Machine learning for observational cosmology.
Rep Prog Phys
; 86(7)2023 May 26.
Article
em En
| MEDLINE
| ID: mdl-37146601
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.
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1
Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Revista:
Rep Prog Phys
Ano de publicação:
2023
Tipo de documento:
Article
País de afiliação:
Japão
País de publicação:
Reino Unido