Machine learning for observational cosmology
© 2023 IOP Publishing Ltd..
An array of large observational programs using ground-based and space-borne telescopes is planned in the next decade. The forthcoming wide-field sky surveys are expected to deliver a sheer volume of data exceeding an exabyte. Processing the large amount of multiplex astronomical data is technically challenging, and fully automated technologies based on machine learning (ML) and artificial intelligence are urgently needed. Maximizing scientific returns from the big data requires community-wide efforts. We summarize recent progress in ML applications in observational cosmology. We also address crucial issues in high-performance computing that are needed for the data processing and statistical analysis.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:86 |
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| Enthalten in: |
Reports on progress in physics. Physical Society (Great Britain) - 86(2023), 7 vom: 26. Mai |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Moriwaki, Kana [VerfasserIn] |
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| Links: |
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| Themen: |
Artificial intelligence |
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| Anmerkungen: |
Date Completed 28.05.2023 Date Revised 28.05.2023 published: Electronic Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1088/1361-6633/acd2ea |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM356497747 |
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| 520 | |a © 2023 IOP Publishing Ltd. | ||
| 520 | |a An array of large observational programs using ground-based and space-borne telescopes is planned in the next decade. The forthcoming wide-field sky surveys are expected to deliver a sheer volume of data exceeding an exabyte. Processing the large amount of multiplex astronomical data is technically challenging, and fully automated technologies based on machine learning (ML) and artificial intelligence are urgently needed. Maximizing scientific returns from the big data requires community-wide efforts. We summarize recent progress in ML applications in observational cosmology. We also address crucial issues in high-performance computing that are needed for the data processing and statistical analysis | ||
| 650 | 4 | |a Journal Article | |
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| 650 | 4 | |a sky survey | |
| 700 | 1 | |a Nishimichi, Takahiro |e verfasserin |4 aut | |
| 700 | 1 | |a Yoshida, Naoki |e verfasserin |4 aut | |
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