^13 Cos[x1]^2 + 660 (-I Sin[x1])^4 Cos[x1]^11 + 660 (-I Sin[x1])^11 Cos[x1]^4 + 1980 (-I Sin[x1])^6 Cos[x1]^9 + 1980 (-I Sin[x1])^9 Cos[x1]^6 + 1848 (-I Sin[x1])^8 Cos[x1]^7 + 1848 (-I Sin[x1])^7 Cos[x1]^8 + 462 (-I Sin[x1])^5 Cos[x1]^10 + 462 (-I Sin[x1])^10 Cos[x1]^5) + Exp[7.0 I y1] (165 (-I Sin[x1])^3 Cos[x1]^12 + 165 (-I Sin[x1])^12 Cos[x1]^3 + 1320 (-I Sin[x1])^5 Cos[x1]^10 + 1320 (-I Sin[x1])^10 Cos[x1]^5 + 330 (-I Sin[x1])^4 Cos[x1]^11 + 330 (-I Sin[x1])^11 Cos[x1]^4 + 2772 (-I Sin[x1])^7 Cos[x1]^8 + 2772 (-I Sin[x1])^8 Cos[x1]^7 + 1848 (-I Sin[x1])^6 Cos[x1]^9 + 1848 (-I Sin[x1])^9 Cos[x1]^6))*(364 (-I Sin[x2])^3 Cos[x2]^12 + 364 (-I Sin[x2])^12 Cos[x2]^3 + 1001 (-I Sin[x2])^5 Cos[x2]^10 + 1001 (-I Sin[x2])^10 Cos[x2]^5) + Exp[-5.0 I y2]*(Exp[-105.0 I y1] (1 (-I Sin[x1])^5 Cos[x1]^10 + 1 (-I Sin[x1])^10 Cos[x1]^5) + Exp[-77.0 I y1] (5 (-I Sin[x1])^4 Cos[x1]^11 + 5 (-I Sin[x1])^11 Cos[x1]^4 + 10 (-I Sin[x1])^6 Cos[x1]^9 + 10 (-I Sin[x1])^9 Cos[x1]^6) + Exp[-53.0 I y1] (10 (-I Sin[x1])^3 Cos[x1]^12 + 10 (-I Sin[x1])^12 Cos[x1]^3 + 50 (-I Sin[x1])^5 Cos[x1]^10 + 50 (-I Sin[x1])^10 Cos[x1]^5 + 45 (-I Sin[x1])^7 Cos[x1]^8 + 45 (-I Sin[x1])^8 Cos[x1]^7) + Exp[-33.0 I y1] (10 (-I Sin[x1])^2 Cos[x1]^13 + 10 (-I Sin[x1])^13 Cos[x1]^2 + 100 (-I Sin[x1])^4 Cos[x1]^11 + 100 (-I Sin[x1])^11 Cos[x1]^4 + 225 (-I Sin[x1])^6 Cos[x1]^9 + 225 (-I Sin[x1])^9 Cos[x1]^6 + 120 (-I Sin[x1])^8 Cos[x1]^7 + 120 (-I Sin[x1])^7 Cos[x1]^8) + Exp[-17.0 I y1] (5 (-I Sin[x1])^1 Cos[x1]^14 + 5 (-I Sin[x1])^14 Cos[x1]^1 + 100 (-I Sin[x1])^3 Cos[x1]^12 + 100 (-I Sin[x1])^12 Cos[x1]^3 + 450 (-I Sin[x1])^5 Cos[x1]^10 + 450 (-I Sin[x1])^10 Cos[x1]^5 + 600 (-I Sin[x1])^7 Cos[x1]^8 + 600 (-I Sin[x1])^8 Cos[x1]^7 + 210 (-I Sin[x1])^9 Cos[x1]^6 + 210 (-I Sin[x1])^6 Cos[x1]^9) + Exp[-5.0 I y1] (1 Cos[x1]^15 + 1 (-I Sin[x1])^15 + 50 (-I Sin[x1])^2 Cos[x1]^13 + 50 (-I Sin[x1])^13 Cos[x1]^2 + 450 (-I Sin[x1])^4 Cos[x1]^11 + 450 (-I Sin[x1])^11 Cos[x1]^4 + 1200 (-I Sin[x1])^6 Cos[x1]^9 + 1200 (-I Sin[x1])^9 Cos[x1]^6 + 1050 (-I Sin[x1])^8 Cos[x1]^7 + 1050 (-I Sin[x1])^7 Cos[x1]^8 + 252 (-I Sin[x1])^10 