Universal phenomenological relations between spherical harmonic modes in non-precessing eccentric binary black hole merger waveforms

TL;DR

This paper extends phenomenological relations between spherical harmonic modes in non-precessing eccentric binary black hole mergers to a broader set of simulations, enabling efficient waveform modeling and noise filtering.

Contribution

It introduces a framework called gwNRXHME that uses these relations to generate multi-modal eccentric waveforms from limited inputs, applicable to a wide range of non-precessing binaries.

Findings

Relations hold across multiple NR catalogs with varying mass ratios.

SXS simulations adhere more closely to the relations than RIT and MAYA.

Relations can be used to filter noisy higher-order modes effectively.

Abstract

Using publicly available numerical relativity (NR) simulations for non-spinning eccentric binary black hole (BBH) mergers, Ref \cite{Islam:2024rhm} demonstrated that the eccentricity-induced modulations in the amplitudes and frequencies of different spherical harmonic modes are mutually consistent and can be modeled using a single time series modulation. We extend the validity of the results to all non-precessing binaries by using 83 NR simulations from the SXS, RIT, and MAYA catalogs for aligned-spin eccentric BBH mergers with mass ratios ranging from $1:1$ to $1:4$. Based on these phenomenological relations, we provide a framework named gwNRXHME to compute multi-modal eccentric non-precessing waveforms using two inputs: quadrupolar eccentric waveforms, and the corresponding multi-modal quasi-circular non-precessing waveforms. Furthermore, we compute an overall degree of departure in SXS, RIT, and MAYA NR data from these relations and find that SXS NR simulations generally adhere to these relations more strictly than RIT and MAYA data. We also show that these relations can offer a cost-effective way to filter out noisy higher-order spherical harmonic modes extracted from NR data. Our framework is publicly available through the gwModels package.