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Published February 20, 2022 | Submitted + Published
Journal Article Open

Substructure at High Speed. I. Inferring the Escape Velocity in the Presence of Kinematic Substructure

Abstract

The local escape velocity provides valuable inputs to the mass profile of the galaxy, and requires understanding the tail of the stellar speed distribution. Following Leonard & Tremaine, various works have since modeled the tail of the stellar speed distribution as ∝(v_(esc)−v)^k, where v_(esc) is the escape velocity, and k is the slope of the distribution. In such studies, however, these two parameters were found to be largely degenerate and often a narrow prior is imposed on k in order to constrain v_(esc). Furthermore, the validity of the power-law form can breakdown in the presence of multiple kinematic substructures or other mis-modeled features in the data. In this paper, we introduce a strategy that for the first time takes into account the presence of kinematic substructure. We model the tail of the velocity distribution as a sum of multiple power laws as a way of introducing a more flexible fitting framework. Using mock data and data from FIRE simulations of Milky Way-like galaxies, we show the robustness of this method in the presence of kinematic structure that is similar to the recently discovered Gaia Sausage. In a companion paper, we present the new measurement of the escape velocity and subsequently the mass of the Milky Way using Gaia eDR3 data.

Additional Information

© 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. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Received 2021 February 23; revised 2021 December 10; accepted 2021 December 11; published 2022 February 24. We are grateful to I. Moult for early discussions and collaboration on the project, and to M. Lisanti for helpful feedback. We would also like to thank L. Anderson, A. Bonaca, G. Collin, A. Deason, P. Hopkins, A. Ji, and J. Johnson for helpful conversations. This work was performed in part at Aspen Center for Physics, which is supported by National Science Foundation grant PHY-1607611. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility operated under Contract No. DE-AC02-05CH11231. L.N. is supported by the DOE under Award No. DESC0011632, the Sherman Fairchild fellowship, the University of California Presidential fellowship, and the fellowship of theoretical astrophysics at Carnegie Observatories. T.L. is supported by an Alfred P. Sloan Research Fellowship and Department of Energy (DOE) grant DE-SC0019195. Software: Astropy (Astropy Collaboration et al. 2013, 2018), corner.py (Foreman-Mackey 2016), emcee (Foreman-Mackey et al. 2013), IPython (Pérez & Granger 2007), Galpy (Bovy 2015).

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Published - Necib_2022_ApJ_926_188.pdf

Submitted - 2102.01704.pdf

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Additional details

Created:
August 22, 2023
Modified:
October 23, 2023