Bayesian inference of stellar parameters and interstellar extinction using parallaxes and multiband photometry

摘要

Astrometric surveys provide the opportunity to measure the absolutemagnitudes of large numbers of stars, but only if the individual line-of-sightextinctions are known. Unfortunately, extinction is highly degenerate withstellar effective temperature when estimated from broad band optical/infraredphotometry. To address this problem, I introduce a Bayesian method forestimating the intrinsic parameters of a star and its line-of-sight extinction.It uses both photometry and parallaxes in a self-consistent manner in order toprovide a non-parametric posterior probability distribution over theparameters. The method makes explicit use of domain knowledge by employing theHertzsprung--Russell Diagram (HRD) to constrain solutions and to ensure thatthey respect stellar physics. I first demonstrate this method by using it toestimate effective temperature and extinction from BVJHK data for a set ofartificially reddened Hipparcos stars, for which accurate effectivetemperatures have been estimated from high resolution spectroscopy. Using justthe four colours, we see the expected strong degeneracy (positive correlation)between the temperature and extinction. Introducing the parallax, apparentmagnitude and the HRD reduces this degeneracy and improves both the precision(reduces the error bars) and the accuracy of the parameter estimates, thelatter by about 35%. The resulting accuracy is about 200K in temperature and0.2mag in extinction. I then apply the method to estimate these parameters andabsolute magnitudes for some 47000 F,G,K Hipparcos stars which have beencross-matched with 2MASS. The method can easily be extended to incorporate theestimation of other parameters, in particular metallicity and surface gravity,making it particularly suitable for the analysis of the 10^9 stars from Gaia.