Williams, D. , Heng, I. S. , Gair, J., Clark, J.A. and Khamesra, B. (2020) A precessing numerical relativity waveform surrogate model for binary black holes: a Gaussian process regression approach. Physical Review D, 101, 063011. (doi: 10.1103/PhysRevD.101.063011)
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209978.pdf - Accepted Version 1MB |
Abstract
Gravitational wave astrophysics relies heavily on the use of matched filtering both to detect signals in noisy data from detectors and to perform parameter estimation and tests of general relativity on those signals. Matched filtering relies upon prior knowledge of the signals expected to be produced by a range of astrophysical systems, such as binary black holes. These waveform signals can be computed using numerical relativity techniques, where the Einstein field equations are solved numerically, and the signal is extracted from the simulation. Numerical relativity simulations are, however, computationally expensive, leading to the need for a surrogate model which can predict waveform signals in regions of the physical parameter space which have not been probed directly by simulation. We present a method for producing such a surrogate using Gaussian process regression which is trained directly on waveforms generated by numerical relativity. This model returns not just a single interpolated value for the waveform at a new point, but a full posterior probability distribution on the predicted value. This model is therefore an ideal component in a Bayesian analysis framework, through which the uncertainty in the interpolation can be taken into account when performing parameter estimation of signals.
Item Type: | Articles |
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Additional Information: | BK acknowledges support from NSF awards PHY-1806580, PHY-1809572, and 1333360. This document has been assigned LIGO document reference LIGO-P1800128. |
Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Heng, Professor Ik Siong and Williams, Dr Daniel |
Authors: | Williams, D., Heng, I. S., Gair, J., Clark, J.A., and Khamesra, B. |
College/School: | College of Science and Engineering > School of Physics and Astronomy |
Research Centre: | College of Science and Engineering > School of Physics and Astronomy > Institute for Gravitational Research |
Journal Name: | Physical Review D |
Publisher: | American Physical Society |
ISSN: | 1550-7998 |
ISSN (Online): | 1550-2368 |
Published Online: | 11 March 2020 |
Copyright Holders: | Copyright © 2020 American Physical Society |
First Published: | First published in Physical Review D 101:063011 |
Publisher Policy: | Reproduced in accordance with the publisher copyright policy |
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