Galactic Mass Estimates using Dwarf Galaxies as Kinematic Tracers
Anika Slizewski, Xander Dufresne, Keslen Murdock, Gwendolyn Eadie,, Robyn Sanderson, Andrew Wetzel, Mario Juric

TL;DR
This paper employs a hierarchical Bayesian approach with dwarf galaxy kinematic data to estimate the Milky Way's mass profile, incorporating prior information and analyzing the influence of the Large Magellanic Cloud.
Contribution
It introduces a new Bayesian hierarchical model for Milky Way mass estimation using dwarf galaxy data, integrating prior info from simulations and past studies.
Findings
Median mass within 200 kpc: 1.19×10^{12} M_⊙
Mass estimates align with recent studies using Gaia data
Evidence suggests some dwarf galaxies are affected by the LMC
Abstract
New mass estimates and cumulative mass profiles with Bayesian credible regions (c.r.) for the Milky Way (MW) are found using the Galactic Mass Estimator (GME) code and dwarf galaxy (DG) kinematic data from multiple sources. GME takes a hierarchical Bayesian approach to simultaneously estimate the true positions and velocities of the DGs, their velocity anisotropy, and the model parameters for the Galaxy's total gravitational potential. In this study, we incorporate meaningful prior information from past studies and simulations. The prior distributions for the physical model are informed by the results of Eadie & Juric (2019), which used globular clusters instead of DGs, as well as by the subhalo distributions of the Ananke Gaia-like surveys from Feedback In Realistic Environments-2 (Fire-2) cosmological simulations (see Sanderson et al. 2020). Using DGs beyond 45 kpc, we report median…
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