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J-PLUS: Searching for very metal-poor star candidates using the SPEEM pipeline

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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J-PLUS: Searching for very metal-poor star candidates using the SPEEM pipeline. / Galarza, Carlos Andrés; Daflon, Simone; Placco, Vinicius M. et al.
In: Astronomy and Astrophysics, Vol. 657, A35, 31.01.2022.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Galarza, CA, Daflon, S, Placco, VM, Allende-Prieto, C, Fernandes, MB, Yuan, H, López-Sanjuan, C, Lee, YS, Solano, E, Jiménez-Esteban, F, Sobral, D, Candal, AA, Pereira, CB, Akras, S, Martín, E, Teja, YJ, Cenarro, J, Cristóbal-Hornillos, D, Hernández-Monteagudo, C, Marín-Franch, A, Moles, M, Varela, J, Ramió, HV, Alcaniz, J, Dupke, R, Ederoclite, A, Jr, LS & Angulo, RE 2022, 'J-PLUS: Searching for very metal-poor star candidates using the SPEEM pipeline', Astronomy and Astrophysics, vol. 657, A35. https://doi.org/10.1051/0004-6361/202141717

APA

Galarza, C. A., Daflon, S., Placco, V. M., Allende-Prieto, C., Fernandes, M. B., Yuan, H., López-Sanjuan, C., Lee, Y. S., Solano, E., Jiménez-Esteban, F., Sobral, D., Candal, A. A., Pereira, C. B., Akras, S., Martín, E., Teja, Y. J., Cenarro, J., Cristóbal-Hornillos, D., Hernández-Monteagudo, C., ... Angulo, R. E. (2022). J-PLUS: Searching for very metal-poor star candidates using the SPEEM pipeline. Astronomy and Astrophysics, 657, Article A35. https://doi.org/10.1051/0004-6361/202141717

Vancouver

Galarza CA, Daflon S, Placco VM, Allende-Prieto C, Fernandes MB, Yuan H et al. J-PLUS: Searching for very metal-poor star candidates using the SPEEM pipeline. Astronomy and Astrophysics. 2022 Jan 31;657:A35. Epub 2021 Dec 24. doi: 10.1051/0004-6361/202141717

Author

Galarza, Carlos Andrés ; Daflon, Simone ; Placco, Vinicius M. et al. / J-PLUS : Searching for very metal-poor star candidates using the SPEEM pipeline. In: Astronomy and Astrophysics. 2022 ; Vol. 657.

Bibtex

@article{8a3073280be54d22a948a34825ab8296,
title = "J-PLUS: Searching for very metal-poor star candidates using the SPEEM pipeline",
abstract = " We explore the stellar content of the Javalambre Photometric Local Universe Survey (J-PLUS) Data Release 2 and show its potential to identify low-metallicity stars using the Stellar Parameters Estimation based on Ensemble Methods (SPEEM) pipeline. SPEEM is a tool to provide determinations of atmospheric parameters for stars and separate stellar sources from quasars, using the unique J-PLUS photometric system. The adoption of adequate selection criteria allows the identification of metal-poor star candidates suitable for spectroscopic follow-up. SPEEM consists of a series of machine learning models which uses a training sample observed by both J-PLUS and the SEGUE spectroscopic survey. The training sample has temperatures Teff between 4\,800 K and 9\,000 K; $\log g$ between 1.0 and 4.5, and $-3.1",
keywords = "methods: data analysis, stars: fundamental parameters, stars: statistics, stars: general, stars: Population III",
author = "Galarza, {Carlos Andr{\'e}s} and Simone Daflon and Placco, {Vinicius M.} and Carlos Allende-Prieto and Fernandes, {Marcelo Borges} and Haibo Yuan and Carlos L{\'o}pez-Sanjuan and Lee, {Young Sun} and Enrique Solano and F. Jim{\'e}nez-Esteban and David Sobral and Candal, {Alvaro Alvarez} and Pereira, {Claudio B.} and Stavros Akras and Eduardo Mart{\'i}n and Teja, {Yolanda Jim{\'e}nez} and Javier Cenarro and David Crist{\'o}bal-Hornillos and Carlos Hern{\'a}ndez-Monteagudo and Antonio Mar{\'i}n-Franch and Mariano Moles and Jes{\'u}s Varela and Rami{\'o}, {H{\'e}ctor V{\'a}zquez} and Jailson Alcaniz and Renato Dupke and Alessandro Ederoclite and Jr, {Laerte Sodr{\'e}} and Angulo, {Raul E.}",
year = "2022",
month = jan,
day = "31",
doi = "10.1051/0004-6361/202141717",
language = "English",
volume = "657",
journal = "Astronomy and Astrophysics",
issn = "1432-0746",
publisher = "EDP Sciences",

