Large-scale structure of the universe : cosmological simulations and machine learning

• Material Type: 図書
• ISBN: 9811958793 hardcover; 9789811958793 hardcover; 9789811958809 (electronic bk.); 9811958807 (electronic bk.)
• ISSN (series): 2190-5053
• Title: Large-scale structure of the universe : cosmological simulations and machine learning
• Author/Editor: Kana Moriwaki
• Series Title: Springer theses
• Author Heading: Moriwaki, Kana [森脇可奈]
• Publication, Distribution, etc.: Singapore : Springer (出版)
• Publication Date: [2022]
• Publication Date (W3CDTF): 2022
• Extent: xii, 120 pages
• Size: 25 cm
• Place of Publication (Country Code): SG
• Text Language Code: eng
• Content Type: text
• Media Type: unmediated
• Carrier Type: volume
• Subject Heading: Large scale structure (Astronomy); Astronomy--Observations; Machine learning; Astronomy.; Machine learning.
• LCC: QB991.L37
• DDC: 523.1
• NDLC: MB31
• Target Audience: 一般
• Note (General): "Doctoral Thesis accepted by The University of Tokyo, Tokyo, Japan"
• Note (Bibliography): Includes bibliographical references
• Collection (particular): 日本関係外国語図書
• Holding library: 国立国会図書館
• Call No.: MB31-D2
• Related Material (DOI): 10.1007/978-981-19-5880-9
• Data Provider (Database): 国立国会図書館 : 国立国会図書館蔵書; https://ndlsearch.ndl.go.jp
• Bibliographic ID (NDL): 032374258; http://id.ndl.go.jp/bib/032374258
• Cataloging Rule: RDA
• Bibliographic Record Category (NDL): 211

• Contents: IntroductionObservations of the Large-Scale Structure of the UniverseModeling Emission Line Galaxies...
• Summary, etc.: Line intensity mapping (LIM) is an observational technique that probes the large-scale structure of the Universe by collecting light from a wide field...