Gravitational-wave memory: waveforms and phenomenology

TL;DR

This paper develops a method to compute gravitational-wave memory waveforms, explores the phenomenology including higher modes and memory effects, and provides a publicly available Python package for these calculations.

Contribution

It introduces a new method for calculating gravitational-wave memory from oscillatory signals, incorporating higher modes and the memory of the memory, with implementation in an accessible software package.

Findings

Higher-order modes contribute to richer memory phenomenology.

The 'memory of the memory' effect introduces small corrections to waveforms.

The method is validated using a numerical relativity surrogate model.

Abstract

The non-linear gravitational-wave memory effect is a prediction of general relativity in which test masses are permanently displaced by gravitational radiation. We implement a method for calculating the expected memory waveform from an oscillatory gravitational-wave time series. We use this method to explore the phenomenology of gravitational-wave memory using a numerical relativity surrogate model. Previous methods of calculating the memory have considered only the dominant oscillatory ($\ell=2$, $m=|2|$) mode in the spherical harmonic decomposition or the post-Newtonian expansion. We explore the contribution of higher-order modes and reveal a richer phenomenology than is apparent with $\ell=|m|=2$ modes alone. We also consider the `memory of the memory' in which the memory is, itself, a source of memory, which leads to a small, $O\left(10^{-4}\right)$, correction to the memory waveform. The method is implemented in the python package {\tt\sc GWMemory}, which is made publicly available.