Young Star Clusters Dominate the Production of Detached Black Hole–Star Binaries

Author:

Di Carlo Ugo NiccolòORCID,Agrawal PoojanORCID,Rodriguez Carl L.ORCID,Breivik KatelynORCID

Abstract

Abstract The recent discovery of two detached black hole–star (BH–star) binaries from Gaia’s third data release has sparked interest in understanding the formation mechanisms of these systems. We investigate the formation of these systems by dynamical processes in young star clusters (SCs) and via isolated binary (IB) evolution, using a combination of direct N-body and population synthesis simulations. We find that dynamical formation in SCs is nearly 50 times more efficient per unit of star formation at producing BH–star binaries than IB evolution. We expand this analysis to the full Milky Way (MW) using a FIRE-2 hydrodynamical simulation of an MW-mass galaxy. Even assuming that only 10% of star formation goes into SCs, we find that approximately four out of every five BH–star systems are formed dynamically, and that the MW contains a total of ∼2 × 105 BH–star systems. Many of these dynamically formed systems have longer orbital periods, greater eccentricities, and greater black hole masses than their isolated counterparts. For binaries older than 100 Myr, we show that any detectable system with e ≳ 0.5 or M BH ≳ 10 M can only be formed through dynamical processes. Our MW model predicts between 64 and 215 such detections from the complete DR4 Gaia catalog, with the majority of systems being dynamically formed in massive and metal-rich SCs. Finally, we compare our populations to the recently discovered Gaia BH1 and Gaia BH2, and conclude that the dynamical scenario is the most favorable formation pathway for both systems.

Funder

National Science Foundation

EC ∣ European Research Council

Charles E. Kaufman Foundation

Alfred P. Sloan Foundation

David and Lucile Packard Foundation

Simons Foundation

Publisher

American Astronomical Society

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3