2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012 | 2011 | 2010 | 2009 | 2008

Laying the foundation of the effective-one-body waveform models SEOBNRv5: Improved accuracy and efficiency for spinning nonprecessing binary black holes

Authors: Pompili, L.; Buonanno, A.; Estellés, H.; Khalil, M.; Meent, M.V.; Mihaylov, D.P.; Ossokine, S.; Puerrer, M.; Ramos-Buades, A.; Mehta, A.K.; Cotesta, R.; Marsat, S.; Boyle, M.; Kidder, L.E.; Pfeiffer, H.P.; Scheel, M.A.; Rüter, H.R.; Vu, N.; Dudi, R.; Ma,

Ref.: Phys. Rev. D 108 (12), 124035 (2023)

Abstract: We present SEOBNRv5HM, a more accurate and faster inspiral-merger-ringdown gravitational waveform model for quasicircular, spinning, nonprecessing binary black holes within the effective-one-body (EOB) formalism. Compared to its predecessor, SEOBNRv4HM, the waveform model (i) incorporates recent high-order post-Newtonian results in the inspiral, with improved resummations, (ii) includes the gravitational modes (l, imi) = (3, 2), (4, 3), in addition to the (2,2), (3,3), (2,1), (4,4), (5,5) modes already implemented in SEOBNRv4HM, (iii) is calibrated to larger mass ratios and spins using a catalog of 442 numerical-relativity (NR) simulations and 13 additional waveforms from black-hole perturbation theory, and (iv) incorporates information from second-order gravitational self-force in the nonspinning modes and radiation-reaction force. Computing the unfaithfulness against NR simulations, we find that for the dominant (2,2) mode the maximum unfaithfulness in the total mass range 10-300M circle dot is below 10-3 for 90% of the cases (38% for SEOBNRv4HM). When including all modes up to l = 5 we find 98% (49%) of the cases with unfaithfulness below 10-2 (10-3), while these numbers reduce to 88% (5%) when using SEOBNRv4HM. Furthermore, the model shows improved agreement with NR in other dynamical quantities (e.g., the angular momentum flux and binding energy), providing a powerful check of its physical robustness. We implemented the waveform model in a high-performance Python package (pySEOBNR), which leads to evaluation times faster than SEOBNRv4HM by a factor of 10 to 50, depending on the configuration, and provides the flexibility to easily include spin-precession and eccentric effects, thus making it the starting point for a new generation of EOBNR waveform models (SEOBNRv5) to be employed for upcoming observing runs of the LIGO-Virgo-KAGRA detectors.

DOI: 10.1103/PhysRevD.108.124035