Cos[x1]^5 + 252 (-I Sin[x1])^5 Cos[x1]^10) + Exp[3.0 I y1] (10 (-I Sin[x1])^1 Cos[x1]^14 + 10 (-I Sin[x1])^14 Cos[x1]^1 + 225 (-I Sin[x1])^3 Cos[x1]^12 + 225 (-I Sin[x1])^12 Cos[x1]^3 + 1200 (-I Sin[x1])^5 Cos[x1]^10 + 1200 (-I Sin[x1])^10 Cos[x1]^5 + 2100 (-I Sin[x1])^7 Cos[x1]^8 + 2100 (-I Sin[x1])^8 Cos[x1]^7 + 210 (-I Sin[x1])^4 Cos[x1]^11 + 210 (-I Sin[x1])^11 Cos[x1]^4 + 1260 (-I Sin[x1])^9 Cos[x1]^6 + 1260 (-I Sin[x1])^6 Cos[x1]^9) + Exp[7.0 I y1] (45 (-I Sin[x1])^2 Cos[x1]^13 + 45 (-I Sin[x1])^13 Cos[x1]^2 + 600 (-I Sin[x1])^4 Cos[x1]^11 + 600 (-I Sin[x1])^11 Cos[x1]^4 + 120 (-I Sin[x1])^3 Cos[x1]^12 + 120 (-I Sin[x1])^12 Cos[x1]^3 + 2100 (-I Sin[x1])^6 Cos[x1]^9 + 2100 (-I Sin[x1])^9 Cos[x1]^6 + 1050 (-I Sin[x1])^5 Cos[x1]^10 + 1050 (-I Sin[x1])^10 Cos[x1]^5 + 2520 (-I Sin[x1])^8 Cos[x1]^7 + 2520 (-I Sin[x1])^7 Cos[x1]^8))*(1001 (-I Sin[x2])^4 Cos[x2]^11 + 1001 (-I Sin[x2])^11 Cos[x2]^4 + 2002 (-I Sin[x2])^6 Cos[x2]^9 + 2002 (-I Sin[x2])^9 Cos[x2]^6) + Exp[3.0 I y2]*(Exp[-105.0 I y1] (1 (-I Sin[x1])^6 Cos[x1]^9 + 1 (-I Sin[x1])^9 Cos[x1]^6) + Exp[-77.0 I y1] (6 (-I Sin[x1])^5 Cos[x1]^10 + 6 (-I Sin[x1])^10 Cos[x1]^5 + 9 (-I Sin[x1])^7 Cos[x1]^8 + 9 (-I Sin[x1])^8 Cos[x1]^7) + Exp[-53.0 I y1] (15 (-I Sin[x1])^4 Cos[x1]^11 + 15 (-I Sin[x1])^11 Cos[x1]^4 + 54 (-I Sin[x1])^6 Cos[x1]^9 + 54 (-I Sin[x1])^9 Cos[x1]^6 + 36 (-I Sin[x1])^8 Cos[x1]^7 + 36 (-I Sin[x1])^7 Cos[x1]^8) + Exp[-33.0 I y1] (20 (-I Sin[x1])^3 Cos[x1]^12 + 20 (-I Sin[x1])^12 Cos[x1]^3 + 135 (-I Sin[x1])^5 Cos[x1]^10 + 135 (-I Sin[x1])^10 Cos[x1]^5 + 216 (-I Sin[x1])^7 Cos[x1]^8 + 216 (-I Sin[x1])^8 Cos[x1]^7 + 84 (-I Sin[x1])^9 Cos[x1]^6 + 84 (-I Sin[x1])^6 Cos[x1]^9) + Exp[-17.0 I y1] (15 (-I Sin[x1])^2 Cos[x1]^13 + 15 (-I Sin[x1])^13 Cos[x1]^2 + 180 (-I Sin[x1])^4 Cos[x1]^11 + 180 (-I Sin[x1])^11 Cos[x1]^4 + 540 (-I Sin[x1])^6 Cos[x1]^9 + 540 (-I Sin[x1])^9 Cos[x1]^6 + 504 (-I Sin[x1])^8 Cos[x1]^7 + 504 (-I Sin[x1])^7 Cos[x1]^8 + 126 (-I Sin[x1])^10 Cos[x1]^5 + 126 (-I Sin[x1])^5 Cos[x1]^10) + Exp[-5.0 I y1] (6 (-I Sin[x1])^1 Cos[x1]^14 + 6 (-I Sin[x1])^14 Cos[x1]^1 + 135 (-I Sin[x1])^3 Cos[x1]^12 + 