The final twist: A model of gravitational waves from precessing black-hole binaries through merger and ringdown

TL;DR

This paper introduces PhenomPNR, a new frequency-domain model for gravitational waves from precessing black-hole binaries, fully calibrated to numerical relativity simulations, improving accuracy in waveform modeling through merger and ringdown phases.

Contribution

It presents the first NR-tuned model of precession dynamics through merger and ringdown, extending existing aligned-spin models to include misaligned spin effects.

Findings

Achieves mismatch accuracy within 0.1% up to mass ratio 1:4.

Achieves mismatch accuracy within 1% up to mass ratio 1:8.

Calibrated on 40 NR simulations with various mass ratios and spin misalignments.

Abstract

We present PhenomPNR, a frequency-domain phenomenological model of the gravitational-wave (GW) signal from binary-black-hole mergers that is tuned to numerical relativity (NR) simulations of precessing binaries. In many current waveform models, e.g., the "Phenom" and "EOBNR" families that have been used extensively to analyse LIGO-Virgo GW observations, analytic approximations are used to add precession effects to models of non-precessing (aligned-spin) binaries, and it is only the aligned-spin models that are fully tuned to NR results. In PhenomPNR we incorporate precessing-binary NR results in two ways: (i) we produce the first NR-tuned model of the signal-based precession dynamics through merger and ringdown, and (ii) we extend a previous aligned-spin model, PhenomD, to include the effects of misaligned spins on the signal in the co-precessing frame. The NR calibration has been performed on 40 simulations of binaries with mass ratios between 1:1 and 1:8, where the larger black hole has a dimensionless spin magnitude of 0.4 or 0.8, and we choose five angles of spin misalignment with the orbital angular momentum. PhenomPNR has a typical mismatch accuracy within 0.1% up to mass-ratio 1:4, and within 1% up to mass-ratio 1:8.