Bayesian inference for gravitational waves from binary neutron star mergers in third generation observatories

Smith, Rory, Borhanian, Ssohrab, Sathyaprakash, Bangalore ORCID: https://orcid.org/0000-0003-3845-7586, Hernandez Vivanco, Francisco, Field, Scott E., Lasky, Paul, Mandel, Ilya, Morisaki, Soichiro, Ottaway, David, Slagmolen, Bram J.?J., Thrane, Eric, Töyrä, Daniel and Vitale, Salvatore 2021. Bayesian inference for gravitational waves from binary neutron star mergers in third generation observatories. Physical Review Letters 127 (8) , 081102. 10.1103/PhysRevLett.127.081102

PDF - Published Version Download (516kB)

Abstract

Third generation (3G) gravitational-wave detectors will observe thousands of coalescing neutron star binaries with unprecedented fidelity. Extracting the highest precision science from these signals is expected to be challenging owing to both high signal-to-noise ratios and long-duration signals. We demonstrate that current Bayesian inference paradigms can be extended to the analysis of binary neutron star signals without breaking the computational bank. We construct reduced-order models for ∼ 90 -min-long gravitational-wave signals covering the observing band (5–2048 Hz), speeding up inference by a factor of ∼ 1.3 × 10 4 compared to the calculation times without reduced-order models. The reduced-order models incorporate key physics including the effects of tidal deformability, amplitude modulation due to Earth’s rotation, and spin-induced orbital precession. We show how reduced-order modeling can accelerate inference on data containing multiple overlapping gravitational-wave signals, and determine the speedup as a function of the number of overlapping signals. Thus, we conclude that Bayesian inference is computationally tractable for the long-lived, overlapping, high signal-to-noise-ratio events present in 3G observatories.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Physics and Astronomy
Publisher:	American Physical Society
ISSN:	0031-9007
Date of First Compliant Deposit:	13 September 2021
Date of Acceptance:	9 July 2021
Last Modified:	11 May 2023 15:49
URI:	https://orca.cardiff.ac.uk/id/eprint/144025

Citation Data

Cited 6 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item