135 (-I Sin[x1])^12 Cos[x1]^3 + 720 (-I Sin[x1])^5 Cos[x1]^10 + 720 (-I Sin[x1])^10 Cos[x1]^5 + 1260 (-I Sin[x1])^7 Cos[x1]^8 + 1260 (-I Sin[x1])^8 Cos[x1]^7 + 756 (-I Sin[x1])^9 Cos[x1]^6 + 756 (-I Sin[x1])^6 Cos[x1]^9 + 126 (-I Sin[x1])^4 Cos[x1]^11 + 126 (-I Sin[x1])^11 Cos[x1]^4) + Exp[3.0 I y1] (1 Cos[x1]^15 + 1 (-I Sin[x1])^15 + 54 (-I Sin[x1])^2 Cos[x1]^13 + 54 (-I Sin[x1])^13 Cos[x1]^2 + 540 (-I Sin[x1])^4 Cos[x1]^11 + 540 (-I Sin[x1])^11 Cos[x1]^4 + 1680 (-I Sin[x1])^6 Cos[x1]^9 + 1680 (-I Sin[x1])^9 Cos[x1]^6 + 84 (-I Sin[x1])^3 Cos[x1]^12 + 84 (-I Sin[x1])^12 Cos[x1]^3 + 1890 (-I Sin[x1])^8 Cos[x1]^7 + 1890 (-I Sin[x1])^7 Cos[x1]^8 + 756 (-I Sin[x1])^5 Cos[x1]^10 + 756 (-I Sin[x1])^10 Cos[x1]^5) + Exp[7.0 I y1] (9 (-I Sin[x1])^1 Cos[x1]^14 + 9 (-I Sin[x1])^14 Cos[x1]^1 + 216 (-I Sin[x1])^3 Cos[x1]^12 + 216 (-I Sin[x1])^12 Cos[x1]^3 + 36 (-I Sin[x1])^2 Cos[x1]^13 + 36 (-I Sin[x1])^13 Cos[x1]^2 + 1260 (-I Sin[x1])^5 Cos[x1]^10 + 1260 (-I Sin[x1])^10 Cos[x1]^5 + 504 (-I Sin[x1])^4 Cos[x1]^11 + 504 (-I Sin[x1])^11 Cos[x1]^4 + 2520 (-I Sin[x1])^7 Cos[x1]^8 + 2520 (-I Sin[x1])^8 Cos[x1]^7 + 1890 (-I Sin[x1])^6 Cos[x1]^9 + 1890 (-I Sin[x1])^9 Cos[x1]^6))*(2002 (-I Sin[x2])^5 Cos[x2]^10 + 2002 (-I Sin[x2])^10 Cos[x2]^5 + 3003 (-I Sin[x2])^7 Cos[x2]^8 + 3003 (-I Sin[x2])^8 Cos[x2]^7) + Exp[7.0 I y2]*(Exp[-105.0 I y1] (1 (-I Sin[x1])^7 Cos[x1]^8 + 1 (-I Sin[x1])^8 Cos[x1]^7) + Exp[-77.0 I y1] (7 (-I Sin[x1])^6 Cos[x1]^9 + 7 (-I Sin[x1])^9 Cos[x1]^6 + 8 (-I Sin[x1])^8 Cos[x1]^7 + 8 (-I Sin[x1])^7 Cos[x1]^8) + Exp[-53.0 I y1] (21 (-I Sin[x1])^5 Cos[x1]^10 + 21 (-I Sin[x1])^10 Cos[x1]^5 + 56 (-I Sin[x1])^7 Cos[x1]^8 + 56 (-I Sin[x1])^8 Cos[x1]^7 + 28 (-I Sin[x1])^9 Cos[x1]^6 + 28 (-I Sin[x1])^6 Cos[x1]^9) + Exp[-33.0 I y1] (35 (-I Sin[x1])^4 Cos[x1]^11 + 35 (-I Sin[x1])^11 Cos[x1]^4 + 168 (-I Sin[x1])^6 Cos[x1]^9 + 168 (-I Sin[x1])^9 Cos[x1]^6 + 196 (-I Sin[x1])^8 Cos[x1]^7 + 196 (-I Sin[x1])^7 Cos[x1]^8 + 56 (-I Sin[x1])^10 Cos[x1]^5 + 56 (-I Sin[x1])^5 Cos[x1]^10) + Exp[-17.0 I y1] (35 (-I Sin[x1])^3 Cos[x1]^12 + 35 (-I Sin[x1])^12 Cos[x1]^3 + 280 (-I Sin[x1])^5 