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Re-analyzing GWTC-3 events with a numerical relativity surrogate waveform model

ORAL

Abstract

The third Gravitational-wave Transient Catalog (GWTC-3) presents a total of 90 signals detected by LIGO-Virgo Collaboration (LVC) up to the end of their third observing run. The source properties of most of the binary black holes (BBH) events have been inferred using either Numerical Relativity (NR) tuned phenomenological waveform models or NR tuned effective one-body (EOB) waveforms. We provide a re-analysis of these BBH events using a precessing numerical-relativity surrogate model, NRSur7dq4. This model is the most accurate waveform model when the analysis is restricted to the NRSur7dq4's training domain. Due to the shorter length of NRSur7dq4 waveforms, we restrict our analysis only for events that have a total mass of greater than 60 solar mass in the detector frame and mass ratios smaller than 6. While for most of the events, inferred source properties using NRSur7dq4 matches with Phenom and EOB results, we do find a handful events where NRSur7dq4 model provides tighter constrained measurements of masses and spins of the black holes, and narrower sky localization. For these events, NRSur7dq4 also recovers higher signal-to-noise ratio when compared against other models. We finally discuss the astrophysical implication of our results.

Presenters

  • Tousif Islam

    University of Massachusetts Dartmouth

Authors

  • Tousif Islam

    University of Massachusetts Dartmouth

  • Feroz H Shaik

    University of Massachusetts Dartmouth

  • Carl-Johan O Haster

    Massachusetts Institute of Technology MIT, Massachusetts Institute of Technology MI

  • Vijay Varma

    Cornell University

  • Scott E Field

    University of Massachusetts Dartmouth

  • Jacob A Lange

    University of Texas at Austin

  • Richard O’Shaughnessy

    RIT, Center for Computational Relativity and Gravitation,Rochester Institute of Technology, Rochester, New York 14623, USA

  • Rory Smith

    Monash University

  • Avi Vajpeyi

    Monash University