On Stochastic Memory Backgrounds In LISA

Abstract

Gravitational-wave (GW) memory is a permanent change in spacetime geometry induced by a burst of gravitational waves. It is theoretically interesting for its connection to asymptotic symmetries, but has not yet been observed. The upcoming Laser Interferometer Space Antenna (LISA) is predicted to detect memory directly in loud events from supermassive black hole (SMBH) mergers. We assess the prospects for the cumulative effect of memory contributions as a stochastic GW memory background (SGWMB). Using two SMBH population models, we recover previously obtained single-event SNR forecasts and compute the power spectrum of the unresolved background, using numerical-relativity waveforms for modeling the memory signal during each event. We find the predicted spectrum is significantly smaller than ones found by modeling the memory waveform with a Heaviside function, with expected SNRs of order $O(0.1-10)$. We further find that our models favor a highly non-Gaussian ("popcorn") spectrum, demonstrating that the background may not appear as the union of continuous, overlapping signals, but rather as a collection of intermittent bursts. In both measures, we demonstrate that any current prediction of the spectrum is heavily dependent on the choice of population model. We interpret these findings in the light of the future LISA mission and emphasize their importance for properly handling memory within the LISA global fit.