Bayesian inference for compact binary coalescences with bilby : validation and application to the first LIGO–Virgo gravitational-wave transient catalogue
ARC Centre of Excellence for Gravitational Wave Discovery · Monash University · +35 more institutions
Abstract
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…
Citation impact
- FWCI
- 30.87
- Percentile
- 100%
- References
- 202
Authors
59- IMI. M. Romero-ShawCorresponding
ARC Centre of Excellence for Gravitational Wave Discovery, Monash University
- CTC. Talbot
California Institute of Technology, ARC Centre of Excellence for Gravitational Wave Discovery, Monash University
- SBS. Biscoveanu
Massachusetts Institute of Technology
- VDV. D’Emilio
Cardiff University
- GAG. Ashton
ARC Centre of Excellence for Gravitational Wave Discovery, Monash University
Topics & keywords
- LIGO
- Physics
- Gravitational wave
- Binary number
- Transient (computer programming)
- Inference
- Astrophysics
- Bayesian inference
Funding
- NSNational Science FoundationAwards: 0757058, 1912648, 0823459, 1726951, PHY-0757058, 1122374, PHY-1764464, DGE-1122374, PHY-1726951, PHY-0823459, PHY-1912648, CE170100004
- MIMassachusetts Institute of TechnologyAwards: PHY-0757058, 1122374
- CICalifornia Institute of Technology
- NUNorthwestern University
- MDMinisterio de Ciencia, Innovación y UniversidadesAwards: BEAGAL 18/00148, FPA2016-76821-P, PID2019, 501100011033, 13039/501100011033
- AGAustralian Government
- ECEuropean CommissionAwards: CE170100004, 13039/501100011033, 501100011033, 751492
- NRNational Research Foundation
- DODepartment of Science and Technology, Ministry of Science and Technology, India
- SUSwinburne University of Technology
- NRNational Research Foundation of KoreaAward: 2019R1A2C2006787
- CNCentre National de la Recherche Scientifique
- MDMinisterio de Ciencia e InnovaciónAwards: BEAGAL 18/00148, PID2019, 501100011033, AEI/10, 13039/501100011033, FPA2016-76821-P
- UDUniversitat de les Illes Balears
- GDGovern de les Illes BalearsAward: ITS 2017-006
- SAScience and Technology Facilities CouncilAwards: ST/V00154X/1, Gravitational Waves, ST/V001213/1, ST/V001337/1, ST/N005422/1, ST/V001396/1
- ARAustralian Research CouncilAwards: CE170100004, FT160100112
- AEAgencia Estatal de InvestigaciónAwards: 019-106416GB-I00/AEI/10.13039/501100011033, PID2019-106416GB-I00, 501100011033, 13039, FPA2016-76821-P, AEI/10, 13039/501100011033, PID2019
- DODivision of Arctic SciencesAwards: CE170100004, FT150100281, DP180103155