Toward constraints on galaxy formation scenarios: stellar properties from Galactic surveys

TL;DR

This paper develops methods to classify and analyze stellar objects using spectral data from SDSS and RAVE, estimating atmospheric parameters to study Galactic populations and identify specific star types.

Contribution

It introduces strategies for classifying stellar objects and estimating their parameters from large survey data, aiding galaxy formation scenario constraints.

Findings

Successful classification of Blue Horizontal-Branch and RR Lyrae stars

Effective estimation of stellar atmospheric parameters from spectral data

Insights into Galactic stellar populations

Abstract

We present some of the strategies being developed to classify and parameterize objects obtained with spectra from the Sloan Digital Sky Survey (SDSS) and the RAdial Velocity Experiment (RAVE) and present some results. We estimate stellar atmospheric parameters (effective temperature, gravity, and metallicity) from spectral and photometric data and use these to analyse Galactic populations. We demonstrate this through the selection of a sample of candidate Blue Horizontal-Branch and RR Lyrae stars selected from SDSS/SEGUE.