Track reconstruction with MIMAC

Abstract

Directional detection of Dark Matter is a promising search strategy. However, to perform such kind of detection, the recoiling tracks have to be accurately reconstructed: direction, sense and position in the detector volume. In order to optimize the track reconstruction and to fully exploit the data from the MIMAC detector, we developed a likelihood method dedicated to the track reconstruction. This likelihood approach requires a full simulation of track measurements with MIMAC in order to compare real tracks to simulated ones. Finally, we found that the MIMAC detector should have the required performance to perform a competitive directional detection of Dark Matter.

9 pages, 6 figures; Proceedings of the 3rd International conference on Directional Detection of Dark Matter (CYGNUS 2011), Aussois, France, 8-10 June 2011