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Distinguishing binary black hole precessional morphologies with gravitational wave observations

Nathan K. Johnson-McDaniel1, Khun Sang Phukon2,3,4,5, N. V. Krishnendu6,7,8, and Anuradha Gupta1

  • 1Department of Physics and Astronomy, The University of Mississippi, University, Mississippi 38677, USA
  • 2Nikhef-National Institute for Subatomic Physics, Science Park, 1098 XG Amsterdam, The Netherlands
  • 3Institute for High-Energy Physics, University of Amsterdam, Science Park, 1098 XG Amsterdam, The Netherlands
  • 4Institute for Gravitational and Subatomic Physics, Utrecht University, Princetonplein 1, 3584 CC Utrecht, The Netherlands
  • 5School of Physics and Astronomy and Institute for Gravitational Wave Astronomy, University of Birmingham, Edgbaston, Birmingham, B15 9TT, United Kingdom
  • 6Max Planck Institute for Gravitational Physics (Albert Einstein Institute), Callinstr. 38, D-30167 Hannover, Germany
  • 7Leibniz Universität Hannover, D-30167 Hannover, Germany
  • 8International Centre for Theoretical Sciences (ICTS), Survey No. 151, Shivakote, Hesaraghatta, Uttarahalli Hobli, Bengaluru, 560089

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Phys. Rev. D 108, 103003 – Published 3 November, 2023Erratum Phys. Rev. D 109, 129903 (2024)

DOI: https://doi.org/10.1103/PhysRevD.108.103003

Abstract

The precessional motion of binary black holes can be classified into one of three morphologies, based on the evolution of the angle between the components of the spins in the orbital plane: Circulating, librating around 0, and librating around π. These different morphologies can be related to the binary’s formation channel and are imprinted in the binary’s gravitational wave signal. In this paper, we develop a Bayesian model selection method to determine the preferred spin morphology of a detected binary black hole. The method involves a fast calculation of the morphology which allows us to restrict to a specific morphology in the Bayesian stochastic sampling. We investigate the prospects for distinguishing between the different morphologies using gravitational waves in the Advanced LIGO/Advanced Virgo network with their plus-era sensitivities. For this, we consider fiducial high- and low-mass binaries having different spin magnitudes and signal-to-noise ratios (SNRs). We find that in the cases with high spin and high SNR, the true morphology is strongly favored with log10 Bayes factors ≳4 compared to both alternative morphologies when the binary’s parameters are not close to the boundary between morphologies. However, when the binary parameters are close to the boundary between morphologies, only one alternative morphology is strongly disfavored. In the low-spin, high-SNR cases, the true morphology is still favored with a log10 Bayes factor ∼2 compared to one alternative morphology, while in the low-SNR cases the log10 Bayes factors are at most ∼1 for many binaries. We also consider the gravitational wave signal from GW200129_065458 that has some evidence for precession (modulo data quality issues) and find that there is no preference for a specific morphology. Our method for restricting the prior to a given morphology is publicly available through an easy-to-use python package called bbh_spin_morphology_prior.

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Erratum

Erratum: Distinguishing binary black hole precessional morphologies with gravitational wave observations [Phys. Rev. D 108, 103003 (2023)]

Nathan K. Johnson-McDaniel, Khun Sang Phukon, N. V. Krishnendu, and Anuradha Gupta
Phys. Rev. D 109, 129903 (2024)

Article Text

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Phys. Rev. D 108, 103003– Published 3 November, 2023
  • Received 25 January 2023
  • Revised 24 August 2023
  • Accepted 22 September 2023
Article part of CHORUS
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