}

RIS

TY - JOUR

T1 - J-PLUS

T2 - Searching for very metal-poor star candidates using the SPEEM pipeline

AU - Galarza, Carlos Andrés

AU - Daflon, Simone

AU - Placco, Vinicius M.

AU - Allende-Prieto, Carlos

AU - Fernandes, Marcelo Borges

AU - Yuan, Haibo

AU - López-Sanjuan, Carlos

AU - Lee, Young Sun

AU - Solano, Enrique

AU - Jiménez-Esteban, F.

AU - Sobral, David

AU - Candal, Alvaro Alvarez

AU - Pereira, Claudio B.

AU - Akras, Stavros

AU - Martín, Eduardo

AU - Teja, Yolanda Jiménez

AU - Cenarro, Javier

AU - Cristóbal-Hornillos, David

AU - Hernández-Monteagudo, Carlos

AU - Marín-Franch, Antonio

AU - Moles, Mariano

AU - Varela, Jesús

AU - Ramió, Héctor Vázquez

AU - Alcaniz, Jailson

AU - Dupke, Renato

AU - Ederoclite, Alessandro

AU - Jr, Laerte Sodré

AU - Angulo, Raul E.

PY - 2022/1/31

Y1 - 2022/1/31

N2 - We explore the stellar content of the Javalambre Photometric Local Universe Survey (J-PLUS) Data Release 2 and show its potential to identify low-metallicity stars using the Stellar Parameters Estimation based on Ensemble Methods (SPEEM) pipeline. SPEEM is a tool to provide determinations of atmospheric parameters for stars and separate stellar sources from quasars, using the unique J-PLUS photometric system. The adoption of adequate selection criteria allows the identification of metal-poor star candidates suitable for spectroscopic follow-up. SPEEM consists of a series of machine learning models which uses a training sample observed by both J-PLUS and the SEGUE spectroscopic survey. The training sample has temperatures Teff between 4\,800 K and 9\,000 K; $\log g$ between 1.0 and 4.5, and $-3.1

AB - We explore the stellar content of the Javalambre Photometric Local Universe Survey (J-PLUS) Data Release 2 and show its potential to identify low-metallicity stars using the Stellar Parameters Estimation based on Ensemble Methods (SPEEM) pipeline. SPEEM is a tool to provide determinations of atmospheric parameters for stars and separate stellar sources from quasars, using the unique J-PLUS photometric system. The adoption of adequate selection criteria allows the identification of metal-poor star candidates suitable for spectroscopic follow-up. SPEEM consists of a series of machine learning models which uses a training sample observed by both J-PLUS and the SEGUE spectroscopic survey. The training sample has temperatures Teff between 4\,800 K and 9\,000 K; $\log g$ between 1.0 and 4.5, and $-3.1

KW - methods: data analysis

KW - stars: fundamental parameters

KW - stars: statistics

KW - stars: general

KW - stars: Population III

U2 - 10.1051/0004-6361/202141717

DO - 10.1051/0004-6361/202141717

M3 - Journal article

VL - 657

JO - Astronomy and Astrophysics

JF - Astronomy and Astrophysics

SN - 1432-0746

M1 - A35

ER -