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Rapidly evaluating the compact-binary likelihood function via interpolation

Smith, R. J. E. and Hanna, C. and Mandel, I. and Vecchio, A. (2014) Rapidly evaluating the compact-binary likelihood function via interpolation. Physical Review D, 90 (4). Art. No. 044074. ISSN 2470-0010.

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Bayesian parameter estimation on gravitational waves from compact-binary coalescences (CBCs) typically requires millions of template waveform computations at different values of the parameters describing the binary. Sampling techniques such as Markov chain Monte Carlo and nested sampling evaluate likelihoods and, hence, compute template waveforms, serially; thus, the total computational time of the analysis scales linearly with that of template generation. Here we address the issue of rapidly computing the likelihood function of CBC sources with nonspinning components. We show how to efficiently compute the continuous likelihood function on the three-dimensional subspace of parameters on which it has a nontrivial dependence—the chirp mass, symmetric mass ratio and coalescence time—via interpolation. Subsequently, sampling this interpolated likelihood function is a significantly cheaper computational process than directly evaluating the likelihood; we report improvements in computational time of two to three orders of magnitude while keeping likelihoods accurate to ≲0.025%. Generating the interpolant of the likelihood function over a significant portion of the CBC mass space is computationally expensive but highly parallelizable, so the wall time can be very small relative to the time of a full parameter-estimation analysis.

Item Type:Article
Related URLs:
URLURL TypeDescription Paper DOIArticle
Mandel, I.0000-0002-6134-8946
Vecchio, A.0000-0002-6254-1617
Additional Information:© 2014 American Physical Society. Received 23 May 2013; revised manuscript received 29 January 2014; published 29 August 2014. We thank Kipp Cannon and Drew Keppel for many helpful discussions. R. J. E. S. acknowledges support from a Perimeter Institute visiting graduate fellowship. Research at Perimeter Institute is supported through Industry Canada and by the Province of Ontario through the Ministry of Research and Innovation. The authors also gratefully acknowledge the support of the United States National Science Foundation for the construction and operation of the LIGO Laboratory under Cooperative Agreement No. NSF-PHY-0757058.
Funding AgencyGrant Number
Perimeter InstituteUNSPECIFIED
Industry CanadaUNSPECIFIED
Province of Ontario Ministry of Research and InnovationUNSPECIFIED
NSF Cooperative AgreementPHY-0757058
Issue or Number:4
Classification Code:PACS: 04.30.-w, 04.80.Nn
Record Number:CaltechAUTHORS:20140925-150256306
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:50040
Deposited By: Tony Diaz
Deposited On:30 Sep 2014 19:46
Last Modified:09 Mar 2020 13:19

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