Bayesian probability

Physics

Inference

LIGO

Mathematics

Operating system

Astronomy

Artificial intelligence

Bayesian inference

Gravitational wave

Computer science

Astrophysics

Transient (computer programming)

Binary number

Arithmetic

Monthly Notices of the Royal Astronomical Society

ABSTRACT 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.

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

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