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J-GLOBAL ID：201902213410763392   Reference number：19A2285981

Denoising weak lensing mass maps with deep learning

深い学習による弱レンズ効果質量マップの雑音除去【JST・京大機械翻訳】

Author (6)： Shirasaki Masato (National Astronomical Observatory of Japan (NAOJ), Mitaka, Tokyo 181-8588, Japan) ,  Yoshida Naoki (Department of Physics, University of Tokyo, Tokyo 113-0033, Japan) ,  Yoshida Naoki (Kavli Institute for the Physics and Mathematics of the Universe (WPI), University of Tokyo, Kashiwa, Chiba 277-8583, Japan) ,  Yoshida Naoki (Institute for Physics of Intelligence, University of Tokyo, Tokyo 113-0033, Japan) ,  Ikeda Shiro (The Institute of Statistical Mathematics, 10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan) ,  Ikeda Shiro (Department of Statistical Science, Graduate University for Advanced Studies, 10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan)
Material： Physical Review. D  (Physical Review. D. Covering Particles, Fields, Gravitation, and Cosmology)
Volume： 100  Issue： 4  Page： 043527  Publication year： 2019 
JST Material Number： D0748A  ISSN： 2470-0010  CODEN： PRVDAQ  Document type： Article
Article type： 原著論文  Country of issue： United States (USA)  Language： ENGLISH (EN)

Abstract/Point： Weak gravitational lensing is ...

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Thesaurus term： network ,  *noise elimination ,  simulation ,  perturbation ,  *noise(signal) ,  outer space ,  *learning ,  bias ,  curvature ,  cosmology ,  *lens(optics) ,  image ,  derivative ,  probe
Semi thesaurus term： 弱い重力レンズ , 【Automatic Indexing@JST】

JST classification (2)： Experimental tests and observations of gravitational theory  (BA07040Q) ,  Cosmology  (DB07000D)

Terms in the title (5)： 学習 ,  レンズ効果 ,  質量 ,  マップ ,  雑音除去