Datasets:
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gate
stringclasses 13
values | run
int64 1
1k
| num_qubits
int64 1
3
| depth
int64 2
2
| size
int64 2
4
| exec_time_sec
float64 0
0.05
| error_rate
float64 0
4.15
| fidelity
float64 -3.15
1
| energy_consumption_mJ
float64 0
0
| quantum_volume
int64 2
6
| depolarization_rate
float64 0.05
0.05
| noise_rate
float64 0.05
0.05
| noise_model_used
stringclasses 2
values |
---|---|---|---|---|---|---|---|---|---|---|---|---|
H | 1 | 1 | 2 | 2 | 0.002356 | 0.50293 | 0.49707 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 2 | 1 | 2 | 2 | 0.002212 | 0.500977 | 0.499023 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 3 | 1 | 2 | 2 | 0.002219 | 0.495117 | 0.504883 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 4 | 1 | 2 | 2 | 0.002203 | 0.470703 | 0.529297 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 5 | 1 | 2 | 2 | 0.002327 | 0.512695 | 0.487305 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 6 | 1 | 2 | 2 | 0.002281 | 0.496094 | 0.503906 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 7 | 1 | 2 | 2 | 0.002154 | 0.5 | 0.5 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 8 | 1 | 2 | 2 | 0.002289 | 0.493164 | 0.506836 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 9 | 1 | 2 | 2 | 0.002248 | 0.506836 | 0.493164 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 10 | 1 | 2 | 2 | 0.002227 | 0.507813 | 0.492188 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 11 | 1 | 2 | 2 | 0.002251 | 0.487305 | 0.512695 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 12 | 1 | 2 | 2 | 0.002167 | 0.481445 | 0.518555 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 13 | 1 | 2 | 2 | 0.002229 | 0.506836 | 0.493164 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 14 | 1 | 2 | 2 | 0.002237 | 0.496094 | 0.503906 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 15 | 1 | 2 | 2 | 0.002196 | 0.525391 | 0.474609 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 16 | 1 | 2 | 2 | 0.002259 | 0.508789 | 0.491211 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 17 | 1 | 2 | 2 | 0.002233 | 0.533203 | 0.466797 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 18 | 1 | 2 | 2 | 0.002308 | 0.494141 | 0.505859 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 19 | 1 | 2 | 2 | 0.002225 | 0.499023 | 0.500977 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 20 | 1 | 2 | 2 | 0.002319 | 0.469727 | 0.530273 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 21 | 1 | 2 | 2 | 0.00229 | 0.504883 | 0.495117 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 22 | 1 | 2 | 2 | 0.002353 | 0.493164 | 0.506836 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 23 | 1 | 2 | 2 | 0.002232 | 0.490234 | 0.509766 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 24 | 1 | 2 | 2 | 0.002233 | 0.505859 | 0.494141 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 25 | 1 | 2 | 2 | 0.002348 | 0.510742 | 0.489258 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 26 | 1 | 2 | 2 | 0.002311 | 0.489258 | 0.510742 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 27 | 1 | 2 | 2 | 0.002286 | 0.499023 | 0.500977 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 28 | 1 | 2 | 2 | 0.002278 | 0.505859 | 0.494141 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 29 | 1 | 2 | 2 | 0.002246 | 0.515625 | 0.484375 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 30 | 1 | 2 | 2 | 0.002213 | 0.486328 | 0.513672 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 31 | 1 | 2 | 2 | 0.002252 | 0.52832 | 0.47168 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 32 | 1 | 2 | 2 | 0.002227 | 0.503906 | 0.496094 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 33 | 1 | 2 | 2 | 0.002283 | 0.5 | 0.5 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 34 | 1 | 2 | 2 | 0.00223 | 0.475586 | 0.524414 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 35 | 1 | 2 | 2 | 0.002239 | 0.479492 | 0.520508 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 36 | 1 | 2 | 2 | 0.002267 | 0.515625 | 0.484375 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 37 | 1 | 2 | 2 | 0.002264 | 0.511719 | 0.488281 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 38 | 1 | 2 | 2 | 0.002367 | 0.490234 | 0.509766 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 39 | 1 | 2 | 2 | 0.002311 | 0.533203 | 0.466797 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 40 | 1 | 2 | 2 | 0.002287 | 0.494141 | 0.505859 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 41 | 1 | 2 | 2 | 0.00236 | 0.493164 | 0.506836 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 42 | 1 | 2 | 2 | 0.002309 | 0.500977 | 0.499023 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 43 | 1 | 2 | 2 | 0.002223 | 0.505859 | 0.494141 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 44 | 1 | 2 | 2 | 0.00221 | 0.513672 | 0.486328 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 45 | 1 | 2 | 2 | 0.002246 | 0.5 | 0.5 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 46 | 1 | 2 | 2 | 0.004087 | 0.500977 | 0.499023 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 47 | 1 | 2 | 2 | 0.002307 | 0.513672 | 0.486328 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 48 | 1 | 2 | 2 | 0.002331 | 0.525391 | 0.474609 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 49 | 1 | 2 | 2 | 0.002234 | 0.483398 | 0.516602 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 50 | 1 | 2 | 2 | 0.002414 | 0.527344 | 0.472656 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 51 | 1 | 2 | 2 | 0.002313 | 0.5 | 0.5 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 52 | 1 | 2 | 2 | 0.002352 | 0.499023 | 0.500977 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 