Title: Photometric redshifts for the S-PLUS Survey: Is machine learning up to the task?

Abstract

The Southern Photometric Local Universe Survey (S-PLUS) is a novel project that aims to map the Southern Hemisphere using a twelve filter system, comprising five broad-band SDSS-like filters and seven narrow-band filters optimized for important stellar features in the local universe. In this paper we use the photometry and morphological information from the first S-PLUS data release (S-PLUS DR1) cross-matched to unWISE data and spectroscopic redshifts from Sloan Digital Sky Survey DR15. We explore three different machine learning methods (Gaussian Processes with GPz and two Deep Learning models made with TensorFlow) and compare them with the currently used template-fitting method in the S-PLUS DR1 to address whether machine learning methods can take advantage of the twelve filter system for photometric redshift prediction. Using tests for accuracy for both single-point estimates such as the calculation of the scatter, bias, and outlier fraction, and probability distribution functions (PDFs) such as the Probability Integral Transform (PIT), the Continuous Ranked Probability Score (CRPS) and the Odds distribution, we conclude that a deep-learning method using a combination of a Bayesian Neural Network and a Mixture Density Network offers the most accurate photometric redshifts for the current test sample. In conclusion, it achieves single-point photometric redshiftsmore » with scatter (σ_NMAD) of 0.023, normalized bias of -0.001, and outlier fraction of 0.64% for galaxies with r_auto magnitudes between 16 and 21.« less

Authors:

Lima, Erik V. Rodrigues  ^[1];

• Search DOE PAGES for author "Lima, Erik V. Rodrigues"
• Search DOE PAGES for ORCID "0000-0002-6268-8600"

Sodré, Laerte  ^[1];

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• Search DOE PAGES for ORCID "0000-0002-3876-268X"

Bom, C. R. ^[2]; Teixeira, Gabriel S.M.  ^[3];

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• Search DOE PAGES for ORCID "0000-0002-1594-208X"

Nakazono, L. ^[1]; Buzzo, Maria Luisa  ^[1];

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• Search DOE PAGES for ORCID "0000-0003-3153-8543"

Queiroz, Carolina  ^[4];

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Herpich, Fabio R.  ^[1];

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• Search DOE PAGES for ORCID "0000-0001-7907-7884"

Castellon, J.L. Nilo ^[5]; Dantas, Maria Luiza Linhares  ^[6];

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• Search DOE PAGES for ORCID "0000-0002-1178-8169"

Dors, O. L. ^[7]; Souza, Rodrigo Clementa Thom de  ^[8];

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• Search DOE PAGES for ORCID "0000-0003-2435-8528"

Akras, Stavros  ^[9];

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• Search DOE PAGES for ORCID "0000-0003-1351-7204"

Jiménez-Teja, Yolanda  ^[10];

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• Search DOE PAGES for ORCID "0000-0002-6090-2853"

Kanaan, A. ^[11]; Ribeiro, T. ^[12]; Schoennell, W. ^[13]

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+ Show Author Affiliations

1. Univ. of Sao Paulo (Brazil)
2. Centro Brasileiro de Pesquisas Físicas, Rio de Janeiro (Brazil); Centro Federal de Educação Tecnológica Celso Suckow da Fonseca, Rio de Janeiro (Brazil)
3. Centro Brasileiro de Pesquisas Físicas, Rio de Janeiro (Brazil)
4. Univ. of Sao Paulo (Brazil); Federal Univ. of Rio Grande do Sul, Porto Alegre (Brazil)
5. Universidad de La Serena (Chile); SIGMA Space Science and Technologies, La Serena (Chile)
6. Polish Academy of Sciences (PAS), Warsaw (Poland)
7. Universidade do Vale do Paraíba, São José dos Campos (Brazil)
8. Universidade Estadual de Maringá (Brazil); Universidade Federal do Paraná, Jandaia do Sul (Brazil)
9. National Observatory of Athens, Penteli (Greece)
10. Consejo Superior de Investigaciones Cientificas (CSIC), Granada (Spain). Instituto de Astrofísica de Andalucía
11. Universidade Federal de Santa Catarina (UFSC), Florianopolis, SC (Brazil)
12. National Optical Astronomy Observatory (NOAO), Tucson, AZ (United States)
13. GMTO Corporation, Pasadena, CA (United States)

Publication Date:

Tue Nov 09 00:00:00 EST 2021

Research Org.:

US Department of Energy (USDOE), Washington, DC (United States). Office of Science, Sloan Digital Sky Survey (SDSS)

Sponsoring Org.:

USDOE Office of Science (SC); Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brazil (CAPES); Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq); São Paulo Research Foundation FAPESP; Southern Office of Aerospace Research and development (SOARD); US Air Force Office of Scientific Research (AFOSR); Polish National Science Centre (NCN); European Union (EU); State Agency for Research of the Spanish MCIU

OSTI Identifier:

1981545

Grant/Contract Number:  

88887.470064/2019-00; 169181/2017-0; 2019/01312-2; 2014/10566-4; 2018/09165-6; 2019/23388-0; 2015/11442-0; 2019/06766-1; FA9550-18-1-0018; FA9550-22-1-0037; 2019/34/E/ST9/00133; 5077; 898633; 2009/54006-4

Resource Type:

Accepted Manuscript

Journal Name:

Astronomy and Computing

Additional Journal Information:

Journal Volume: 38; Journal Issue: C; Journal ID: ISSN 2213-1337

Publisher:

Elsevier

Country of Publication:

United States

Language:

English

Subject:

79 ASTRONOMY AND ASTROPHYSICS; astronomy; astrophysics; computer science; galaxies; distances; redshifts; data analysis; software development; photometric techniques; surveys