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Published December 2020 | Published + Submitted
Journal Article Open

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


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.

Additional Information

© 2020 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model). Accepted 2020 September 11. Received 2020 September 8; in original form 2020 June 1. Published: 21 September 2020. This work is supported through Australian Research Council (ARC) Centre of Excellence CE170100004. PDL is supported through ARC Future Fellowship FT160100112 and ARC Discovery Project DP180103155. ET is supported through ARC Future Fellowship FT150100281 and CE170100004. This work is partially supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 2019R1A2C2006787). NB acknowledges Inspire division, DST, Government of India for the fellowship support. This work is partially supported by the National Science Foundation under Grant No. PHY-1912648. SB, C-JH, and CT acknowledge support of the National Science Foundation, and the LIGO Laboratory. SB is also supported by the Paul and Daisy Soros Fellowship for New Americans and the NSF Graduate Research Fellowship under Grant No. DGE-1122374. This work was partially supported by European Union FEDER funds, the Spanish Ministry of Science and Innovation and the Spanish Agencia Estatal de Investigación grants FPA2016-76821-P and PID2019-106416GB-I00/AEI/10.13039/501100011033, the Comunitat Autonoma de les Illes Balears through the Direcció General de Política Universitaria i Recerca with funds from the Tourist Stay Tax Law ITS 2017-006 (PRD2018/24), the Vicepresidència i Conselleria d'Innovació, Recerca i Turisme, Conselleria d'Educació, i Universitats del Govern de les Illes Balears and Fons Social Europeu. MC acknowledges funding from the European Union's Horizon 2020 research and innovation programme, under the Marie Skłodowska-Curie grant agreement No. 751492. D.K. is supported by the Spanish Ministerio de Ciencia, Innovación y Universidades (ref. BEAGAL 18/00148) and cofinanced by the Universitat de les Illes Balears. This work used BILBY = v0.6.9, BILBYPIPE = v0.3.12, DYNESTY = v1.0.1, LALSUITE =v6.49, and PESUMMARY = v0.5.6. This research has made use of data, software and/or web tools obtained from the Gravitational Wave Open Science Center (Abbott et al. 2019e), a service of LIGO Laboratory, the LIGO Scientific Collaboration and the Virgo Collaboration. Computing was performed on the OzSTAR Australian national facility at Swinburne University of Technology, which receives funding in part from the Astronomy National Collaborative Research Infrastructure Strategy (NCRIS) allocation provided by the Australian Government, LIGO Laboratory computing clusters at California Institute of Technology and LIGO Hanford Observatory supported by National Science Foundation Grants PHY-0757058 and PHY-0823459, and the Quest computing cluster, which is jointly supported by the Office of the Provost, the Office for Research and Northwestern University Information Technology, and funded by the National Science Foundation under Grant No. PHY-1726951. LIGO was constructed by the California Institute of Technology and Massachusetts Institute of Technology with funding from the National Science Foundation and operates under cooperative agreement PHY-1764464. Virgo is funded by the French Centre National de Recherche Scientifique (CNRS), the Italian Istituto Nazionale della Fisica Nucleare (INFN) and the Dutch Nikhef, with contributions by Polish and Hungarian institutes. Data Availability Statement: We analyse publicly available data (Abbott et al. 2019e), and make use of publicly available PSDs (Abbott et al. 2019b) and calibration envelopes (Abbott et al. 2019c). We compare our results against publicly available posterior samples (Abbott et al. 2018a). We make our own results publicly accessible online (Romero-Shaw et al. 2020c).

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August 20, 2023
August 20, 2023