Set the Night on FIRE: Building an Empirical Local Dark Matter Velocity Distribution
Xiuyuan Zhang, Andreas Thoyas, Lina Necib, Andrew Wetzel, Arpit Arora

TL;DR
This paper develops a method to reconstruct the local dark matter velocity distribution by using stellar data and simulation insights, capturing merger-induced features beyond the Standard Halo Model.
Contribution
It introduces a framework combining stellar and dark matter data from simulations to accurately model the local dark matter velocity distribution, including merger effects.
Findings
Strong correlation between stellar and dark matter velocity distributions from mergers.
Reconstructed velocity distribution captures features absent in the Standard Halo Model.
Uncertainty dominated by stellar mass-halo mass relation, limiting further improvements.
Abstract
The majority of terrestrial direct detection experiments for Dark Matter (DM) rely on the Standard Halo Model (SHM), which assumes the local DM velocity distribution follows a Maxwell-Boltzmann distribution. However, galaxy mergers can deposit DM that remains kinematically clustered today, inducing deviations from the smooth SHM prediction. Previous studies have suggested that the local stellar velocity distribution may serve as a tracer for DM populations originating from the same progenitor systems. In this work, we systematically investigate how merger mass and accretion time affect the correlation between local stellar and DM velocity distributions in Milky Way-like galaxies from the FIRE-2 simulations. We find a strong correlation between traceable DM components and their stellar counterparts, with the tightest correspondence arising from lower-mass mergers accreted at earlier…
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