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

@article{RomeroShaw2020BayesianIF,
  title={Bayesian inference for compact binary coalescences with bilby: validation and application to the first LIGO–Virgo gravitational-wave transient catalogue},
  author={Isobel M Romero-Shaw and Colm Talbot and Sylvia Biscoveanu and V D’Emilio and Gregory Ashton and Christopher P. L. Berry and S Coughlin and Shanika Galaudage and C Hoy and Moritz Huebner and Khun Sang Phukon and Matthew Pitkin and Monica Rizzo and N Sarin and Royce Smith and Simon Stevenson and A Vajpeyi and M Ar{\`e}ne and Kamal Athar and Sharan Banagiri and Nirban Bose and Matthew Carney and Katerina Chatziioannou and J. A. Clark and Marta Colleoni and Roberto Cotesta and B Edelman and H{\'e}ctor Estell{\'e}s and C Garc{\'i}a-Quir{\'o}s and Abhirup Ghosh and Rhys Green and Carl-Johan Haster and Sascha Husa and David Keitel and A. X. Kim and Francisco Hernandez-Vivanco and I Maga{\~n}a Hernandez and Christos Karathanasis and Paul D. Lasky and N De Lillo and M. E. Lower and D Macleod and M Mateu-Lucena and A. L. Miller and M Millhouse and Soichiro Morisaki and S. H. Oh and Serguei Ossokine and Ethan Payne and Jade Powell and Geraint Pratten and Michael P{\"u}rrer and Antoni Ramos-Buades and V Raymond and Eric Thrane and John Veitch and D. C. Williams and M J Williams and L. Xiao},
  journal={Monthly Notices of the Royal Astronomical Society},
  year={2020},
  volume={499},
  pages={3295-3319}
}
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… Expand

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