Exclusion, Discovery and Identification of Dark Matter with Directional Detection

Laboratoire de Physique Subatomique et de Cosmologie, Université Joseph Fourier Grenoble 1, CNRS/IN2P3, Institut Polytechnique de Grenoble, Grenoble, France

Abstract

Directional detection is a promising search strategy to discover galactic Dark Matter. We present a Bayesian analysis framework dedicated to data from upcoming directional detectors. The interest of directional detection as a powerful tool to set exclusion limits, to authentify a Dark Matter detection or to constrain the Dark Matter properties, both from particle physics and galactic halo physics, will be demonstrated.