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

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  • Carlos Andrés Galarza
  • Simone Daflon
  • Vinicius M. Placco
  • Carlos Allende-Prieto
  • Marcelo Borges Fernandes
  • Haibo Yuan
  • Carlos López-Sanjuan
  • Young Sun Lee
  • Enrique Solano
  • F. Jiménez-Esteban
  • Alvaro Alvarez Candal
  • Claudio B. Pereira
  • Stavros Akras
  • Eduardo Martín
  • Yolanda Jiménez Teja
  • Javier Cenarro
  • David Cristóbal-Hornillos
  • Carlos Hernández-Monteagudo
  • Antonio Marín-Franch
  • Mariano Moles
  • Jesús Varela
  • Héctor Vázquez Ramió
  • Jailson Alcaniz
  • Renato Dupke
  • Alessandro Ederoclite
  • Laerte Sodré Jr
  • Raul E. Angulo
Article numberA35
<mark>Journal publication date</mark>31/01/2022
<mark>Journal</mark>Astronomy and Astrophysics
Number of pages13
Publication StatusPublished
Early online date24/12/21
<mark>Original language</mark>English


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