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On the accuracy and precision of numerical waveforms: effect of waveform extraction methodology

Chu, Tony and Fong, Heather and Kumar, Prayush and Pfeiffer, Harald P. and Boyle, Michael and Hemberger, Daniel A. and Kidder, Lawrence E. and Scheel, Mark A. and Szilágyi, Béla (2016) On the accuracy and precision of numerical waveforms: effect of waveform extraction methodology. Classical and Quantum Gravity, 33 (16). Art. No. 165001. ISSN 0264-9381. https://resolver.caltech.edu/CaltechAUTHORS:20160729-133053389

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Abstract

We present a new set of 95 numerical relativity simulations of non-precessing binary black holes (BBHs). The simulations sample comprehensively both black-hole spins up to spin magnitude of 0.9, and cover mass ratios 1–3. The simulations cover on average 24 inspiral orbits, plus merger and ringdown, with low initial orbital eccentricities e < 10^(-4). A subset of the simulations extends the coverage of non-spinning BBHs up to mass ratio q = 10. Gravitational waveforms at asymptotic infinity are computed with two independent techniques: extrapolation and Cauchy characteristic extraction. An error analysis based on noise-weighted inner products is performed. We find that numerical truncation error, error due to gravitational wave extraction, and errors due to the Fourier transformation of signals with finite length of the numerical waveforms are of similar magnitude, with gravitational wave extraction errors dominating at noise-weighted mismatches of ~3 x 10^(-4). This set of waveforms will serve to validate and improve aligned-spin waveform models for gravitational wave science.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1088/0264-9381/33/16/165001DOIArticle
http://iopscience.iop.org/article/10.1088/0264-9381/33/16/165001/metaPublisherArticle
https://arxiv.org/abs/1512.06800arXivDiscussion Paper
ORCID:
AuthorORCID
Pfeiffer, Harald P.0000-0001-9288-519X
Kidder, Lawrence E.0000-0001-5392-7342
Additional Information:© 2016 IOP Publishing Ltd. Received 19 January 2016, revised 9 June 2016; Accepted for publication 27 June 2016; Published 14 July 2016. We gratefully acknowledge support for this research at CITA from NSERC of Canada, the Ontario Early Researcher Awards Program, the Canada Research Chairs Program, and the Canadian Institute for Advanced Research; at Caltech from the Sherman Fairchild Foundation and NSF grants PHY-1404569 and AST-1333520; at Cornell from the Sherman Fairchild Foundation and NSF grants PHY-1306125 and AST-1333129; and at Princeton from NSF grant PHY-1305682 and the Simons Foundation. Calculations were performed at the GPC supercomputer at the SciNet HPC Consortium [88]; SciNet is funded by: the Canada Foundation for Innovation (CFI) under the auspices of Compute Canada; the Government of Ontario; Ontario Research Fund (ORF)—Research Excellence; and the University of Toronto. Further calculations were performed on the Briarée cluster at Sherbrooke University, managed by Calcul Québec and Compute Canada and with operation funded by the Canada Foundation for Innovation (CFI), Ministére de l'Économie, de l'Innovation et des Exportations du Quebec (MEIE), RMGA and the Fonds de recherche du Québec—Nature et Technologies (FRQ-NT); on the Zwicky cluster at Caltech, which is supported by the Sherman Fairchild Foundation and by NSF award PHY-0960291; on the NSF XSEDE network under grant TG-PHY990007N; on the NSF/NCSA Blue Waters at the University of Illinois with allocation jr6 under NSF PRAC Award ACI-1440083. HP and PK thank the Albert-Einstein Institute, Potsdam, for hospitality during part of the time where this research was completed.
Funders:
Funding AgencyGrant Number
Natural Sciences and Engineering Research Council of Canada (NSERC)UNSPECIFIED
Ontario Early Researcher Awards ProgramUNSPECIFIED
Canada Research Chairs ProgramUNSPECIFIED
Canadian Institute for Advanced Research (CIAR)UNSPECIFIED
Sherman Fairchild FoundationUNSPECIFIED
NSFPHY-1404569
NSFAST-1333520
NSFPHY-1306125
NSFAST-1333129
NSFPHY-1305682
Simons FoundationUNSPECIFIED
Canada Foundation for InnovationUNSPECIFIED
Compute CanadaUNSPECIFIED
Government of OntarioUNSPECIFIED
Ontario Research FundUNSPECIFIED
University of TorontoUNSPECIFIED
Ministére de l’Économie, de l’Innovation et des Exportations du Quebec (MEIE)UNSPECIFIED
RMGAUNSPECIFIED
Fonds de recherche du Québec-Nature et Technologies (FRQ-NT)UNSPECIFIED
NSFPHY-0960291
NSFTG-PHY990007N
NSFACI-1440083
Issue or Number:16
Record Number:CaltechAUTHORS:20160729-133053389
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20160729-133053389
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:69321
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:29 Jul 2016 21:10
Last Modified:09 Mar 2020 13:19

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