Posterior samples of the parameters of binary black holes from Advanced LIGO, Virgo’s second observing run

De, Soumi; Biwer, Christopher M.; Capano, Collin D.; Nitz, Alexander H.; Brown, Duncan A.

doi:10.1038/s41597-019-0086-6

Title: Posterior samples of the parameters of binary black holes from Advanced LIGO, Virgo’s second observing run

Journal Article · Mon Jun 03 00:00:00 EDT 2019 · Scientific Data

DOI:https://doi.org/10.1038/s41597-019-0086-6· OSTI ID:1532724

^[1]; Biwer, Christopher M. ^[2]; Capano, Collin D. ^[3]; Nitz, Alexander H. ^[3]; Brown, Duncan A. ^[1]

Syracuse Univ., Syracuse, NY (United States)
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Max-Planck-Institut für Gravitationsphysik, Hannover (Germany); Leibniz Univ. Hannover, Hannover (Germany)

This paper presents a parameter estimation analysis of the seven binary black hole mergers—GW170104, GW170608, GW170729, GW170809, GW170814, GW170818, and GW170823—detected during the second observing run of the Advanced LIGO and Virgo observatories using the gravitational-wave open data. We describe the methodology for parameter estimation of compact binaries using gravitational-wave data, and we present the posterior distributions of the inferred astrophysical parameters. We release our samples of the posterior probability density function with tutorials on using and replicating our results presented in this paper.

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Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: National Science Foundation (NSF); USDOE

Grant/Contract Number:: 89233218CNA000001

OSTI ID:: 1532724

Report Number(s):: LA-UR-19-22468

Journal Information:: Scientific Data, Vol. 6, Issue 1; ISSN 2052-4463

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 6 works

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Cited By (1)

Open data from the first and second observing runs of Advanced LIGO and Advanced Virgo Abbott, Rich; Abbott, Thomas D.; Abraham, Sheelu SoftwareX, Vol. 13, p. 100658 https://doi.org/10.1016/j.softx.2021.100658	journal	January 2021

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