Name:
Shen_2022_ApJ_925_1.pdf
Size:
2.885Mb
Format:
PDF
Description:
Final Published Version
Author
Shen, J.Eadie, G.M.
Murray, N.
Zaritsky, D.
Speagle, J.S.
Ting, Y.-S.
Conroy, C.
Cargile, P.A.
Johnson, B.D.
Naidu, R.P.
Han, J.J.
Affiliation
Steward Observatory, University of ArizonaIssue Date
2022
Metadata
Show full item recordPublisher
American Astronomical SocietyCitation
Shen, J., Eadie, G. M., Murray, N., Zaritsky, D., Speagle, J. S., Ting, Y.-S., Conroy, C., Cargile, P. A., Johnson, B. D., Naidu, R. P., & Han, J. J. (2022). The Mass of the Milky Way from the H3 Survey. Astrophysical Journal.Journal
Astrophysical JournalRights
Copyright © 2022. The Author(s). Published by the American Astronomical Society. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.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 (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%. © 2022. The Author(s). Published by the American Astronomical Society..Note
Open access articleISSN
0004-637XVersion
Final published versionae974a485f413a2113503eed53cd6c53
10.3847/1538-4357/ac3a7a
Scopus Count
Collections
Except where otherwise noted, this item's license is described as Copyright © 2022. The Author(s). Published by the American Astronomical Society. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence.