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Published October 21, 2018 | Published + Accepted Version
Journal Article Open

Predicting the binary black hole population of the Milky Way with cosmological simulations

Abstract

Binary black holes are the primary endpoint of massive stars. Their properties provide a unique opportunity to constrain binary evolution, which remains poorly understood. We predict the main properties of binary black holes and their merger products in/around the Milky Way. We present the first combination of a high-resolution cosmological simulation of a Milky Way-mass galaxy with a binary population synthesis model in this context. The hydrodynamic simulation, taken from the FIRE project, provides a cosmologically realistic star formation history for the galaxy, its stellar halo, and satellites. During post-processing, we apply a metallicity-dependent evolutionary model to the star particles to produce individual binary black holes. We find that 7 × 10^5 binary black holes have merged in the model Milky Way, and 1.2 × 10^6 binaries are still present, with a mean mass of 28 M_⊙⁠. Because the black hole progenitors are strongly biased towards low-metallicity stars, half reside in the stellar halo and satellites and a third were formed outside the main galaxy. The numbers and mass distribution of the merged systems is broadly compatible with the LIGO/Virgo detections. Our simplified binary evolution models predict that LISA will detect more than 20 binary black holes, but that electromagnetic observations will be challenging. Our method will allow for constraints on the evolution of massive binaries based on comparisons between observations of compact objects and the predictions of varying binary evolution models. We provide online data of our star formation model and binary black hole distribution.

Additional Information

© 2018 The Author(s) Published by Oxford University Press on behalf of the 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) Accepted 2018 July 25. Received 2018 July 20; in original form 2018 January 8. Astrid Lamberts would like to thank V. Ravi, H. Vedantham, M. Heida, C. Henderson, Y. Shvarzvald, S. Novati, and S. Taylor for discussions about observational implications of this work and D. Clausen for his help with the BPS models. Numerical calculations were run on the Caltech compute cluster 'Wheeler,' allocations from XSEDE TG-AST130039 and PRAC NSF.1713353 supported by the NSF, and NASA HEC SMD-16-7592. Support for AL and PFH was provided by an Alfred P. Sloan Research Fellowship, NASA ATP Grant NNX14AH35G, and NSF Collaborative Research Grant 1715847 and CAREER grant 1455342. Support for SGK was provided by NASA through Einstein Postdoctoral Fellowship grant number PF5-160136 awarded by the Chandra X-ray Center, which is operated by the Smithsonian Astrophysical Observatory for NASA under contract NAS8-03060. EQ was supported in part by NSF grant AST-1715070 and a Simons Investigator Award from the Simons Foundation. JSB was supported by NSF grant AST-1518291 and by NASA through HST theory grants ( programmes AR-13921, AR-13888, and AR-14282.001) awarded by STScI, which is operated by the Association of Universities for Research in Astronomy (AURA), Inc., under NASA contract NAS5-26555. CAFG was supported by NSF through grants AST-1412836, AST-1517491, AST-1715216, and CAREER award AST-1652522 and by NASA trough grant NXX-15AB22G. AW was supported by NASA through grants HST-GO-14734 and HST-AR-15057 from STScI. DK acknowledges support from NSF grants AST-1412153 and AST-1715101 and the Cottrell Scholar Award from the Research Corporation for Science Advancement. RES was supported by an NSF astronomy & Astrophysics Postdoctoral Fellowship under grant AST-1400989. This study was initiated during K. Drango's 'Freshman Summer Research Internship', organized by the Caltech Center for Diversity. We thank Kacper Kowalik and the whole yt hub team where our dataset is hosted. It is supported in part by the Gordon and Betty Moore Foundation's Data Drive Discovery Initiative through grant GBMF4561 to Matthew Turk and the National Science Foundation under Grant number ACI-1535651.

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Additional details

Created:
August 19, 2023
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October 19, 2023