Published April 1, 2022 | Submitted + Published
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Gravitational Microlensing Rates in Milky Way Globular Clusters

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Abstract

Many recent observational and theoretical studies suggest that globular clusters (GCs) host compact object populations large enough to play dominant roles in their overall dynamical evolution. Yet direct detection, particularly of black holes and neutron stars, remains rare and limited to special cases, such as when these objects reside in close binaries with bright companions. Here we examine the potential of microlensing detections to further constrain these dark populations. Based on state-of-the-art GC models from the CMC Cluster Catalog, we estimate the microlensing event rates for black holes, neutron stars, white dwarfs (WDs), and, for comparison, also for M dwarfs in Milky Way GCs, as well as the effects of different initial conditions on these rates. Among compact objects, we find that WDs dominate the microlensing rates, simply because they largely dominate by numbers. We show that microlensing detections are in general more likely in GCs with higher initial densities, especially in clusters that undergo core collapse. We also estimate microlensing rates in the specific cases of M22 and 47 Tuc using our best-fitting models for these GCs. Because their positions on the sky lie near the rich stellar backgrounds of the Galactic bulge and the Small Magellanic Cloud, respectively, these clusters are among the Galactic GCs best suited for dedicated microlensing surveys. The upcoming 10 yr survey with the Rubin Observatory may be ideal for detecting lensing events in GCs.

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 November 23; revised 2022 February 22; accepted 2022 February 23; published 2022 April 7. This work was supported by NSF grant Nos. AST-1716762 and AST-2108624 at Northwestern University and through the computational resources and staff contributions provided for the Quest High Performance Computing Facility at Northwestern University. Quest is jointly supported by the Office of the Provost, the Office for Research, and Northwestern University Information Technology. K.K. is supported by an NSF Astronomy and Astrophysics Postdoctoral Fellowship under award AST-2001751. N.C.W. acknowledges support from the CIERA Riedel Family Graduate Fellowship. F.K acknowledges support from the CIERA BoV Graduate Fellowship. G.F., N.C.W., and F.A.R. acknowledge support from NASA grant No. 80NSSC21K1722. Software: CMC (Joshi et al. 2000, 2001; Fregeau et al. 2003; Fregeau & Rasio 2007; Chatterjee et al. 2010; Umbreit et al. 2012; Chatterjee et al. 2013; Pattabiraman & Umbreit 2013; Morscher et al. 2015; Rodriguez et al. 2016, 2022), Fewbody (Fregeau et al. 2004), COSMIC (Breivik et al. 2020), NumPy (Harris et al. 2020), matplotlib (Hunter 2007), pandas (McKinney 2010; Reback et al. 2021).

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Submitted - 2111-14866.pdf

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Additional details

Created:
October 9, 2023
Modified:
October 24, 2023