Stellar Parameters Determination Using Slice Inverse Regression (speaker: Marwan Gebran, Columbia University)

Monday April 30, 2018 12:05 pm
Marlar Lounge


Sky and On-ground spectroscopic surveys are challenging our capabilities of performing fast and efficient analysis techniques. Our understanding of stars and exoplanets hosts highly depend on the stellar properties. In that context, I will present a new spectroscopic automated procedure that simultaneously derives the effective temperature Teff , surface gravity log g, metallicity [Fe/H], and equatorial projected rotational velocity vsin i for stars. It is based on a combination of the principal component analysis (PCA) inversion and a Regularized Slice inverse regression method (RSIR). The efficiency and accuracy of this procedure have been proven for FGK, A , and late type M dwarf stars. The technique requires a learning database that is generated using observed and/or synthetic data.