Determination of Dark Matter Halo Mass from Dynamics of Satellite Galaxies
Zhao-Zhou Li, Y.P. Jing, Yong-Zhong Qian, Zhen Yuan, Dong-Hai Zhao

TL;DR
This paper presents a method to estimate dark matter halo mass using the phase space distribution of satellite galaxies, achieving about 25-40% accuracy with current data and highlighting the influence of halo formation history.
Contribution
It introduces a new likelihood-based approach to infer halo mass from satellite dynamics, accounting for formation history dependence and scaling from simulations.
Findings
Mass can be estimated within ~40% accuracy with current satellite data.
Using 30 tracers improves accuracy to ~25%.
Formation history imposes a ~20% minimum uncertainty.
Abstract
We show that the mass of a dark matter halo can be inferred from the dynamical status of its satellite galaxies. Using 9 dark-matter simulations of halos like the Milky Way (MW), we find that the present-day substructures in each halo follow a characteristic distribution in the phase space of orbital binding energy and angular momentum, and that this distribution is similar from halo to halo but has an intrinsic dependence on the halo formation history. We construct this distribution directly from the simulations for a specific halo and extend the result to halos of similar formation history but different masses by scaling. The mass of an observed halo can then be estimated by maximizing the likelihood in comparing the measured kinematic parameters of its satellite galaxies with these distributions. We test the validity and accuracy of this method with mock samples taken from the…
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