The Mass of the Milky Way from the H3 Survey

The mass of the Milky Way is a critical quantity that, despite decades of research, remains uncertain within a factor of two. Until recently, most studies have used dynamical tracers in the inner regions of the halo, relying on extrapolations to estimate the mass of the Milky Way. In this paper, we extend the hierarchical Bayesian model applied in Eadie & Juri to study the mass distribution of the Milky Way halo; the new model allows for the use of all available 6D phase-space measurements. We use kinematic data of halo stars out to 142 kpc, obtained from the H3 survey and Gaia EDR3, to infer the mass of the Galaxy. Inference is carried out with the No-U-Turn sampler, a fast and scalable extension of Hamiltonian Monte Carlo. We report a median mass enclosed within 100 kpc of M(< 100 kpc) = 0.69(-0.04)(+0.05) x 10(12) M circle dot (68% Bayesian credible interval), or a virial mass of M-200 = M(<216.2(-7.5)(+7.5) kpc) = 1.08(-0.11)(+0.12) x 10(12) M-circle dot, in good agreement with other recent estimates. We analyze our results using posterior predictive checks and find limitations in the model's ability to describe the data. In particular, we find sensitivity with respect to substructure in the halo, which limits the precision of our mass estimates to similar to 15%.

Automated summary

This paper uses a hierarchical Bayesian model to study the mass distribution of the Milky Way halo and infers the mass of the Galaxy using kinematic data. The results are in good agreement with other studies, but limitations in the model's ability to describe the data are found, leading to an accuracy of about 15% in mass estimates.