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Improved effective-one-body model of spinning, nonprecessing binary black holes for the era of gravitational-wave astrophysics with advanced detectors

Bohé, Alejandro and Shao, Lijing and Taracchini, Andrea and Buonanno, Alessandra and Babak, Stanislav and Harry, Ian W. and Hinder, Ian and Ossokine, Serguei and Pürrer, Michael and Raymond, Vivien and Chu, Tony and Fong, Heather and Kumar, Prayush and Pfeiffer, Harald P. and Boyle, Michael and Hemberger, Daniel A. and Kidder, Lawrence E. and Lovelace, Geoffrey and Scheel, Mark A. and Szilágyi, Béla (2017) Improved effective-one-body model of spinning, nonprecessing binary black holes for the era of gravitational-wave astrophysics with advanced detectors. Physical Review D, 95 (4). Art. No. 044028. ISSN 2470-0010. http://resolver.caltech.edu/CaltechAUTHORS:20170222-095610973

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Abstract

We improve the accuracy of the effective-one-body (EOB) waveforms that were employed during the first observing run of Advanced LIGO for binaries of spinning, nonprecessing black holes by calibrating them to a set of 141 numerical-relativity (NR) waveforms. The NR simulations expand the domain of calibration toward larger mass ratios and spins, as compared to the previous EOBNR model. Merger-ringdown waveforms computed in black-hole perturbation theory for Kerr spins close to extremal provide additional inputs to the calibration. For the inspiral-plunge phase, we use a Markov-chain Monte Carlo algorithm to efficiently explore the calibration space. For the merger-ringdown phase, we fit the NR signals with phenomenological formulae. After extrapolation of the calibrated model to arbitrary mass ratios and spins, the (dominant-mode) EOBNR waveforms have faithfulness—at design Advanced-LIGO sensitivity—above 99% against all the NR waveforms, including 16 additional waveforms used for validation, when maximizing only on initial phase and time. This implies a negligible loss in event rate due to modeling for these binary configurations. We find that future NR simulations at mass ratios ≳4 and double spin ≳0.8 will be crucial to resolving discrepancies between different ways of extrapolating waveform models. We also find that some of the NR simulations that already exist in such region of parameter space are too short to constrain the low-frequency portion of the models. Finally, we build a reduced-order version of the EOBNR model to speed up waveform generation by orders of magnitude, thus enabling intensive data-analysis applications during the upcoming observation runs of Advanced LIGO.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1103/PhysRevD.95.044028DOIArticle
http://journals.aps.org/prd/abstract/10.1103/PhysRevD.95.044028PublisherArticle
https://arxiv.org/abs/1611.03703arXivDiscussion Paper
Additional Information:© 2017 American Physical Society. Received 14 November 2016; published 17 February 2017. We would like to thank Mark Hannam and Sascha Husa for kindly providing us with the nonpublic BAM (q,χ_1,χ_2)=(8,0.85,0.85) waveform, which was used in Sec. IV to calibrate the EOB model. This work was supported in part at Caltech by the Sherman Fairchild Foundation and NSF Grants No. PHY-1404569, at Cornell by NSF Grants No. PHY-1606654 and No. AST-1333129 and the Sherman Fairchild Foundation and at Cal State Fullerton by NSF grants PHY-1307489 and PHY-1606522. 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. Calculations were performed at the GPC supercomputer at the SciNet HPC Consortium; 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), Ministère 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). Some of the calculations were performed on the ORCA cluster at Cal State Fullerton, which is supported by the Research Corporation for Science Advancement, PHY-1429873, and Cal State Fullerton. New NR simulations were performed on the AEI Datura and Minerva clusters. The Markov-chain Monte Carlo runs were performed on the AEI Vulcan cluster.
Group:LIGO
Funders:
Funding AgencyGrant Number
Sherman Fairchild FoundationUNSPECIFIED
NSFPHY-1404569
NSFPHY-1606654
NSFAST-1333129
NSFPHY-1307489
NSFPHY-1606522
Natural Sciences and Engineering Research Council of Canada (NSERC)UNSPECIFIED
Ontario Early Researcher Awards ProgramUNSPECIFIED
Canada Research Chairs ProgramUNSPECIFIED
Canadian Institute for Advanced Research (CIFAR)UNSPECIFIED
Canada Foundation for InnovationUNSPECIFIED
Compute CanadaUNSPECIFIED
Government of OntarioUNSPECIFIED
Ontario Research Fund-Research ExcellenceUNSPECIFIED
University of TorontoUNSPECIFIED
Ministère 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-1429873
California State University, FullertonUNSPECIFIED
Record Number:CaltechAUTHORS:20170222-095610973
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20170222-095610973
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:74463
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:22 Feb 2017 19:27
Last Modified:22 Feb 2017 19:27

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