Adding equatorial-asymmetric effects for spin-precessing binaries into the SEOBNRv5PHM waveform model

TL;DR

This paper enhances the SEOBNRv5PHM gravitational waveform model by incorporating equatorial asymmetric effects in spin-precessing binaries, significantly improving accuracy in waveform prediction and recoil velocity estimation.

Contribution

The paper introduces SEOBNRv5PHM_w/asym, a new model that includes equatorial asymmetric contributions, calibrated against extensive numerical relativity data, for better modeling of spin-precessing binary systems.

Findings

Improved waveform agreement with numerical relativity across inclinations.

Reduced median unfaithfulness by up to 50% compared to previous models.

Significantly better recoil velocity predictions, with median error dropping from 70% to 1%.

Abstract

Gravitational waves from spin-precessing binaries exhibit equatorial asymmetries absent in non-precessing systems, leading to net linear momentum emission and contributing to the remnant's recoil. This effect, recently incorporated into only a few waveform models, is crucial for accurate recoil predictions and improved parameter estimation. We present an upgrade to the SEOBNRv5PHM model -- SEOBNRv5PHM_w/asym -- which includes equatorial asymmetric contributions to the l=m<=4 waveform modes in the co-precessing frame. The model combines post-Newtonian inputs with calibrated amplitude and phase corrections and a phenomenological merger-ringdown description, tuned against 1523 quasi-circular spin-precessing numerical relativity waveforms and single-spin precessing test-body plunging-geodesic waveforms. We find that SEOBNRv5PHM_w/asym improves the agreement with NR waveforms across inclinations, with median unfaithfulness reduced by up to 50% compared to SEOBNRv5PHM, and achieves 30-60% lower unfaithfulness than IMRPhenomXPNR and 76-80% lower than TEOBResumS_Dali. The model significantly improves the prediction of the recoil velocity, reducing the median relative error with numerical relativity from 70% to 1%. Bayesian inference on synthetic injections demonstrates improved recovery of spin orientations and mass parameters, and a reanalysis of GW200129 shows a threefold increase in the spin-precessing Bayes factor, highlighting the importance of these effects for interpreting spin-precessing events.