The local dark matter phase-space density and impact on WIMP direct detection
Riccardo Catena, Piero Ullio

TL;DR
This paper derives a new, more accurate local dark matter phase-space density using Bayesian methods and compares it to traditional models, revealing significant differences impacting direct detection experiments.
Contribution
It introduces a novel Bayesian approach to determine the local dark matter phase-space density, accounting for different density profiles and astrophysical uncertainties.
Findings
Dark matter velocity dispersion varies with density profile.
Derived phase-space densities differ from Maxwell-Boltzmann assumptions.
Results suggest larger detection rates when using self-consistent densities.
Abstract
We present a new determination of the local dark matter phase-space density. This result is obtained implementing, in the limit of isotropic velocity distribution and spherical symmetry, Eddington's inversion formula, which links univocally the dark matter distribution function to the density profile, and applying, within a Bayesian framework, a Markov Chain Monte Carlo algorithm to sample mass models for the Milky Way against a broad and variegated sample of dynamical constraints. We consider three possible choices for the dark matter density profile, namely the Einasto, NFW and Burkert profiles, finding that the velocity dispersion, which characterizes the width in the distribution, tends to be larger for the Burkert case, while the escape velocity depends very weakly on the profile, with the mean value we obtain being in very good agreement with estimates from stellar kinematics. The…
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