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(Teff,Log G,[Fe/H]) Classification Of Low-Resolution Stellar Spectra Using Artificial Neural Networks, Shawn Snider, Yuan Qu, Carlos Allende Prieto, Ted Von Hippel, Timothy C. Beers, Christopher Sneden, David L. Lambert, Silvia Rossi

Publications

New generation large-aperture telescopes, multi-object spectrographs, and large format detectors are making it possible to acquire very large samples of stellar spectra rapidly. In this context, traditional star-by-star spectroscopic analysis are no longer practical. New tools are required that are capable of extracting quickly and with reasonable accuracy important basic stellar parameters coded in the spectra. Recent analyses of Artificial Neural Networks (ANNs) applied to the classification of astronomical spectra have demonstrated the ability of this concept to derive estimates of temperature and luminosity. We have adapted the back-propagation ANN technique developed by von Hippel et al. (1994) to predict …