Gravitational memory in binary black hole mergers

TL;DR

This paper investigates the nonlinear gravitational wave memory effect in binary black hole mergers using numerical simulations, revealing its growth during late inspiral and merger, and assessing its detectability with current and future detectors.

Contribution

It provides the first detailed numerical evaluation of the nonlinear memory during black hole mergers, highlighting its dependence on black hole spins and implications for detection.

Findings

Memory grows significantly during late inspiral and merger.

Ringdown is most prominent for low-spin models.

Maximal spin black holes produce the largest memory offset.

Abstract

In addition to the dominant oscillatory gravitational wave signals produced during binary inspirals, a non-oscillatory component arises from the nonlinear "memory" effect, sourced by the emitted gravitational radiation. The memory grows significantly during the late inspiral and merger, modifying the signal by an almost step-function profile, and making it difficult to model by approximate methods. We use numerical evolutions of binary black holes to evaluate the nonlinear memory during late-inspiral, merger and ringdown. We identify two main components of the signal: the monotonically growing portion corresponding to the memory, and an oscillatory part which sets in roughly at the time of merger and is due to the black hole ringdown. Counter-intuitively, the ringdown is most prominent for models with the lowest total spin. Thus, the case of maximally spinning black holes anti-aligned to the orbital angular momentum exhibits the highest signal-to-noise (SNR) for interferometric detectors. The largest memory offset, however, occurs for highly spinning black holes, with an estimated value of h^tot_20 \approx 0.24 in the maximally spinning case. These results are central to determining the detectability of nonlinear memory through pulsar timing array measurements.