Improved methodology for the automated classification of periodic variable stars

Details Improved methodology for the automated classification of periodic variable stars Improved methodology for the automated classification of periodic variable stars

Nov 2011

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011mnras.418...96b&link_type=abstract

Monthly Notices of the Royal Astronomical Society, Volume 418, Issue 1, pp. 96-106.

Astronomy and Astrophysics

Astronomy

1

Methods: Data Analysis, Methods: Statistical, Techniques: Photometric

Scientific paper

We present a novel automated methodology to detect and classify periodic variable stars in a large data base of photometric time series. The methods are based on multivariate Bayesian statistics and use a multistage approach. We applied our method to the ground-based data of the Trans-Atlantic Exoplanet Survey (TrES) Lyr1 field, which is also observed by the Kepler satellite, covering ˜26 000 stars. We found many eclipsing binaries as well as classical non-radial pulsators, such as slowly pulsating B stars, γ Doradus, β Cephei and δ Scuti stars. Also a few classical radial pulsators were found.

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