Year: 2024
Type: article
Abstract: We present an approach to detecting (linear) gravitational wave memory in a Galactic core-collapse supernova using current interferometers. Gravitational wave memory is an important prediction of general relativity that has yet to be confirmed. Our approach uses a combination of linear prediction filtering and matched filtering. We present the results of our approach on data from core-collapse supernova simulations that span a range of progenitor mass and metallicity. We are able to detect gravitational wave memory out to 10 kpc. We also present the false alarm probabilities assuming an on-source window compatible with the presence of a neutrino detection.
Source: Physical Review Letters
Language: English
Subfield: Astronomy and Astrophysics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
Funders: National Science and Technology Council, National Science Foundation, National Research Foundation, Ministry of Education, Culture, Sports, Science and Technology, Academia Sinica, National Research Foundation of Korea, Max-Planck-Gesellschaft, Narodowe Centrum Nauki, Vetenskapsrådet, Centre National de la Recherche Scientifique, Istituto Nazionale di Fisica Nucleare, Ministry of Science and ICT, South Korea, National Science and Technology Council, Science and Technology Facilities Council, Australian Research Council, Japan Society for the Promotion of Science, Instituto Nazionale di Fisica Nucleare
Awards: Core Collapse Supernova Gravitational Wave Signature Predictions based on 3D Ab Initio Models with Increasing GR Realism, LIGO Detector Characterization and Supernova Data Analysis, LIGO Detector Characterization and Supernova Data Analysis, Black Holes from Core-Collapse Supernovae, G7346024287, WoU-MMA: Core Collapse Supernova Gravitational Wave Signature Predictions Based on 3D Models with Increasing GR Realism
OpenAlex ID: W4405072279