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Published November 15, 2015 | Published + Submitted
Journal Article Open

Accuracy and precision of gravitational-wave models of inspiraling neutron star-black hole binaries with spin: Comparison with matter-free numerical relativity in the low-frequency regime

Abstract

Coalescing binaries of neutron stars and black holes are one of the most important sources of gravitational waves for the upcoming network of ground-based detectors. Detection and extraction of astrophysical information from gravitational-wave signals requires accurate waveform models. The effective-one-body and other phenomenological models interpolate between analytic results and numerical relativity simulations, that typically span O(10) orbits before coalescence. In this paper we study the faithfulness of these models for neutron star-black hole binaries. We investigate their accuracy using new numerical relativity (NR) simulations that span 36–88 orbits, with mass ratios q and black hole spins χ_(BH) of (q,χ_(BH))=(7,±0.4),(7,±0.6), and (5,−0.9). These simulations were performed treating the neutron star as a low-mass black hole, ignoring its matter effects. We find that (i) the recently published SEOBNRv1 and SEOBNRv2 models of the effective-one-body family disagree with each other (mismatches of a few percent) for black hole spins χ_(BH)≥0.5 or χ_(BH)≤−0.3, with waveform mismatch accumulating during early inspiral; (ii) comparison with numerical waveforms indicates that this disagreement is due to phasing errors of SEOBNRv1, with SEOBNRv2 in good agreement with all of our simulations; (iii) phenomenological waveforms agree with SEOBNRv2 only for comparable-mass low-spin binaries, with overlaps below 0.7 elsewhere in the neutron star-black hole binary parameter space; (iv) comparison with numerical waveforms shows that most of this model's dephasing accumulates near the frequency interval where it switches to a phenomenological phasing prescription; and finally (v) both SEOBNR and post-Newtonian models are effectual for neutron star-black hole systems, but post-Newtonian waveforms will give a significant bias in parameter recovery. Our results suggest that future gravitational-wave detection searches and parameter estimation efforts would benefit from using SEOBNRv2 waveform templates when focused on neutron star-black hole systems with q≲7 and χ_(BH)≈[−0.9,+0.6]. For larger black hole spins and/or binary mass ratios, we recommend the models be further investigated as NR simulations in that region of the parameter space become available.

Additional Information

© 2015 American Physical Society. Received 1 July 2015; published 4 November 2015. We thank the Gravitational-Wave group at Syracuse University for productive discussions. D. A. B. and P. K. are grateful for hospitality of the Theoretical AstroPhysics Including Relativity and Cosmology (TAPIR) group at the California Institute of Technology, where part of this work was completed. P. K. acknowledges support through the Ontario Early Research Award Program and the Canadian Institute for Advanced Research. D. A. B. and S. B. are supported by National Science Foundation (NSF) Awards No. PHY-1404395 and No. AST-1333142; N. A. and G. L. are supported by NSF Award No. PHY-1307489 and by the Research Corporation for Science Advancement. K. B., M. S., and B. Sz. are supported by the Sherman Fairchild Foundation and by NSF Grants No. PHY-1440083 and No. AST-1333520 at Caltech. Simulations used in this work were performed with the SpEC code [52]. Calculations were performed on the Zwicky cluster at Caltech, which is supported by the Sherman Fairchild Foundation and by NSF Award No. PHY-0960291; on the NSF XSEDE network under Grant No. TG-PHY990007N; on the Syracuse University Gravitation and Relativity cluster, which is supported by NSF Awards No. PHY-1040231 and No. PHY-1104371 and Syracuse University ITS; on the Orca cluster supported by NSF Award No. PHY-1429873, the Research Corporation for Science Advancement, and by California State University Fullerton; and on the GPC supercomputer at the SciNet HPC Consortium [97]. SciNet is funded by the Canada Foundation for Innovation under the auspices of Compute Canada, the Government of Ontario, Ontario Research Fund–Research Excellence, and the University of Toronto.

Attached Files

Published - PhysRevD.92.102001.pdf

Submitted - 1507.00103v1.pdf

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Additional details

Created:
August 20, 2023
Modified:
October 25, 2023