Galactic Mass Estimates Using Dwarf Galaxies as Kinematic Tracers

New mass estimates and cumulative mass profiles with Bayesian credible regions 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, who 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 cosmological simulations (see Sanderson et al.). Using DGs beyond 45 kpc, we report median and 95% credible region estimates for r (200) = 212.8 (191.12, 238.44) kpc, and for the total enclosed mass M (200) = 1.19 (0.87, 1.68) x 10(12) M (circle dot) (adopting Delta( c ) = 200). Median mass estimates at specific radii are also reported (e.g., M (< 50 kpc) = 0.52 x 10(12) M (circle dot) and M (100 kpc) = 0.78 x 10(12) M (circle dot)). Estimates are comparable to other recent studies using Gaia DR2 and DGs, but notably different from the estimates of Eadie & Juric. We perform a sensitivity analysis to investigate whether individual DGs and/or a more massive Large Magellanic Cloud on the order of 10(11) M (circle dot) may be affecting our mass estimates. We find possible supporting evidence for the idea that some DGs are affected by a massive LMC and are not in equilibrium with the MW.

Automated summary

This study uses the Galactic Mass Estimator (GME) code and dwarf galaxy (DG) kinematic data from multiple sources to find new mass estimates and cumulative mass profiles for the Milky Way (MW). Bayesian credible regions are also provided for the estimates. The results show that the estimates are comparable to other recent studies, but differ significantly from previous research.