The Velocity Distribution Function of Galaxy Clusters as a Cosmological Probe
M. Ntampaka, H. Trac, J. Cisewski, and L.C. Price

TL;DR
This paper introduces the velocity distribution function (VDF) as a new, more precise method for constraining cosmological parameters using galaxy cluster velocities, outperforming traditional mass-based methods.
Contribution
The paper proposes the VDF as a novel statistic for cosmological inference, demonstrating its advantages over the traditional halo mass function (HMF) in mock analyses.
Findings
VDF provides tighter constraints on $\sigma_8$ and $\Omega_m$ than HMF.
VDF shows minimal bias in parameter estimation.
Combining VDF with CMB data reduces parameter degeneracies.
Abstract
We present a new approach for quantifying the abundance of galaxy clusters and constraining cosmological parameters using dynamical measurements. In the standard method, galaxy line-of-sight (LOS) velocities, , or velocity dispersions are used to infer cluster masses, , in order to quantify the halo mass function (HMF), , which is strongly affected by mass measurement errors. In our new method, the probability distribution of velocities for each cluster in the sample are summed to create a new statistic called the velocity distribution function (VDF), . The VDF can be measured more directly and precisely than the HMF and it can also be robustly predicted with cosmological simulations which capture the dynamics of subhalos or galaxies. We apply these two methods to mock cluster catalogs and forecast the bias and constraints on the matter density parameter…
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