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Published July 2023 | Published + Supplemental Material
Journal Article Open

An elusive dark central mass in the globular cluster M4

Abstract

Recent studies of nearby globular clusters have discovered excess dark mass in their cores, apparently in an extended distribution, and simulations indicate that this mass is composed mostly of white dwarfs (respectively stellar-mass black holes) in clusters that are core collapsed (respectively with a flatter core). We perform mass-anisotropy modelling of the closest globular cluster, M4, with intermediate slope for the inner stellar density. We use proper motion data from Gaia Early Data Release 3 (EDR3) and from observations by the Hubble Space Telescope. We extract the mass profile employing Bayesian Jeans modelling, and check our fits with realistic mock data. Our analyses return isotropic motions in the cluster core and tangential motions (β ≈ −0.4 ± 0.1) in the outskirts. We also robustly measure a dark central mass of roughly 800±300M⊙ , but it is not possible to distinguish between a point-like source, such as an intermediate-mass black hole (IMBH), and a dark population of stellar remnants of extent ≈0.016pc≃3300au. However, when removing a high-velocity star from the cluster centre, the same mass excess is found, but more extended (⁠∼0.034pc≈7000au). We use Monte Carlo N-body models of M4 to interpret the second outcome, and find that our excess mass is not sufficiently extended to be confidently associated with a dark population of remnants. Finally, we discuss the feasibility of these two scenarios (i.e. IMBH versus remnants), and propose new observations that could help to better grasp the complex dynamics in M4's core.

Additional Information

© 2023 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model). We thank the anonymous referee for the constructive report, with comments that have helped us to improve the quality of our results and clarify some descriptions in the manuscript. We also acknowledge Roeland van der Marel and the HSTPROMO Collaboration for useful comments. EV was funded by an AMX doctoral grant from École Polytechnique. KK is supported by an NSF Astronomy and Astrophysics Postdoctoral Fellowship under award AST-2001751. LRB acknowledges support by MIUR under PRIN programme #2017Z2HSMF and by PRIN-INAF 2012 and 2019. Support for this work was provided by a grant for HST program 13297 provided by the Space Telescope Science Institute, which is operated by AURA, Inc., under NASA contract NAS 5–26555. This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. We greatly benefited from the public software python (Van Rossum & Drake 2009) packages BALRoGO (Vitral 2021), scipy (Jones, Oliphant & Peterson 2001), numpy (van der Walt, Colbert & Varoquaux 2011), and matplotlib (Hunter 2007). We also used the spyder Integrated Development Environment (Raybaut 2009).

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Additional details

Created:
August 22, 2023
Modified:
October 20, 2023