Inferring Stellar Properties Using Colours, Parallaxes and an HRD Prior

Abstract

Stellar parameters – effective temperature, metallicity, interstellar extinction etc. – are typically estimated from a spectrum or multiband photometry. I outline a probabilistic method for estimating stellar parameters which uses not only the spectral energy distribution but also the apparent magnitude, parallax (if available) and the strong constraints provided by the Hertzsprung–Russell Diagram. This (a) improves the accuracy and precision over use of just the spectrum, and (b) ensures that the inferred parameters are both physically realistic and are consistent with the distance, apparent magnitude and stellar physics. The method provides full covariate probability distributions over the parameters, i.e. it provides not just parameter estimates but also confidence intervals and the correlations between the estimates. The latter is particularly important given the degeneracies between some parameters, such as temperature and extinction. These degeneracies are shown to be reduced by use of this method. Here I provide a short summary of the method and show some results of its application to 85 000 Hipparcos–2MASS stars and to the Hyades clusters. A full description and further results can be found in Bailer-Jones (Mon. Not. R. Astron. Soc.arXiv:1009.2766, 2011).