Blomme, J. and Sarro, L. M. and O'Donovan, F. T. and Debosscher, J. and Brown, T. and Lopez, M. and Dubath, P. and Rimoldini, L. and Charbonneau, D. and Dunham, E. and Mandushev, G. and Ciardi, D. R. and De Ridder, J. and Aerts, C. (2011) Improved methodology for the automated classification of periodic variable stars. Monthly Notices of the Royal Astronomical Society, 418 (1). pp. 96-106. ISSN 0035-8711
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Abstract
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 ∼26000 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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