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Full-Text Articles in Physical Sciences and Mathematics
Three-Dimensional Spectral Classification Of Low-Metallicity Stars Using Artificial Neural Networks, Shawn Snider, Ted Von Hippel, Et Al.
Three-Dimensional Spectral Classification Of Low-Metallicity Stars Using Artificial Neural Networks, Shawn Snider, Ted Von Hippel, Et Al.
Ted von Hippel
We explore the application of artificial neural networks (ANNs) for the estimation of atmospheric parameters (Teff, log g, and [Fe/H]) for Galactic F- and G-type stars. The ANNs are fed with medium-resolution (Δλ ~ 1-2 Å) non-flux-calibrated spectroscopic observations. From a sample of 279 stars with previous high-resolution determinations of metallicity and a set of (external) estimates of temperature and surface gravity, our ANNs are able to predict Teff with an accuracy of σ(Teff) = 135-150 K over the range 4250 ≤ Teff ≤ 6500 K, log g with an accuracy …
Three-Dimensional Spectral Classification Of Low-Metallicity Stars Using Artificial Neural Networks, Shawn Snider, Ted Von Hippel, Carlos Allende Prieto, Timothy C. Beers, Christopher Sneden, Et Al.
Three-Dimensional Spectral Classification Of Low-Metallicity Stars Using Artificial Neural Networks, Shawn Snider, Ted Von Hippel, Carlos Allende Prieto, Timothy C. Beers, Christopher Sneden, Et Al.
Ted von Hippel
We explore the application of artificial neural networks (ANNs) for the estimation of atmospheric parameters (Teff, log g, and [Fe/H]) for Galactic F- and G-type stars. The ANNs are fed with medium-resolution (Δλ ~ 1-2 Å) non-flux-calibrated spectroscopic observations. From a sample of 279 stars with previous high-resolution determinations of metallicity and a set of (external) estimates of temperature and surface gravity, our ANNs are able to predict Teff with an accuracy of σ(Teff) = 135-150 K over the range 4250 ≤ Teff ≤ 6500 K, log g with an accuracy of σ(log …