Dilated convolutional neural network for detecting extreme-mass-ratio inspirals-Reference-Cited by-同舟云学术

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Dilated convolutional neural network for detecting extreme-mass-ratio inspirals

Published:2024-04-23 Issue:8 Volume:109 Page:
ISSN:2470-0010
Container-title:Physical Review D
language:en
Short-container-title:Phys. Rev. D

Author:

Zhao Tianyu¹²³^ORCID,Zhou Yue²^ORCID,Shi Ruijun¹³^ORCID,Cao Zhoujian¹³⁴^ORCID,Ren Zhixiang²^ORCID

Affiliation:

1. Department of Astronomy, Beijing Normal University, Beijing 100875, China

2. Peng Cheng Laboratory, Shenzhen, 518055, China

3. Institute for Frontiers in Astronomy and Astrophysics, Beijing Normal University, Beijing 102206, China

4. School of Fundamental Physics and Mathematical Sciences, Hangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China

Funder

Peng Cheng Laboratory

National Key Research and Development Program of China

National Natural Science Foundation of China

Beijing Normal University

Chinese Academy of Sciences

Publisher

American Physical Society (APS)

Link

http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevD.109.084054/fulltext

Reference60 articles.

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

2. Advanced LIGO

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

4. Tests of General Relativity with GW150914

5. Gravitational-wave physics and astronomy in the 2020s and 2030s

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1. Premerger detection of massive black hole binaries using deep learning;Physical Review D;2024-06-24

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