Fast prediction and evaluation of eccentric inspirals using reduced-order models

Dániel Barta and Mátyás Vasúth
Phys. Rev. D 97, 124011 – Published 7 June 2018

Abstract

A large number of theoretically predicted waveforms are required by matched-filtering searches for the gravitational-wave signals produced by compact binary coalescence. In order to substantially alleviate the computational burden in gravitational-wave searches and parameter estimation without degrading the signal detectability, we propose a novel reduced-order-model (ROM) approach with applications to adiabatic 3PN-accurate inspiral waveforms of nonspinning sources that evolve on either highly or slightly eccentric orbits. We provide a singular-value decomposition-based reduced-basis method in the frequency domain to generate reduced-order approximations of any gravitational waves with acceptable accuracy and precision within the parameter range of the model. We construct efficient reduced bases comprised of a relatively small number of the most relevant waveforms over three-dimensional parameter-space covered by the template bank (total mass 2.15MM215M, mass ratio 0.01q1, and initial orbital eccentricity 0e00.95). The ROM is designed to predict signals in the frequency band from 10 Hz to 2 kHz for aLIGO and aVirgo design sensitivity. Beside moderating the data reduction, finer sampling of fiducial templates improves the accuracy of surrogates. Considerable increase in the speedup from several hundreds to thousands can be achieved by evaluating surrogates for low-mass systems especially when combined with high-eccentricity.

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  • Received 2 March 2018

DOI:https://doi.org/10.1103/PhysRevD.97.124011

© 2018 American Physical Society

Physics Subject Headings (PhySH)

Gravitation, Cosmology & Astrophysics

Authors & Affiliations

Dániel Barta* and Mátyás Vasúth

  • Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Hungarian Academy of Sciences, Konkoly-Thege Miklós út 29-33, H-1121 Budapest, Hungary

  • *barta.daniel@wigner.mta.hu
  • vasuth.matyas@wigner.mta.hu

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Vol. 97, Iss. 12 — 15 June 2018

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