Flexible mapping of ringdown amplitudes for nonprecessing binary black holes

TL;DR

This paper introduces a highly accurate, flexible surrogate model for ringdown amplitudes and phases of nonprecessing binary black holes, improving gravitational wave analysis and enabling future extensions to more complex systems.

Contribution

A novel data-driven surrogate model for ringdown amplitudes and phases that includes multiple modes and overtones, with significantly reduced errors and adaptable to future complexities.

Findings

Achieves reconstruction errors ~100 times smaller than measurement errors

Includes 16 emission modes with overtones and quadratic contributions

Flexible framework allows future extensions to eccentricity and precession

Abstract

The remnant black hole from a binary coalescence emits ringdown gravitational waves characterized by quasinormal modes, which depend solely on the remnant's mass and spin. In contrast, the ringdown amplitudes and phases are determined by the properties of the merging progenitors. Accurately modeling these amplitudes and phases reduces systematic biases in parameter estimation and enables the development and performance of rigorous tests of general relativity. We present a state-of-the-art, data-driven surrogate model for ringdown amplitudes and phases, leveraging Gaussian process regression trained against SXS numerical-relativity simulations. Focusing on nonprecessing, quasicircular binary black holes, our model offers the most comprehensive fit that includes 16 emission modes, incorporating overtones and quadratic contributions. Our surrogate model achieves reconstruction errors that are approximately 2 orders of magnitude smaller than the typical measurement errors of current gravitational-wave interferometers. An additional benefit of our approach is its flexibility, which allows for future extensions to include features such as eccentricity and precession, broadening the scope of its applicability to more generic astrophysical scenarios. Finally, we are releasing our model in a ready-to-use package called postmerger.