Bayesian Mass Estimates of the Milky Way II: The dark and light sides of parameter assumptions

We present mass and mass profile estimates for the Milky Way Galaxy using the Bayesian analysis developed by Eadie et al (2015b) and using globular clusters (GCs) as tracers of the Galactic potential. The dark matter and GCs are assumed to follow different spatial distributions; we assume power-law model profiles and use the model distribution functions described in Evans et al. (1997); Deason et al (2011, 2012a). We explore the relationships between assumptions about model parameters and how these assumptions affect mass profile estimates. We also explore how using subsamples of the GC population beyond certain radii affect mass estimates. After exploring the posterior distributions of different parameter assumption scenarios, we conclude that a conservative estimate of the Galaxy's mass within 125kpc is $5.22\times10^{11} M_{\odot}$, with a $50\%$ probability region of $(4.79, 5.63) \times10^{11} M_{\odot}$. Extrapolating out to the virial radius, we obtain a virial mass for the Milky Way of $6.82\times10^{11} M_{\odot}$ with $50\%$ credible region of $(6.06, 7.53) \times 10^{11} M_{\odot}$ ($r_{vir}=185^{+7}_{-7}$kpc). If we consider only the GCs beyond 10kpc, then the virial mass is $9.02~(5.69, 10.86) \times 10^{11} M_{\odot}$ ($r_{vir}=198^{+19}_{-24}$kpc). We also arrive at an estimate of the velocity anisotropy parameter $\beta$ of the GC population, which is $\beta=0.28$ with a $50\%$ credible region (0.21, 0.35). Interestingly, the mass estimates are sensitive to both the dark matter halo potential and visible matter tracer parameters, but are not very sensitive to the anisotropy parameter.