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Accuracy of binary black hole waveform models for aligned-spin binaries

Kumar, Prayush and Chu, Tony and Fong, Heather and Pfeiffer, Harald P. and Boyle, Michael and Hemberger, Daniel A. and Kidder, Lawrence E. and Scheel, Mark A. and Szilágyi, Béla (2016) Accuracy of binary black hole waveform models for aligned-spin binaries. Physical Review D, 93 (10). Art. No. 104050. ISSN 2470-0010.

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Coalescing binary black holes are among the primary science targets for second generation ground-based gravitational wave detectors. Reliable gravitational waveform models are central to detection of such systems and subsequent parameter estimation. This paper performs a comprehensive analysis of the accuracy of recent waveform models for binary black holes with aligned spins, utilizing a new set of 84 high-accuracy numerical relativity simulations. Our analysis covers comparable mass binaries (mass-ratio 1≤q≤3), and samples independently both black hole spins up to a dimensionless spin magnitude of 0.9 for equal-mass binaries and 0.85 for unequal mass binaries. Furthermore, we focus on the high-mass regime (total mass ≳50M⊙). The two most recent waveform models considered (PhenomD and SEOBNRv2) both perform very well for signal detection, losing less than 0.5% of the recoverable signal-to-noise ratio ρ, except that SEOBNRv2’s efficiency drops slightly for both black hole spins aligned at large magnitude. For parameter estimation, modeling inaccuracies of the SEOBNRv2 model are found to be smaller than systematic uncertainties for moderately strong GW events up to roughly ρ≲15. PhenomD’s modeling errors are found to be smaller than SEOBNRv2’s, and are generally irrelevant for ρ≲20. Both models’ accuracy deteriorates with increased mass ratio, and when at least one black hole spin is large and aligned. The SEOBNRv2 model shows a pronounced disagreement with the numerical relativity simulation in the merger phase, for unequal masses and simultaneously both black hole spins very large and aligned. Two older waveform models (PhenomC and SEOBNRv1) are found to be distinctly less accurate than the more recent PhenomD and SEOBNRv2 models. Finally, we quantify the bias expected from all four waveform models during parameter estimation for several recovered binary parameters: chirp mass, mass ratio, and effective spin.

Item Type:Article
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URLURL TypeDescription Paper
Pfeiffer, Harald P.0000-0001-9288-519X
Kidder, Lawrence E.0000-0001-5392-7342
Additional Information:© 2016 American Physical Society. Received 28 January 2016; published 25 May 2016. We thank Kipp Cannon, Adam Lewis, Eric Poisson and Aaron Zimmerman for helpful discussions. We are grateful to Ofek Birnholtz, Sebastian Khan, Lionel London, Frank Ohme and Michael Pürrer, for providing access to the IMRPhenomD code. Simulations used in this work were performed with SpEC [44]. 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 No. PHY-1404569 and No. AST-1333520; at Cornell from the Sherman Fairchild Foundation and NSF Grants No. PHY-1306125 and No. AST-1333129; and at Princeton from NSF Grant No. PHY-1305682 and the Simons Foundation. Calculations were performed at the GPC supercomputer at the SciNet HPC Consortium [113]; 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 Grant No. PHY-0960291; on the NSF XSEDE network under Grant No. TG-PHY990007N; on the NSF/NCSA Blue Waters at the University of Illinois with allocation jr6 under NSF PRAC Grant No. ACI-1440083. H. P. and P. K. thank the Albert-Einstein Institute, Potsdam, for hospitality during part of the time where this research was completed.
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
Simons FoundationUNSPECIFIED
Canada Foundation for InnovationUNSPECIFIED
Government of OntarioUNSPECIFIED
Ontario Research Fund-Research ExcellenceUNSPECIFIED
University of TorontoUNSPECIFIED
Ministére de l’Économie, de l’Innovation et des Exportations du Quebec (MEIE)UNSPECIFIED
Fonds de recherche du Québec-Nature et Technologies (FRQ-NT)UNSPECIFIED
Issue or Number:10
Record Number:CaltechAUTHORS:20160525-111650853
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Official Citation:Accuracy of binary black hole waveform models for aligned-spin binaries Prayush Kumar, Tony Chu, Heather Fong, Harald P. Pfeiffer, Michael Boyle, Daniel A. Hemberger, Lawrence E. Kidder, Mark A. Scheel, and Bela Szilagyi Phys. Rev. D 93, 104050
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:67349
Deposited By: Tony Diaz
Deposited On:26 May 2016 17:10
Last Modified:09 Mar 2020 13:19

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