English

Measuring gravitational wave memory with LISA

General Relativity and Quantum Cosmology 2024-12-06 v2 Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics

Abstract

Gravitational wave (GW) astronomy has revolutionized our capacity to explore nature. The next generation of observatories, among which the space-borne detector Laser Interferometer Space Antenna LISA, is expected to yield orders of magnitude of signal-to-noise ratio improvement, and reach fainter and novel features of General Relativity. Among them, an exciting possibility is the detection of GW memory. Interpreted as a permanent deformation of the background spacetime after a GW perturbation has passed through the detector, GW memory offers a novel avenue to proof-test General Relativity, access the non-linear nature of gravity, and provide complementary information to better characterize the GW source. Previous studies have shown that GW memory detection from individual mergers of massive black hole binaries is expected with LISA. However, these works have not simulated the proper time domain response of the detector to the GW memory. This work is filling this gap and presents the detection prospects of LISA regarding GW memory and the expected signature of GW memory on the data-streams using the most up-to-date LISA consortium simulations of the response. We focus on the GW memory of massive black hole binary mergers and use state-of-the-art population models to assess the likelihood of detecting the GW memory within the LISA lifetime. We conclude that GW memory will be a key feature of several events detected by LISA, and will help to exploit the scientific potential of the mission fully.

Keywords

Cite

@article{arxiv.2406.09228,
  title  = {Measuring gravitational wave memory with LISA},
  author = {Henri Inchauspé and Silvia Gasparotto and Diego Blas and Lavinia Heisenberg and Jann Zosso and Shubhanshu Tiwari},
  journal= {arXiv preprint arXiv:2406.09228},
  year   = {2024}
}

Comments

19 pages, 15 figures. v2 structure of document and modeling of memory signal revised, with extra clarifications. Main results and conclusions unchanged

R2 v1 2026-06-28T17:04:44.187Z