Comparative study of 1D and 2D convolutional neural network models with attribution analysis for gravitational wave detection from compact binary coalescences-Reference-Cited by-同舟云学术

Comparative study of 1D and 2D convolutional neural network models with attribution analysis for gravitational wave detection from compact binary coalescences

Published:2024-02-07 Issue:4 Volume:109 Page:
ISSN:2470-0010
Container-title:Physical Review D
language:en
Short-container-title:Phys. Rev. D

Author:

Sasaoka Seiya^ORCID,Koyama Naoki^ORCID,Dominguez Diego^ORCID,Sakai Yusuke,Somiya Kentaro,Omae Yuto^ORCID,Takahashi Hirotaka^ORCID

Funder

Japan Society for the Promotion of Science

University of Tokyo

National Science Foundation

Science and Technology Facilities Council

Max-Planck-Gesellschaft

Australian Research Council

Centre National de la Recherche Scientifique

Instituto Nazionale di Fisica Nucleare

Ministry of Education, Culture, Sports, Science and Technology

National Research Foundation of Korea

Ministry of Science and ICT, South Korea

Academia Sinica

National Science and Technology Council

Tokyo City University

European Gravitational Observatory

Publisher

American Physical Society (APS)

Link

http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevD.109.043011/fulltext

Reference69 articles.

1. Advanced LIGO

2. Observation of Gravitational Waves from a Binary Black Hole Merger

3. Advanced Virgo: a second-generation interferometric gravitational wave detector

4. Multi-messenger Observations of a Binary Neutron Star Merger

5. GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs

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