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

Abstract

Gravitational waves provide a unique tool for observational astronomy. While the first LIGO–Virgo catalogue of gravitational-wave transients (GWTC-1) contains eleven 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 eleven 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.

Towards the routine use of subdominant harmonics in gravitational-wave inference: Reanalysis of GW190412 with generation X waveform models

“…To this end we have varied the number of live points n live and the number n act of autocorrelation times to use before accepting a point. Our main series of runs, summarized in Table III, uses marginalisation over the distance parameter and then a reconstruction of the distance posterior as discussed in [47,86] to accelerate the convergence of nested sampling 1 . In Sec.…”

“…It was observed by all three detectors, with a network signal-tonoise ratio (SNR) of 19.1 +0.1 −0.3 from the final coherent Bayesian analysis reported in [1]. In briefly summarizing the event properties, we concentrate here on the results from Bayesian inference using the Bilby [45][46][47], LALInference [48] and RIFT [54,55] packages and the SEOBNR PHM [34] and IMRP P HM [33] waveform models. These LVC estimates of the properties of GW190412's source are listed in Table I together with our own results.…”

“…The modularity and flexibility of the model family allows to compare different approximations for the effects of spin precession and different choices for the final spin of the remnant black hole. Furthermore the drastically reduced computational cost of the new waveforms allows us to test in detail the impact of varying some of the settings of the Bayesian sampling algorithms we use [45][46][47]. We find that by replacing IMRP P HM with our upgraded precessing higher-modes model IMRP -XPHM, the disagreement between the frequency and timedomain models observed in [1] can be reduced significantly, and the uncertainty intervals for key parameters can be tightened.…”

“…IV, and a summary and our conclusions in Sec. V. Further comparisons are presented in appendices: while all our main results are obtained with the parallel Bilby code [45][46][47], in appendix A we also compare these results with comparison runs of the LALInference code [48]. And in appendix B we compare our main Bilby runs, which have been obtained with marginalisation over distance in order to improve convergence, with runs that do not use this approximation.…”

Measuring the Primordial Gravitational-Wave Background in the Presence of Astrophysical Foregrounds

“…(11)] on a grid in ðΩ α ; αÞ. For each segment we use the CPNEST [62] nested sampler as implemented in the BILBY [63,64] package to obtain posterior samples for the binary parameters using the likelihood in Eq. (4) under the assumption that there is no Gaussian background present: Ω α ¼ 0.…”