8-12 juin, 2014

Résumé

Bayesian Statistics as a New Tool for Spectral Analysis: Application for Massive Stars Fondamental Parameters Determination

Jean-Michel Mugnes (Université Laval)

Camelle robert, Université laval, CRAQ

Spectral analysis is a powerful tool to investigate stellar properties and it has been widely used for decades. However, the methods used to perform this kind of analysis are mostly based on iteration between a few diagnostic lines to determine the fundamental parameters of the stars. And while it is a simple and a fast method, it can lead to errors and wide uncertainties in the resulting parameters due to the required assumptions of the classical approach. Namely, the need of initial guessed parameters and the fact that each of these parameters are considered as quasi-independant from the others. Here we present a method based on Bayesian Statistics to find simultaneously the best combination of all the fundamental stellar parameters using all available spectral lines. We applied this method on 52 field and clusters B stars spectra obtained at the Mont-Mégantic Observatory. We also compare our results with those found in the literature.
(doit être confirmé par le SOC)