  As astronomical photometric surveys continue to tile the sky repeatedly, the
potential to pushdetection thresholds to fainter limits increases; however,
traditional digital-tracking methods cannotachieve this efficiently beyond time
scales where motion is approximately linear. In this paper weprototype an
optimal detection scheme that samples under a user defined prior on a
parameterizationof the motion space, maps these sampled trajectories to the
data space, and computes an optimalsignal-matched filter for computing the
signal to noise ratio of trial trajectories. We demonstrate thecapability of
this method on a small test data set from the Dark Energy Camera. We recover
themajority of asteroids expected to appear and also discover hundreds of new
asteroids with only a fewhours of observations. We conclude by exploring the
potential for extending this scheme to larger datasets that cover larger areas
of the sky over longer time baselines.

Earth and Planetary Astrophysics;Instrumentation and Methods for Astrophysics