TY - JOUR
T1 - The Mass of the Milky Way from the H3 Survey
AU - Shen, Jeff
AU - Eadie, Gwendolyn M.
AU - Murray, Norman
AU - Zaritsky, Dennis
AU - Speagle, Joshua S.
AU - Ting, Yuan Sen
AU - Conroy, Charlie
AU - Cargile, Phillip A.
AU - Johnson, Benjamin D.
AU - Naidu, Rohan P.
AU - Han, Jiwon Jesse
N1 - Publisher Copyright:
© 2022. The Author(s). Published by the American Astronomical Society..
PY - 2022/1/20
Y1 - 2022/1/20
N2 - 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 (68% Bayesian credible interval), or a virial mass of , 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 ∼15%.
AB - 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 (68% Bayesian credible interval), or a virial mass of , 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 ∼15%.
UR - http://www.scopus.com/inward/record.url?scp=85124155929&partnerID=8YFLogxK
U2 - 10.3847/1538-4357/ac3a7a
DO - 10.3847/1538-4357/ac3a7a
M3 - Article
SN - 0004-637X
VL - 925
JO - Astrophysical Journal
JF - Astrophysical Journal
IS - 1
M1 - 1
ER -