Volume 622, February 2019
|Number of page(s)||18|
|Published online||21 February 2019|
J-PLUS: Identification of low-metallicity stars with artificial neural networks using SPHINX
Department of Physics, University of Notre Dame,
2 JINA Center for the Evolution of the Elements, East Lansing, USA
3 Departamento de Astronomia, Instituto de Física, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
4 Centro de Estudios de Física del Cosmos de Aragón (CEFCA) – Unidad Asociada al CSIC, Plaza San Juan, Planta 2, 44001 Teruel, Spain
5 Instituto de Astrofísica de Canarias, 38205 La Laguna, Tenerife, Spain
6 Departamento de Astrofísica, Universidad de La Laguna, 38206 La Laguna, Tenerife, Spain
7 Department of Astronomy and Space Science, Chungnam National University, Daejon 34134, Korea
8 Observatório Nacional – MCTIC (ON), Rua Gal. José Cristino 77, São Cristóvão, 20921-400, Rio de Janeiro, Brazil
9 Centro de Astrobiología (CSIC-INTA), ESAC, Camino Bajo del Castillo S/N, 28692 Villanueva de la Cañada Madrid, Spain
10 Instituto de Astronomia, Geofísica e Ciências Atmosféricas (IAG), Universidade de São Paulo, Rua do Matão 1226, C. Universitária, São Paulo, 05508-090, Brazil
11 Departamento de Física, Universidade Federal de Sergipe, Av. Marechal Rondon, s/n, 49000-000 São Cristóvão, SE, Brazil
12 Centro de Estudios de Física del Cosmos de Aragón (CEFCA), Plaza San Juan, 1, 44001, Teruel, Spain
13 Department of Astronomy, University of Michigan, 1085 S. Ave, University Ann Arbor, MI 48109, USA
14 Department of Phys. & Astronomy, University of Alabama, Gallalee Hall, Tuscaloosa, AL 35401, USA
15 X-ray Astrophysics Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
16 Department of Physics, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA
Accepted: 5 November 2018
Context. We present a new methodology for the estimation of stellar atmospheric parameters from narrow- and intermediate-band photometry of the Javalambre Photometric Local Universe Survey (J-PLUS), and propose a method for target pre-selection of low-metallicity stars for follow-up spectroscopic studies. Photometric metallicity estimates for stars in the globular cluster M15 are determined using this method.
Aims. By development of a neural-network-based photometry pipeline, we aim to produce estimates of effective temperature, Teff, and metallicity, [Fe/H], for a large subset of stars in the J-PLUS footprint.
Methods. The Stellar Photometric Index Network Explorer, SPHINX, was developed to produce estimates of Teff and [Fe/H], after training on a combination of J-PLUS photometric inputs and synthetic magnitudes computed for medium-resolution (R ~ 2000) spectra of the Sloan Digital Sky Survey. This methodology was applied to J-PLUS photometry of the globular cluster M15.
Results. Effective temperature estimates made with J-PLUS Early Data Release photometry exhibit low scatter, σ(Teff) = 91 K, over the temperature range 4500 < Teff (K) < 8500. For stars from the J-PLUS First Data Release with 4500 < Teff (K) < 6200, 85 ± 3% of stars known to have [Fe/H] < −2.0 are recovered by SPHINX. A mean metallicity of [Fe/H] = − 2.32 ± 0.01, with a residual spread of 0.3 dex, is determined for M15 using J-PLUS photometry of 664 likely cluster members.
Conclusions. We confirm the performance of SPHINX within the ranges specified, and verify its utility as a stand-alone tool for photometric estimation of effective temperature and metallicity, and for pre-selection of metal-poor spectroscopic targets.
Key words: stars: chemically peculiar / stars: fundamental parameters / stars: abundances / techniques: photometric / methods: data analysis
© ESO 2019
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