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Published November 15, 2020 | Published + Submitted
Journal Article Open

Gravitational wave peak luminosity model for precessing binary black holes

Abstract

When two black holes merge, a tremendous amount of energy is released in the form of gravitational radiation in a short span of time, making such events among the most luminous phenomenon in the Universe. Models that predict the peak luminosity of black hole mergers are of interest to the gravitational wave community, with potential applications in tests of general relativity. We present a surrogate model for the peak luminosity that is directly trained on numerical relativity simulations of precessing binary black holes. Using Gaussian process regression, we interpolate the peak luminosity in the seven-dimensional parameter space of precessing binaries with mass ratios q ≤ 4 and spin magnitudes χ₁, χ₂ ≤ 0.8. We demonstrate that our errors in estimating the peak luminosity are lower than those of existing fitting formulas by about an order of magnitude. In addition, we construct a model for the peak luminosity of aligned-spin binaries with mass ratios q ≤ 8 and spin magnitudes |χ₁_z|,|χ₂_z| ≤ 0.8. We apply our precessing model to infer the peak luminosity of the GW event GW190521 and find the results to be consistent with previous predictions.

Additional Information

© 2020 American Physical Society. Received 1 October 2020; accepted 27 October 2020; published 18 November 2020. We thank Scott Field, Leo Stein, and Carl-Johan Haster for useful comments. A. T. gratefully acknowledges the support of the United States National Science Foundation for the construction and operation of the LIGO Laboratory and Advanced LIGO, the LIGO Laboratory NSF Research Experience for Undergraduates program, and the Carl A. Rouse Family. V. V. is generously supported by a Klarman Fellowship at Cornell, the Sherman Fairchild Foundation, and NSF Grants No. PHY–170212 and No. PHY–1708213 at Caltech.

Attached Files

Published - PhysRevD.102.104047.pdf

Submitted - 2010.00120.pdf

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