Bayesian inference for compact binary coalescences with bilby: validation and application to the first LIGO–Virgo gravitational-wave transient catalogue

By I. Romero-Shaw, Colm Talbot, S. Biscoveanu, V. d’Emilio, G. Ashton, Christopher P. L. Berry, S. Coughlin, S. Galaudage, C. Hoy, M. Huebner and 49 more. Monthly notices of the Royal Astronomical Society, 2020

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Gravitational waves provide a unique tool for observational astronomy. While the first LIGO–Virgo catalogue of gravitational-wave transients (GWTC-1) contains 11 signals from black hole and neutron star binaries, the number of observations is increasing rapidly as detector sensitivity improves. To extract information from the observed signals, it is imperative to have fast, flexible, and scalable inference techniques. In a previous paper, we introduced bilby: a modular and user-friendly Bayesian inference library adapted to address the needs of gravitational-wave inference. In this work, we demonstrate that bilby produces reliable results for simulated gravitational-wave signals from compact binary mergers, and verify that it accurately reproduces results reported for the 11 GWTC-1 signals. Additionally, we provide configuration and output files for all analyses to allow for easy reproduction, modification, and future use. This work establishes that bilby is primed and ready to analyse the rapidly growing population of compact binary coalescence gravitational-wave signals.

Subfields: Astronomy and Astrophysics, Oceanography

View Paper: https://www.semanticscholar.org/paper/6c4e2fc3730b206adbd71e9f652e90d79a7ae1cd

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Citations in the corpus

GWTC-2.1: Deep extended catalog of compact binary coalescences observed by LIGO and Virgo during the first half of the third observing run (2021, methodology): “The rates of BBH and BNS binary mergers in the local Universe were estimated in a companion paper [122] to GWTC-2, using the count of detected events with FAR below 1 per year, combined with estimates of search sensitivity to the respective populations.”
GW231123: A Binary Black Hole Merger with Total Mass 190–265 M⊙ (2025, positive): “To sample the posterior distribution, we interface with dynesty (Speagle 2020) via the bilby library (Ashton et al. 2019; Romero-Shaw et al. 2020b).”
Properties and astrophysical implications of the 150 Msun binary black hole merger GW190521 (2020, methodology): “Using the dynesty nested sampling algorithm (Speagle 2020) within Bilby (Ashton et al. 2019; Romero-Shaw et al. 2020), we find Bayes factors log10B BBH cusp = 29.8 and log10B BBH kink = 29.7, strongly favoring the BBH hypothesis, thus it is highly unlikely that this event was of cosmic string origin”
GW190521: Orbital Eccentricity and Signatures of Dynamical Formation in a Binary Black Hole Merger Signal (2020, methodology): “We use the Bayesian inference library BILBY (Ashton et al. 2019; Romero-Shaw et al. 2020) to perform an analysis using our “proposal” model: the spinaligned quasi-circular-waveform model IMRPHENOMD (Khan et al. 2016).”
Observation of Gravitational Waves from the Coalescence of a 2.5–4.5 M ⊙ Compact Object and a Neutron Star (2024, methodology): “Standard priors (e.g., Romero-Shaw et al. 2020; Abbott et al. 2024b) are used for all the other extrinsic binary parameters.”
GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run (2020, background): “002 bit, which is the variation that is shown to arise due to stochastic sampling [234].”