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Physical Review Letters
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Physical Review Letters
Article . 2015 . Peer-reviewed
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https://dx.doi.org/10.48550/ar...
Article . 2015
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Fast and Accurate Prediction of Numerical Relativity Waveforms from Binary Black Hole Coalescences Using Surrogate Models

Authors: Blackman, Jonathan; Field, Scott E.; Galley, Chad R.; Szilágyi, Béla; Scheel, Mark A.; Tiglio, Manuel; Hemberger, Daniel A.;

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

Abstract

Simulating a binary black hole (BBH) 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 non-spinning BBH 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 {\em 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 ${}_{-2}Y_{\ell m}$ waveform modes resolved by the NR code up to $\ell=8.$ We compare our surrogate model to Effective One Body waveforms from $50$-$300 M_\odot$ for advanced LIGO detectors and find that the surrogate is always more faithful (by at least an order of magnitude in most cases).

Updated to published version, which includes a section comparing the surrogate and effective-one-body models. The surrogate is publicly available for download at http://www.black-holes.org/surrogates/ . 6 pages, 6 figures

Country
United States
Keywords

High Energy Astrophysical Phenomena (astro-ph.HE), FOS: Computer and information sciences, FOS: Physical sciences, General Relativity and Quantum Cosmology (gr-qc), 530, General Relativity and Quantum Cosmology, 510, Computational Engineering, Finance, and Science (cs.CE), Physics - Data Analysis, Statistics and Probability, Astrophysics - High Energy Astrophysical Phenomena, Computer Science - Computational Engineering, Finance, and Science, Data Analysis, Statistics and Probability (physics.data-an)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
128
Top 1%
Top 10%
Top 1%
Green
hybrid