J-PLUS: stellar parameter determination of members of open clusters using machine learning
E. Machado-Pereira, Sarah Dario Alves Daflon, V M Placco, P Cruz et autres
ABSTRACT We present a machine learning approach to estimate stellar atmospheric parameters ($T_\mathrm{eff}$, $\log \, g$, and $[\mathrm{Fe}/\mathrm{H}]$) for stars in the J-PLUS DR3 footprint using photometric and astrometric data from J-PLUS, Gaia, and CatWISE. Our models are based on the gradient …
br, us, es, cn, cu (code pays fourni par la source)
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Monthly Notices of the Royal Astronomical Society