Predicting the dark matter velocity distribution in galactic structures:
  tests against hydrodynamic cosmological simulations
  Reducing theoretical uncertainties in Galactic dark matter (DM) searches is
an important challenge as several experiments are now delving into the
parameter space relevant to popular (particle or not) candidates. Since many DM
signal predictions rely on the knowledge of the DM velocity
distribution---direct searches, capture by stars, p-wave-suppressed or
Sommerfeld-enhanced annihilation rate, microlensing of primordial black holes,
etc.---it is necessary to assess the accuracy of our current theoretical
handle. Beyond Maxwellian approximations or ad-hoc extrapolations of fits on
cosmological simulations, approaches have been proposed to self-consistently
derive the DM phase-space distribution only from the detailed mass content of
the Galaxy and some symmetry assumptions (e.g. the Eddington inversion and its
anisotropic extensions). Although theoretically sound, these methods are still
based on simplifying assumptions and their relevance to real galaxies can be
questioned. In this paper, we use zoomed-in cosmological simulations to
quantify the associated uncertainties. Assuming isotropy, we predict the speed
distribution and its moments from the DM and baryonic content measured in
simulations, and compare them with the true ones. Taking as input galactic mass
models fitted on full simulation data, we reach a predictivity down to ~ 10%
for some velocity-related observables, significantly better than some
Maxwellian models. This moderate theoretical error is particularly encouraging
at a time when stellar surveys like the Gaia mission should allow us to improve
constraints on Galactic mass models.
