High-Precision Ringdown Surrogate Model for Non-Precessing Binary Black Holes

TL;DR

This paper introduces a highly accurate, spin-aligned surrogate model for black hole ringdowns, enabling precise tests of general relativity by predicting complex QNM amplitudes with minimal errors.

Contribution

The novel contribution is the development of NRSur3dq8_RD, a surrogate model that accurately predicts complex QNM amplitudes and remnant black hole properties using numerical waveforms.

Findings

Median relative errors of $10^{-2}-10^{-3}$ in QNM amplitudes.

Median errors of $10^{-4}$ in ringdown waveforms.

Model is publicly available via the surfinBH Python package.

Abstract

Highly precise and robust waveform models are required as improvements in detector sensitivity enable us to test general relativity with more precision than ever before. In this work, we introduce a spin-aligned surrogate ringdown model. This ringdown surrogate, NRSur3dq8_RD, is built with numerical waveforms produced using Cauchy-characteristic evolution. In addition, these waveforms are in the superrest frame of the remnant black hole allowing us to do a correct analysis of the ringdown spectrum. The novel prediction of our surrogate model is complex-valued quasinormal mode (QNM) amplitudes, with median relative errors of $10^{-2}-10^{-3}$ over the parameter space. Like previous remnant surrogates, we also predict the remnant black hole's mass and spin. The QNM mode amplitude errors translate into median errors on ringdown waveforms of $10^{-4}$. The high accuracy and QNM mode content provided by our surrogate will enable high-precision ringdown analyses such as tests of general relativity. Our ringdown model is publicly available through the python package surfinBH.