The most powerful astrophysical events: Gravitational-wave peak luminosity of binary black holes as predicted by numerical relativity

TL;DR

This paper develops an improved model for the peak gravitational-wave luminosity of binary black hole mergers, based on extensive numerical relativity simulations, enabling better predictions of these powerful astrophysical events.

Contribution

It introduces a highly accurate, comprehensive fit for peak luminosity as a function of black hole masses and spins, covering a wide parameter space and including higher modes and systematic uncertainties.

Findings

Model fit improves accuracy over previous results.

Calibrated with 378 NR simulations up to mass ratio 18.

Includes effects of unequal spins and large mass ratios.

Abstract

For a brief moment, a binary black hole (BBH) merger can be the most powerful astrophysical event in the visible universe. Here we present a model fit for this gravitational-wave peak luminosity of nonprecessing quasicircular BBH systems as a function of the masses and spins of the component black holes, based on numerical relativity (NR) simulations and the hierarchical fitting approach introduced by X. Jim\'enez-Forteza et al. [Phys. Rev. D 95, 064024 (2017), arXiv:1611.00332]. This fit improves over previous results in accuracy and parameter-space coverage and can be used to infer posterior distributions for the peak luminosity of future astrophysical signals like GW150914 and GW151226. The model is calibrated to the l<=6 modes of 378 nonprecessing NR simulations up to mass ratios of 18 and dimensionless spin magnitudes up to 0.995, and includes unequal-spin effects. We also constrain the fit to perturbative numerical results for large mass ratios. Studies of key contributions to the uncertainty in NR peak luminosities, such as (i) mode selection, (ii) finite resolution, (iii) finite extraction radius, and (iv) different methods for converting NR waveforms to luminosity, allow us to use NR simulations from four different codes as a homogeneous calibration set. This study of systematic fits to combined NR and large-mass-ratio data, including higher modes, also paves the way for improved inspiral-merger-ringdown waveform models.