A Novel Method for Placement of Numerical Relativity Simulations Informed by NR-based Parameter Estimation
ORAL
Abstract
On the 21st of May 2019, the LIGO-Virgo-KAGRA Collaboration detected a gravitational wave signal from a massive, highly precessing binary black hole merger. While all the analyses with different gravitation wave models recovered similar parameters, the peaks of the posterior distributions were noticeably different for models that include different physics. In this work, we present results for GW190521 from a method that suggests new numerical relativity simulations based on a parameter estimation analysis using only numerical relativity waveforms. This method attempts to place new simulations by taking into account the part of parameter space relevant for a given event as well as the sparse part of parameter space in the existing numerical relativity grid. We then add these new simulations into the NR-based analysis and quantify the impact of these targeted simulations by assessing the change in the posterior.
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Presenters
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Jacob A Lange
University of Texas at Austin
Authors
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Jacob A Lange
University of Texas at Austin
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Michael Boyle
Cornell University
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Manuela Campanelli
Rochester Institute of Technology
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Andrea Ceja
California State University, Fullerton
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Deborah Ferguson
University of Texas at Austin
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James Healy
Rochester Institute of Technology
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Hector L Iglesias
University of Texas at Austin
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Aasim Z Jan
University of Texas at Austin
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Lawrence E Kidder
Cornell University
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Pablo Laguna
University of Texas at Austin
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Carlos O Lousto
Rochester Institute of Technology
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Geoffrey Lovelace
California State University, Fullerton
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Erick Martinez
University of Texas at Austin
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Ryan Nowicki
University of Texas at Austin
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Richard O'Shaughnessy
Rochester Institute of Technology
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Harald P Pfeiffer
Max Planck Inst, Max Planck Institute for Gravitational Physics
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Mark A Scheel
Caltech
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Deirdre M Shoemaker
University of Texas at Austin
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Daniel Tellez
California State University, Fullerton
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Saul A Teukolsky
Cornell University
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Yosef Zlochower
Rochester Institute of Technology