Rapster: a fast code for dynamical formation of black-hole binaries in dense star clusters

ORAL

Abstract

Recent gravitational wave observations revealed the existence of binary black-hole (BBH) mergers with unusually asymmetric and massive components. These events could have formed in dense stellar environments and theoretical understanding of the underlying astrophysical BBH populations is required to interpret the data. I present Rapster, a public python software that simulates the dynamical assembly of BBHs in star clusters implementing semi-analytic prescriptions (e-Print: 2210.10055 [astro-ph.HE]). The code is fast and simulates a typical cluster within a few seconds. As an application, I also discuss the formation of massive black holes via repeated mergers in nuclear star clusters.

*NSF Grants No. AST-2006538, No. PHY-2207502, No. PHY-090003, and No. PHY-20043NASA Grants No. 19-ATP19-0051, No. 20-LPS20-0011, and No. 21-ATP21-0010

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Publication: e-Print: 2210.10055 [astro-ph.HE]

Presenters

  • Konstantinos Kritos

    • Johns Hopkins University

Authors

  • Konstantinos Kritos

    • Johns Hopkins University

  • Vladimir Strokov

    • Johns Hopkins University

  • Vishal Baibhav

    • Northwestern University

  • Emanuele Berti

    • Johns Hopkins University

  • Joseph Silk

    • Johns Hopkins University