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A self-consistent method to estimate the rate of compact binary coalescences with a Poisson mixture model

Kapadia, Shasvath J. and Caudill, Sarah and Creighton, Jolien D. E. and Farr, Will M. and Mendell, Gregory and Weinstein, Alan and Cannon, Kipp and Fong, Heather and Godwin, Patrick and Lo, Rico K. L. and Magee, Ryan and Meacher, Duncan and Messick, Cody and Mohite, Siddharth R. and Mukherjee, Debnandini and Sachdev, Surabhi (2020) A self-consistent method to estimate the rate of compact binary coalescences with a Poisson mixture model. Classical and Quantum Gravity, 37 (4). Art. No. 045007. ISSN 0264-9381. doi:10.1088/1361-6382/ab5f2d. https://resolver.caltech.edu/CaltechAUTHORS:20200116-101440415

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Abstract

The recently published GWTC-1 (Abbott B P et al (LIGO Scientific Collaboration and Virgo Collaboration) 2019 Phys. Rev. X 9 031040)—a journal article summarizing the search for gravitational waves (GWs) from coalescing compact binaries in data produced by the LIGO-Virgo network of ground-based detectors during their first and second observing runs—quoted estimates for the rates of binary neutron star, neutron star black hole binary, and binary black hole mergers, as well as assigned probabilities of astrophysical origin for various significant and marginal GW candidate events. In this paper, we delineate the formalism used to compute these rates and probabilities, which assumes that triggers above a low ranking statistic threshold, whether of terrestrial or astrophysical origin, occur as independent Poisson processes. In particular, we include an arbitrary number of astrophysical categories by redistributing, via mass-based template weighting, the foreground probabilities of candidate events, across source classes. We evaluate this formalism on synthetic GW data, and demonstrate that this method works well for the kind of GW signals observed during the first and second observing runs.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1088/1361-6382/ab5f2dDOIArticle
https://arxiv.org/abs/1903.06881arXivDiscussion Paper
https://resolver.caltech.edu/CaltechAUTHORS:20190507-102334917Related ItemAbbott B P et al.; 2019 Phys. Rev. X 9 031040
ORCID:
AuthorORCID
Kapadia, Shasvath J.0000-0001-5318-1253
Caudill, Sarah0000-0002-8927-6673
Farr, Will M.0000-0003-1540-8562
Weinstein, Alan0000-0002-0928-6784
Magee, Ryan0000-0001-9769-531X
Messick, Cody0000-0002-8230-3309
Mukherjee, Debnandini0000-0001-7335-9418
Sachdev, Surabhi0000-0002-2432-7070
Additional Information:© 2020 IOP Publishing Ltd. Received 13 May 2019, revised 13 November 2019; Accepted for publication 5 December 2019; Published 16 January 2020. We thank the LIGO-Virgo Scientific Collaboration for access to data. LIGO was constructed by the California Institute of Technology and Massachusetts Institute of Technology with funding from the National Science Foundation (NSF) and operates under cooperative agreement PHY-0757058. We gratefully acknowledge the support by NSF Grant PHY-1626190 for the UWM computer cluster. We also thank Deep Chatterjee, Shaon Ghosh and Chad Hanna for illuminating discussions. SJK gratefully acknowledges suppport through NSF grant PHY-1607585. SRM thanks the LSSTC Data Science Fellowship Program, which is funded by LSSTC, NSF Cybertraining Grant # 1829740, the Brinson Foundation, and the Moore Foundation.
Group:LIGO
Funders:
Funding AgencyGrant Number
NSFPHY-0757058
NSFPHY-1626190
NSFPHY-1607585
Large Synoptic Survey Telescope CorporationUNSPECIFIED
NSFOAC-1829740
Brinson FoundationUNSPECIFIED
Gordon and Betty Moore FoundationUNSPECIFIED
Subject Keywords:gravitational waves, LIGO, rates of compact binary mergers
Issue or Number:4
DOI:10.1088/1361-6382/ab5f2d
Record Number:CaltechAUTHORS:20200116-101440415
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20200116-101440415
Official Citation:Shasvath J Kapadia et al 2020 Class. Quantum Grav. 37 045007
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:100760
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:16 Jan 2020 18:30
Last Modified:12 Jul 2022 19:41

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