NAOC Open IR
Twenty-First-Century Statistical and Computational Challenges in Astrophysics
Feigelson, Eric D.1,2,3; de Souza, Rafael S.4; Ishida, Emille E. O.5; Babu, Gutti Jogesh1,2,3
2021
Source PublicationANNUAL REVIEW OF STATISTICS AND ITS APPLICATION, VOL 8, 2021
ISSN2326-8298
Volume8Pages:493-517
AbstractModern astronomy has been rapidly increasing our ability to see deeper into the Universe, acquiring enormous samples of cosmic populations. Gaining astrophysical insights from these data sets requires a wide range of sophisticated statistical and machine learning methods. Long-standing problems in cosmology include characterization of galaxy clustering and estimation of galaxy distances from photometric colors. Bayesian inference, central to linking astronomical data to nonlinear astrophysical models, addresses problems in solar physics, properties of star clusters, and exoplanet systems. Likelihood-free methods are growing in importance. Detection of faint signals in complicated noise is needed to find periodic behaviors in stars and detect explosive gravitational wave events. Open issues concern treatment of heteroscedastic measurement errors and understanding probability distributions characterizing astrophysical systems. The field of astrostatistics needs increased collaboration with statisticians in the design and analysis stages of research projects, and joint development of new statistical methodologies. This collaboration will yield more astrophysical insights into astronomical populations and the cosmos itself.
Keywordastronomy astrophysics astrostatistics cosmology galaxies stars exoplanets gravitational waves Bayesian inference likelihood-free modeling signal detection periodic time series machine learning measurement errors
Funding OrganizationNSF ; NSF ; NASA ; NASA ; Eberly College of Science through the Center for Astrostatistics ; Eberly College of Science through the Center for Astrostatistics ; 2018-20 CNRS MOMENTUM fellowship ; 2018-20 CNRS MOMENTUM fellowship ; NSF ; NSF ; NASA ; NASA ; Eberly College of Science through the Center for Astrostatistics ; Eberly College of Science through the Center for Astrostatistics ; 2018-20 CNRS MOMENTUM fellowship ; 2018-20 CNRS MOMENTUM fellowship ; NSF ; NSF ; NASA ; NASA ; Eberly College of Science through the Center for Astrostatistics ; Eberly College of Science through the Center for Astrostatistics ; 2018-20 CNRS MOMENTUM fellowship ; 2018-20 CNRS MOMENTUM fellowship ; NSF ; NSF ; NASA ; NASA ; Eberly College of Science through the Center for Astrostatistics ; Eberly College of Science through the Center for Astrostatistics ; 2018-20 CNRS MOMENTUM fellowship ; 2018-20 CNRS MOMENTUM fellowship
DOI10.1146/annurev-statistics-042720-112045
WOS KeywordGENERALIZED LINEAR-MODELS ; SUPERNOVA PHOTOMETRIC CLASSIFICATION ; APPROXIMATE BAYESIAN COMPUTATION ; LIKELIHOOD-FREE INFERENCE ; DENSITY-ESTIMATION ; SPECTRAL-ANALYSIS ; MASS ; REGRESSION ; ASTRONOMY ; GALAXIES
Language英语
Funding ProjectNSF[AST-1614690] ; NASA[80NSSC17K0122] ; Eberly College of Science through the Center for Astrostatistics ; 2018-20 CNRS MOMENTUM fellowship
Funding OrganizationNSF ; NSF ; NASA ; NASA ; Eberly College of Science through the Center for Astrostatistics ; Eberly College of Science through the Center for Astrostatistics ; 2018-20 CNRS MOMENTUM fellowship ; 2018-20 CNRS MOMENTUM fellowship ; NSF ; NSF ; NASA ; NASA ; Eberly College of Science through the Center for Astrostatistics ; Eberly College of Science through the Center for Astrostatistics ; 2018-20 CNRS MOMENTUM fellowship ; 2018-20 CNRS MOMENTUM fellowship ; NSF ; NSF ; NASA ; NASA ; Eberly College of Science through the Center for Astrostatistics ; Eberly College of Science through the Center for Astrostatistics ; 2018-20 CNRS MOMENTUM fellowship ; 2018-20 CNRS MOMENTUM fellowship ; NSF ; NSF ; NASA ; NASA ; Eberly College of Science through the Center for Astrostatistics ; Eberly College of Science through the Center for Astrostatistics ; 2018-20 CNRS MOMENTUM fellowship ; 2018-20 CNRS MOMENTUM fellowship
WOS Research AreaMathematics
WOS SubjectMathematics, Interdisciplinary Applications ; Statistics & Probability
WOS IDWOS:000627718500022
PublisherANNUAL REVIEWS
Citation statistics
Document Type期刊论文
Identifierhttp://ir.bao.ac.cn/handle/114a11/78412
Collection中国科学院国家天文台
Corresponding AuthorFeigelson, Eric D.
Affiliation1.Penn State Univ, Dept Astron & Astrophys, University Pk, PA 16802 USA
2.Penn State Univ, Dept Stat, University Pk, PA 16802 USA
3.Penn State Univ, Ctr Astrostat, University Pk, PA 16802 USA
4.Chinese Acad Sci, Shanghai Astron Observ, Key Lab Res Galaxies & Cosmol, Shanghai 200030, Peoples R China
5.Univ Clermont Auvergne, CNRS, IN2P3, LPC, F-63000 Clermont Ferrand, France
Recommended Citation
GB/T 7714
Feigelson, Eric D.,de Souza, Rafael S.,Ishida, Emille E. O.,et al. Twenty-First-Century Statistical and Computational Challenges in Astrophysics[J]. ANNUAL REVIEW OF STATISTICS AND ITS APPLICATION, VOL 8, 2021,2021,8:493-517.
APA Feigelson, Eric D.,de Souza, Rafael S.,Ishida, Emille E. O.,&Babu, Gutti Jogesh.(2021).Twenty-First-Century Statistical and Computational Challenges in Astrophysics.ANNUAL REVIEW OF STATISTICS AND ITS APPLICATION, VOL 8, 2021,8,493-517.
MLA Feigelson, Eric D.,et al."Twenty-First-Century Statistical and Computational Challenges in Astrophysics".ANNUAL REVIEW OF STATISTICS AND ITS APPLICATION, VOL 8, 2021 8(2021):493-517.
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