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The Mass of the Milky Way from the H3 Survey.

Authors :
Shen, Jeff
Eadie, Gwendolyn M.
Murray, Norman
Zaritsky, Dennis
Speagle, Joshua S.
Ting, Yuan-Sen
Conroy, Charlie
Cargile, Phillip A.
Johnson, Benjamin D.
Naidu, Rohan P.
Han, Jiwon Jesse
Source :
Astrophysical Journal; 1/20/2022, Vol. 925 Issue 1, p1-19, 19p
Publication Year :
2022

Abstract

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 âˆ' 0.04 + 0.05 Ă— 10 12 M ⊙ (68% Bayesian credible interval), or a virial mass of M 200 = M (< 216.2 âˆ' 7.5 + 7.5 kpc) = 1.08 âˆ' 0.11 + 0.12 Ă— 10 12 M ⊙ , 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%. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0004637X
Volume :
925
Issue :
1
Database :
Complementary Index
Journal :
Astrophysical Journal
Publication Type :
Academic Journal
Accession number :
154934631
Full Text :
https://doi.org/10.3847/1538-4357/ac3a7a