University of Tasmania
Browse

File(s) under permanent embargo

Binary black hole population properties inferred from the first and second observing runs of advanced LIGO and advanced Virgo

journal contribution
posted on 2023-05-21, 09:24 authored by Karelle SiellezKarelle Siellez

We present results on the mass, spin, and redshift distributions with phenomenological population models using the 10 binary black hole (BBH) mergers detected in the first and second observing runs completed by Advanced LIGO and Advanced Virgo. We constrain properties of the BBH mass spectrum using models with a range of parameterizations of the BBH mass and spin distributions. We find that the mass distribution of the more massive BH in such binaries is well approximated by models with no more than 1% of BHs more massive than 45 and a power-law index of α =  (90% credibility). We also show that BBHs are unlikely to be composed of BHs with large spins aligned to the orbital angular momentum. Modeling the evolution of the BBH merger rate with redshift, we show that it is flat or increasing with redshift with 93% probability. Marginalizing over uncertainties in the BBH population, we find robust estimates of the BBH merger rate density of R =  Gpc−3 yr−1 (90% credibility). As the BBH catalog grows in future observing runs, we expect that uncertainties in the population model parameters will shrink, potentially providing insights into the formation of BHs via supernovae, binary interactions of massive stars, stellar cluster dynamics, and the formation history of BHs across cosmic time.

History

Publication title

The Astrophysical Journal Letters

Volume

882

Article number

L24

Number

L24

Pagination

1-30

ISSN

2041-8205

Department/School

School of Natural Sciences

Publisher

Institute of Physics Publishing Ltd.

Place of publication

United Kingdom

Rights statement

Copyright (2019) The American Astronomical Society.

Repository Status

  • Restricted

Socio-economic Objectives

Expanding knowledge in the physical sciences

Usage metrics

    University Of Tasmania

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC