SIMBAD references

We have employed feedforward neural networks trained on synthetic spectra in the range 3800 to 5600Å with resolutions of ∼2-3Å to determine metallicities from spectra of about 1000 main-sequence turn-off, subgiant and red giant stars in the globular clusters M55 and ω Cen. The overall metallicity accuracies are of the order of 0.15 to 0.2dex. In addition, we tested how well the stellar parameters logg and T_eff can be retrieved from such data without additional colour or photometric information. We find overall uncertainties of 0.3 to 0.4dex for logg and 140 to 190K for T_eff. In order to obtain some measure of uncertainty for the determined values of [Fe/H], logg and T_eff, we applied the bootstrap method for the first time to neural networks for this kind of parametrization problem. The distribution of metallicities for stars in ω Cen clearly shows a large spread in agreement with the well known multiple stellar populations in this cluster.