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Detection and parameter estimation of binary neutron star merger remnants

Easter, Paul J. and Ghonge, Sudarshan and Lasky, Paul D. and Casey, Andrew R. and Clark, James A. and Hernandez Vivanco, Francisco and Chatziioannou, Katerina (2020) Detection and parameter estimation of binary neutron star merger remnants. Physical Review D, 102 (4). Art. No. 043011. ISSN 2470-0010. doi:10.1103/PhysRevD.102.043011.

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Detection and parameter estimation of binary neutron star merger remnants can shed light on the physics of hot matter at supranuclear densities. Here we develop a fast, simple model that can generate gravitational waveforms, and show it can be used for both detection and parameter estimation of postmerger remnants. The model consists of three exponentially damped sinusoids with a linear frequency-drift term. We test the model against nine equal-mass numerical-relativity simulations selected for emission of gravitational waves for ≳25  ms. The median fitting factors between the model waveforms and numerical-relativity simulations exceed 0.90. We detect remnants at a postmerger signal-to-noise ratio of ≥7 using a Bayes-factor detection statistic with a threshold of 3000. We can constrain the primary postmerger frequency to ±^(1.4)_(1.2)% at postmerger signal-to-noise ratios of 15 with an increase in precision to ±^(0.3)_(0.2)% for postmerger signal-to-noise ratios of 50. The tidal coupling constant can be constrained to ±⁹₁₂% at postmerger signal-to-noise ratios of 15, and ±5% at postmerger signal-to-noise ratios of 50 using a hierarchical inference model.

Item Type:Article
Related URLs:
URLURL TypeDescription Paper
Easter, Paul J.0000-0003-2212-9051
Lasky, Paul D.0000-0003-3763-1386
Casey, Andrew R.0000-0003-0174-0564
Hernandez Vivanco, Francisco0000-0002-1942-7608
Chatziioannou, Katerina0000-0002-5833-413X
Additional Information:© 2020 American Physical Society. Received 8 June 2020; accepted 27 July 2020; published 14 August 2020. P. D. L. is supported through Australian Research Council (ARC) Future Fellowship No. FT160100112, ARC Discovery Project No. DP180103155, and ARC Centre of Excellence No. CE170100004. A. R. C. is supported by ARC Grant No. DE190100656. S. G. and J. A. C. gratefully acknowledge the NSF for financial support from Grants No. PHY 1806580, No. PHY 1809572, and No. TG-PHY120016. The Flatiron Institute is supported by the Simons Foundation. This research has made use of data, software and/or web tools obtained from the Gravitational Wave Open Science Center [54], a service of LIGO Laboratory, the LIGO Scientific Collaboration and the Virgo Collaboration. LIGO is funded by the U.S. National Science Foundation. Virgo is funded by the French Centre National de Recherche Scientifique (CNRS), the Italian Istituto Nazionale della Fisica Nucleare (INFN) and the Dutch Nikhef, with contributions by Polish and Hungarian institutes. The authors are grateful for computational resources provided by the LIGO Laboratory and supported by National Science Foundation Grants No. PHY-0757058 and No. PHY-0823459. This research was done using resources provided by the Open Science Grid [55,56], which is supported by the National Science Foundation Award No. 1148698, and the U.S. Department of Energy’s Office of Science. We are grateful to Sukanta Bose for valuable comments on the manuscript.
Funding AgencyGrant Number
Australian Research CouncilFT160100112
Australian Research CouncilDP180103155
Australian Research CouncilCE170100004
Australian Research CouncilDE190100656
Simons FoundationUNSPECIFIED
Centre National de la Recherche Scientifique (CNRS)UNSPECIFIED
Istituto Nazionale di Fisica Nucleare (INFN)UNSPECIFIED
Department of Energy (DOE)UNSPECIFIED
Issue or Number:4
Record Number:CaltechAUTHORS:20200731-150337553
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:104687
Deposited By: Tony Diaz
Deposited On:31 Jul 2020 22:39
Last Modified:16 Nov 2021 18:34

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