Galarza, Carlos Andrés and Daflon, Simone and Placco, Vinicius M. and Allende-Prieto, Carlos and Fernandes, Marcelo Borges and Yuan, Haibo and López-Sanjuan, Carlos and Lee, Young Sun and Solano, Enrique and Jiménez-Esteban, F. and Sobral, David and Candal, Alvaro Alvarez and Pereira, Claudio B. and Akras, Stavros and Martín, Eduardo and Teja, Yolanda Jiménez and Cenarro, Javier and Cristóbal-Hornillos, David and Hernández-Monteagudo, Carlos and Marín-Franch, Antonio and Moles, Mariano and Varela, Jesús and Ramió, Héctor Vázquez and Alcaniz, Jailson and Dupke, Renato and Ederoclite, Alessandro and Jr, Laerte Sodré and Angulo, Raul E. (2022) J-PLUS : Searching for very metal-poor star candidates using the SPEEM pipeline. Astronomy and Astrophysics, 657: A35. ISSN 1432-0746
Full text not available from this repository.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