LIGO Document P2000140-v4
- As gravitational-wave detectors become more sensitive and broaden their frequency bandwidth, we will access a greater variety of signals emitted by compact binary systems, shedding light on their astrophysical origin and environment. A key physical effect that can distinguish among different
formation scenarios is the misalignment of the spins with the orbital angular momentum, causing the spins and the binary's orbital plane to precess. To accurately model such precessing signals, especially when masses and spins vary in the wide astrophysical range, it is crucial to include multipoles beyond the dominant quadrupole. Here, we develop the first {\it multipolar} precessing waveform model in the effective-one-body (EOB) formalism for the entire coalescence stage (i.e., inspiral, merger and ringdown) of binary black holes: SEOBNRv4PHM. In the nonprecessing limit, the model reduces to SEOBNRv4HM, which was calibrated to numerical-relativity (NR) simulations, and waveforms from black-hole perturbation theory. We validate the SEOBNRv4PHM by comparing it to the public catalog of 1405 precessing NR waveforms of the Simulating eXtreme Spacetimes (SXS) collaboration, and also to 118 SXS precessing NR waveforms, produced as part of this project, which span mass ratios 1-4 and (dimensionless) black-hole's spins up to 0.9. We stress that SEOBNRv4PHM is not calibrated to NR simulations in the precessing sector. We compute the unfaithfulness against the 1523 SXS precessing NR waveforms, and found that, for 94% (57% ) of the cases, the maximum value, in the total mass range 20 -200 \( M_\odot \), is below \( 3\% \) (\( 1\% \)). Those numbers change to 83% (20%) when using the inspiral-merger-ringdown, multipolar, precessing phenomenological model IMRPhenomPv3HM. We investigate the impact of such unfaithfulness values with two Bayesian, parameter-estimation studies on synthetic signals. We also compute the unfaithfulness between those waveform models as function of the mass and spin parameters to identify in which part of the parameter space they differ the most. We validate them also against the multipolar, precessing NR surrogate model NRSur7dq4, and find that the SEOBNRv4PHM model outperforms IMRPhenomPv3HM.
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