Velocity and mass bias in the distribution of dark matter halos
Elise Jennings (KICP, EFI, University of Chicago), Carlton M. Baugh, (Durham University), Dylan Hatt (University of Chicago)

TL;DR
This paper investigates scale-dependent biases in dark matter halo distributions and velocities, revealing significant systematic effects that impact cosmological parameter estimation from galaxy clustering and redshift space distortions.
Contribution
It provides the first detailed analysis of velocity divergence bias in halos, highlighting its significance for cosmological measurements.
Findings
Mass bias is scale independent only at large scales ($k<0.1 h/{ m Mpc}$) at $z=0$ and $k<0.2 h/{ m Mpc}$ at $z=0.7.
The Tinker et al. 2005 model accurately predicts halo bias to within 5% at $z=0$.
Velocity divergence bias increases with decreasing halo number density, reaching about 20% at $k=0.1h/{ m Mpc}$ for typical halo samples.
Abstract
The non-linear, scale-dependent bias in the mass distribution of galaxies and the underlying dark matter is a key systematic affecting the extraction of cosmological parameters from galaxy clustering. Using 95 million halos from the Millennium-XXL N-body simulation, we find that the mass bias is scale independent only for today () and for at . We test analytic halo bias models against our simulation measurements and find that the model of Tinker et al. 2005 is accurate to better then 5% at . However, the simulation results are better fit by an ellipsoidal collapse model at . We highlight, for the first time, another potentially serious systematic due to a sampling bias in the halo velocity divergence power spectra which will affect the comparison between observations and any redshift space distortion model which…
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