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Fast and Accurate Prediction of Numerical Relativity Waveforms from Binary Black Hole Coalescences Using Surrogate Models

Blackman, Jonathan and Field, Scott E. and Galley, Chad R. and Szilágyi, Béla and Scheel, Mark A. and Tiglio, Manuel and Hemberger, Daniel A. (2015) Fast and Accurate Prediction of Numerical Relativity Waveforms from Binary Black Hole Coalescences Using Surrogate Models. Physical Review Letters, 115 (12). Art. No. 121102. ISSN 0031-9007. https://resolver.caltech.edu/CaltechAUTHORS:20151013-153704017

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Abstract

Simulating a binary black hole coalescence by solving Einstein’s equations is computationally expensive, requiring days to months of supercomputing time. Using reduced order modeling techniques, we construct an accurate surrogate model, which is evaluated in a millisecond to a second, for numerical relativity (NR) waveforms from nonspinning binary black hole coalescences with mass ratios in [1, 10] and durations corresponding to about 15 orbits before merger. We assess the model’s uncertainty and show that our modeling strategy predicts NR waveforms not used for the surrogate’s training with errors nearly as small as the numerical error of the NR code. Our model includes all spherical-harmonic _(-2)Y_(ℓm) waveform modes resolved by the NR code up to ℓ=8. We compare our surrogate model to effective one body waveforms from 50M⊙ to 300M⊙ for advanced LIGO detectors and find that the surrogate is always more faithful (by at least an order of magnitude in most cases).


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1103/PhysRevLett.115.121102 DOIArticle
http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.115.121102PublisherArticle
http://arxiv.org/abs/1502.07758arXivDiscussion Paper
Additional Information:© 2015 American Physical Society. Received 2 March 2015; revised manuscript received 5 August 2015; published 18 September 2015. We thank Mike Boyle, Alessandra Buonanno, Collin Capano, Jan Hesthaven, Jason Kaye, Geoffrey Lovelace, Lee Lindblom, Tom Loredo, Christian Ott, Yi Pan, Harald Pfeiffer, Rory Smith, and Nicholas Taylor for many useful discussions throughout this project. This work was supported in part by NSF Grants No. CAREER PHY-0956189, No. PHY-1068881, No. PHY-1005655, No. PHY-1440083, No. PHY-1404569, and No. AST-1333520 to Caltech, NSF Grants No. PHY-1306125 and No. AST-1333129 to Cornell University, NSF Grant No. PHY-1500818 to the University of California at San Diego, NSF Grants No. PHY-1208861 and No. PHY-1316424 to the University of Maryland (UMD), NSERC of Canada, and the Sherman Fairchild Foundation. Computations were performed on the Zwicky cluster at Caltech, which is supported by the Sherman Fairchild Foundation and by NSF Grant No. PHY-0960291. Portions of this research were carried out at the Center for Scientific Computation and Mathematical Modeling cluster at UMD.
Funders:
Funding AgencyGrant Number
NSFPHY-0956189
NSFPHY-1068881
NSFPHY-1005655
NSFPHY-1440083
NSFPHY-1404569
NSFAST-1333520
NSFPHY-1306125
NSFAST-1333129
NSFPHY-1500818
NSFPHY-1208861
NSFPHY-1316424
Natural Sciences and Engineering Research Council of Canada (NSERC)UNSPECIFIED
Sherman Fairchild FoundationUNSPECIFIED
NSFPHY-0960291
Issue or Number:12
Classification Code:PACS numbers: 04.25.dg, 02.60.-x, 04.30.-w, 04.30.Db
Record Number:CaltechAUTHORS:20151013-153704017
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20151013-153704017
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:61089
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:14 Oct 2015 14:49
Last Modified:03 Oct 2019 09:04

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