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Improved methodology for the automated classification of periodic variable stars

Blomme, J. ; Sarro, L. M. ; O'Donovan, F. T. ; Debosscher, J. ; Brown, T. ; Lopez, M. ; Dubath, P. ; Rimoldini, L. ; Charbonneau, D. ; Dunham, E. ; Mandushev, G. ; Ciardi, D. R. ; De Ridder, J. ; Aerts, C.

In: Monthly Notices of the Royal Astronomical Society, 2011, vol. 418, no. 1, p. 96-106

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    Titre
    • Improved methodology for the automated classification of periodic variable stars
    Auteur
    • Blomme, J.. Instituut voor Sterrenkunde, Katholieke Universiteit Leuven, Celestijnenlaan 200D, B-3001 Leuven, Belgium
    • Sarro, L. M.. Dpt. de Inteligencia Artificial, UNED, Juan del Rosal, 16, 28040 Madrid, Spain
    • O'Donovan, F. T.. California Institute of Technology, 1200 E. California Blvd. Pasadena, CA 91125, USA
    • Debosscher, J.. Instituut voor Sterrenkunde, Katholieke Universiteit Leuven, Celestijnenlaan 200D, B-3001 Leuven, Belgium
    • Brown, T.. Las Cumbres Observatory Global Telescope, Goleta, CA 93117, USA
    • Lopez, M.. Departamento de Astrofísica, Centro de Astrobiología (INTA-CSIC), PO Box 78, E-28691 Villanueva de la Cañada, Spain
    • Dubath, P.. Geneva Observatory, Chemin d'Écogia 16, CH-1290 Versoix, Switzerland
    • Rimoldini, L.. Geneva Observatory, Chemin d'Écogia 16, CH-1290 Versoix, Switzerland
    • Charbonneau, D.. Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, MA 02138, USA
    • Dunham, E.. Lowell Observatory, 1400 W. Mars Hill Road, Flagstaff, AZ 86001, USA
    • Mandushev, G.. Lowell Observatory, 1400 W. Mars Hill Road, Flagstaff, AZ 86001, USA
    • Ciardi, D. R.. NASA Exoplanet Science Institute/Caltech, Pasadena, CA 91125, USA
    • De Ridder, J.. Instituut voor Sterrenkunde, Katholieke Universiteit Leuven, Celestijnenlaan 200D, B-3001 Leuven, Belgium
    • Aerts, C.. Instituut voor Sterrenkunde, Katholieke Universiteit Leuven, Celestijnenlaan 200D, B-3001 Leuven, Belgium
    Type de document
    • Postprint
    Langue
    • Inglese
    Publié dans
    • Monthly Notices of the Royal Astronomical Society, 2011, vol. 418, no. 1, p. 96-106. Blackwell Publishing Ltd
    Autre version électronique
    Identifiant OAI-PMH
    • oai:doc.rero.ch:302309
    Summary
    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