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Published November 2011 | Published + Supplemental Material
Journal Article Open

Improved methodology for the automated classification of periodic variable stars


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.

Additional Information

© 2011 The Authors. Monthly Notices of the Royal Astronomical Society © 2011 RAS. Accepted 2011 July 18. Received 2011 July 18; in original form 2010 October 2. Article first published online: 22 Sep. 2011. The research leading to these results has received funding from the European Research Council under the European Community's Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement no. 227224 (PROSPERITY), the Research Council of K. U. Leuven (GOA/2008/04), from the Fund for Scientific Research of Flanders (G.0332.06), the Belgian Federal Science Policy Office (C90309: CoRoT Data Exploitation, C90291 Gaia-DPAC) and the Spanish Ministerio de Educaciόn y Ciencia through grant AYA2005-04286. Public access to the TrES data was provided to the through the NASA Star and Exoplanet Database (NStED, http://nsted.ipac.caltech.edu).

Attached Files

Published - Blomme2011p16563Mon_Not_R_Astron_Soc.pdf

Supplemental Material - MNR_19466_sm_Table6.zip


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