Cos[x1]^10 + 280 (-I Sin[x1])^10 Cos[x1]^5 + 588 (-I Sin[x1])^7 Cos[x1]^8 + 588 (-I Sin[x1])^8 Cos[x1]^7 + 392 (-I Sin[x1])^9 Cos[x1]^6 + 392 (-I Sin[x1])^6 Cos[x1]^9 + 70 (-I Sin[x1])^11 Cos[x1]^4 + 70 (-I Sin[x1])^4 Cos[x1]^11) + Exp[-5.0 I y1] (21 (-I Sin[x1])^2 Cos[x1]^13 + 21 (-I Sin[x1])^13 Cos[x1]^2 + 280 (-I Sin[x1])^4 Cos[x1]^11 + 280 (-I Sin[x1])^11 Cos[x1]^4 + 980 (-I Sin[x1])^6 Cos[x1]^9 + 980 (-I Sin[x1])^9 Cos[x1]^6 + 1176 (-I Sin[x1])^8 Cos[x1]^7 + 1176 (-I Sin[x1])^7 Cos[x1]^8 + 56 (-I Sin[x1])^3 Cos[x1]^12 + 56 (-I Sin[x1])^12 Cos[x1]^3 + 490 (-I Sin[x1])^10 Cos[x1]^5 + 490 (-I Sin[x1])^5 Cos[x1]^10) + Exp[3.0 I y1] (7 (-I Sin[x1])^1 Cos[x1]^14 + 7 (-I Sin[x1])^14 Cos[x1]^1 + 168 (-I Sin[x1])^3 Cos[x1]^12 + 168 (-I Sin[x1])^12 Cos[x1]^3 + 980 (-I Sin[x1])^5 Cos[x1]^10 + 980 (-I Sin[x1])^10 Cos[x1]^5 + 28 (-I Sin[x1])^2 Cos[x1]^13 + 28 (-I Sin[x1])^13 Cos[x1]^2 + 1960 (-I Sin[x1])^7 Cos[x1]^8 + 1960 (-I Sin[x1])^8 Cos[x1]^7 + 392 (-I Sin[x1])^4 Cos[x1]^11 + 392 (-I Sin[x1])^11 Cos[x1]^4 + 1470 (-I Sin[x1])^9 Cos[x1]^6 + 1470 (-I Sin[x1])^6 Cos[x1]^9) + Exp[7.0 I y1] (1 Cos[x1]^15 + 1 (-I Sin[x1])^15 + 56 (-I Sin[x1])^2 Cos[x1]^13 + 56 (-I Sin[x1])^13 Cos[x1]^2 + 8 (-I Sin[x1])^1 Cos[x1]^14 + 8 (-I Sin[x1])^14 Cos[x1]^1 + 588 (-I Sin[x1])^4 Cos[x1]^11 + 588 (-I Sin[x1])^11 Cos[x1]^4 + 196 (-I Sin[x1])^3 Cos[x1]^12 + 196 (-I Sin[x1])^12 Cos[x1]^3 + 1960 (-I Sin[x1])^6 Cos[x1]^9 + 1960 (-I Sin[x1])^9 Cos[x1]^6 + 1176 (-I Sin[x1])^5 Cos[x1]^10 + 1176 (-I Sin[x1])^10 Cos[x1]^5 + 2450 (-I Sin[x1])^8 Cos[x1]^7 + 2450 (-I Sin[x1])^7 Cos[x1]^8))*(3003 (-I Sin[x2])^6 Cos[x2]^9 + 3003 (-I Sin[x2])^9 Cos[x2]^6 + 3432 (-I Sin[x2])^8 Cos[x2]^7 + 3432 (-I Sin[x2])^7 Cos[x2]^8))\/Sqrt[2^nqubits];\nprobability[x1_,y1_,x2_,y2_] := Abs[amplitude[x1,y1,x2,y2]]^2;\n\nresult = Maximize[{nstates*probability[a, b, c, d], 0 <= a < Pi\/2, 0 <= b < Pi, 0 <= c < Pi\/2, 0 <= d < Pi}, {a, b, c, d}, Method -> {\"SimulatedAnnealing\", \"PerturbationScale\" -> 15}];\nPrint[name, \": \", result]\n\nn = Pi;\n","avg_line_length":1262.25,"max_line_length":14817,"alphanum_fraction":0.5216214432}