Detecting regular precession using a new gravitational waveform model directly parameterized by both precession amplitude and frequency
Abstract
Nearly 210 binary black hole (BBH) mergers have been observed by the LIGO-Virgo-KAGRA network during its four observing runs. Generic BBHs are spinning, and their spins are misaligned with the orbital angular momentum . These misaligned spins cause to precess in a cone with dimensionless precession amplitude and frequency about the nearly constant direction of the total angular momentum. This precession modulates the observed GWs. We propose a model of regularly precessing (RP) waveforms that incorporates and directly as parameters. We investigate how these waveforms vary as functions of these precessional parameters, as well as binary orientation and sky location. We use the Lindblom criterion to estimate that precession can be detected in a RP source with signal-to-noise ratio when the mismatch with a non-precessing (NP) source with otherwise identical parameters exceeds . Precession is most detectable when precesses through configurations we call +~nulls during the inspiral. At +~nulls, a NP source only emits +-polarization to which the GW detector is insensitive. The large mismatch between a RP source and this vanishing NP signal enhances the detectability of precession. We also explore the detectability of precession as a function of redshift for different BBH populations. We find that for BBHs with isotropically oriented maximal spins, precession is detectable in a majority of systems out to for chirp masses and mass ratios . Reduced spin magnitudes or greater alignment between the spins and make it difficult to observe beyond . (abridged)
Cite
@article{arxiv.2509.10628,
title = {Detecting regular precession using a new gravitational waveform model directly parameterized by both precession amplitude and frequency},
author = {Tamanjyot Singh and Evangelos Stoikos and Saif Ali and Nathan Steinle and Michael Kesden and Lindsay King},
journal= {arXiv preprint arXiv:2509.10628},
year = {2025}
}
Comments
26 pages, 11 figures, submitted to PRD, codes are available at https://github.com/singhtaman/regular_precession/