Dark Matter direct detection and Bayesian statistics
Chiara Arina
University of Amsterdam
Mercredi 20/02/2013, 14:15
Salle Claude Itzykson, Bât. 774, Orme des Merisiers
Bayesian statistical methods offer a simple and consistent framework for incorporating uncertainties into a multi-parameter inference problem. In this talk we apply these methods to a selection of current direct dark matter searches. We consider the simplest scenarios of spin-independent WIMP scattering, and infer the WIMP mass and cross-section from the experimental data with the essential systematic uncertainties folded into the analysis. In the same vein, we investigate the impact of astrophysical uncertainties on the preferred WIMP parameters. We then discuss and interpret the results to quantitatively estimate the disagreement between the controversial hints of detection claimed by DAMA, CoGeNT and CRESST with respect the most stringent upper bounds of XENON100. We conclude with the prospects for dark matter direct detection experiments in the forthcoming years to close in the incompatibility question between these data sets.
Contact : ccaprini


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