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Physical Parameterization Of Stellar Spectra: The Neural Network Approach, Coryn A.L. Bailer-Jones, Ted Von Hippel, Mike Irwin, Gerard Gilmore

Publications

We present a technique which employs artificial neural networks to produce physical parameters for stellar spectra. A neural network is trained on a set of synthetic optical stellar spectra to give physical parameters (e.g. Teff, log g, [M/H]). The network is then used to produce physical parameters for real, observed spectra. Our neural networks are trained on a set of 155 synthetic spectra, generated using the spectrum program written by Gray (Gray & Corbally 1994, Gray & Arlt 1996). Once trained, the neural network is used to yield Teff for over 5000 B–K spectra extracted from a set of photographic …