Spectral Classification of Unresolved Binary Stars with Artificial Neural Networks

An artificial neural network technique has been developed to perform two-dimensional spectral classification of the components of binary stars. The spectra are based on the 15 Å resolution near-infrared (NIR) spectral classification system described by Torres-Dodgen & Weaver. Using the spectrum with no manual intervention except wavelength registration, a single artificial neural network (ANN) can classify these spectra with Morgan-Keenan types with an average accuracy of about 2.5 types (subclasses) in temperature and about 0.45 classes in luminosity for up to 3 mag of difference in luminosity. The error in temperature classification does not increase substantially until the secondary contributes less than 10% of the light of the system. By following the coarse-classification ANN with a specialist ANN, the mean absolute errors are reduced to about 0.5 types in temperature and 0.33 classes in luminosity. The resulting ANN network was applied to seven binary stars.