53 | 1 | 2 | 2 | 0.002237 | 0.5 | 0.5 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 54 | 1 | 2 | 2 | 0.002295 | 0.5 | 0.5 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 55 | 1 | 2 | 2 | 0.002259 | 0.498047 | 0.501953 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 56 | 1 | 2 | 2 | 0.002232 | 0.499023 | 0.500977 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 57 | 1 | 2 | 2 | 0.002756 | 0.482422 | 0.517578 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 58 | 1 | 2 | 2 | 0.002312 | 0.491211 | 0.508789 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 59 | 1 | 2 | 2 | 0.002214 | 0.506836 | 0.493164 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 60 | 1 | 2 | 2 | 0.002172 | 0.492188 | 0.507813 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 61 | 1 | 2 | 2 | 0.002381 | 0.522461 | 0.477539 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 62 | 1 | 2 | 2 | 0.00227 | 0.482422 | 0.517578 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 63 | 1 | 2 | 2 | 0.002373 | 0.525391 | 0.474609 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 64 | 1 | 2 | 2 | 0.002371 | 0.482422 | 0.517578 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 65 | 1 | 2 | 2 | 0.002322 | 0.486328 | 0.513672 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 66 | 1 | 2 | 2 | 0.002239 | 0.517578 | 0.482422 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 67 | 1 | 2 | 2 | 0.002188 | 0.483398 | 0.516602 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 68 | 1 | 2 | 2 | 0.00235 | 0.491211 | 0.508789 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 69 | 1 | 2 | 2 | 0.002311 | 0.515625 | 0.484375 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 70 | 1 | 2 | 2 | 0.002306 | 0.474609 | 0.525391 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 71 | 1 | 2 | 2 | 0.002365 | 0.478516 | 0.521484 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 72 | 1 | 2 | 2 | 0.002317 | 0.511719 | 0.488281 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 73 | 1 | 2 | 2 | 0.002385 | 0.530273 | 0.469727 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 74 | 1 | 2 | 2 | 0.002366 | 0.493164 | 0.506836 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 75 | 1 | 2 | 2 | 0.002243 | 0.479492 | 0.520508 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 76 | 1 | 2 | 2 | 0.015402 | 0.504883 | 0.495117 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 77 | 1 | 2 | 2 | 0.004719 | 0.514648 | 0.485352 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 78 | 1 | 2 | 2 | 0.011196 | 0.491211 | 0.508789 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 79 | 1 | 2 | 2 | 0.002905 | 0.495117 | 0.504883 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 80 | 1 | 2 | 2 | 0.014531 | 0.493164 | 0.506836 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 81 | 1 | 2 | 2 | 0.014737 | 0.501953 | 0.498047 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 82 | 1 | 2 | 2 | 0.015199 | 0.5 | 0.5 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 83 | 1 | 2 | 2 | 0.015056 | 0.481445 | 0.518555 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 84 | 1 | 2 | 2 | 0.014659 | 0.489258 | 0.510742 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 85 | 1 | 2 | 2 | 0.015097 | 0.5 | 0.5 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 86 | 1 | 2 | 2 | 0.015038 | 0.511719 | 0.488281 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 87 | 1 | 2 | 2 | 0.014831 | 0.475586 | 0.524414 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 88 | 1 | 2 | 2 | 0.01496 | 0.483398 | 0.516602 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 89 | 1 | 2 | 2 | 0.014433 | 0.479492 | 0.520508 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 90 | 1 | 2 | 2 | 0.002218 | 0.500977 | 0.499023 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 91 | 1 | 2 | 2 | 0.002268 | 0.495117 | 0.504883 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 92 | 1 | 2 | 2 | 0.002298 | 0.50293 | 0.49707 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 93 | 1 | 2 | 2 | 0.00222 | 0.508789 | 0.491211 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 94 | 1 | 2 | 2 | 0.002183 | 0.458984 | 0.541016 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 95 | 1 | 2 | 2 | 0.002339 | 0.49707 | 0.50293 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 96 | 1 | 2 | 2 | 0.002282 | 0.496094 | 0.503906 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 97 | 1 | 2 | 2 | 0.002306 | 0.519531 | 0.480469 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 98 | 1 | 2 | 2 | 0.00232 | 0.473633 | 0.526367 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 99 | 1 | 2 | 2 | 0.002263 | 0.50293 | 0.49707 | 0.001 | 2 | 0.05 | 0.05 | Yes |
H | 100 | 1 | 2 | 2 | 0.002438 | 0.53418 | 0.46582 | 0.001 | 2 | 0.05 | 0.05 | Yes |
End of preview. Expand
in Data Studio
π§ͺ Quantum Gate Performance Dataset
π Title:
Comprehensive Quantum Gate Performance Analysis: A Comparative Study of Noise and No-Noise Effects
π Dataset Description:
This repository contains benchmarking results for 13 quantum gates (e.g., H, CNOT, Toffoli) tested under noisy and noise-free conditions, based on 1000 simulation runs per gate configuration. Total 26000 rows and 13 columns.
π Features include:
- Gate Type
- Execution Time
- Error Rate
- Fidelity
- Energy Consumption
- Quantum Volume
- Noise Model used
π Use Cases:
- Quantum Machine Learning (QML)
- Circuit optimization
- Noise modeling
- Educational demos
π DOI and Original Source:
Originally published on Mendeley Data:
https://doi.org/10.17632/kf5mbvft5t.1
π License:
Released under Creative Commons Attribution 4.0 (CC BY 4.0)
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