Method and application to the first four exoplanet fields
Instituut voor Sterrenkunde, Catholic University of Leuven, Celestijnenlaan 200D, 3001 Leuven, Belgium e-mail: firstname.lastname@example.org
2 Dpt. de Inteligencia Artificial , UNED, Juan del Rosal, 16, 28040 Madrid, Spain
3 LAEX-CAB (INTA-CSIC), Postal address.- LAEFF, European Space Astronomy Center (ESAC), PO Box 78, 28691 Villanueva de la Cañada, Madrid, Spain
4 LAM, UMR 6110, CNRS/Univ. de Provence, 38 rue F. Joliot-Curie, 13388 Marseille, France
5 Department of Astrophysics, Radboud University Nijmegen, PO Box 9010, 6500 GL Nijmegen, The Netherlands
6 LESIA, UMR8109, Université Pierre et Marie Curie, Université Denis Diderot, Observatoire de Paris, 92195 Meudon Cedex, France
7 IAS, Université Paris XI, 91405 Orsay, France
8 Observatoire de la Côte d'Azur, Université Nice Sophia-Antipolis, UMR 6525. Parc Valrose, 06108 Nice, France
9 Laboratoire d'Astrophysique de Toulouse-Tarbes, Université de Toulouse, CNRS, 14 Av. E. Belin, 31400 Toulouse, France
10 Royal Observatory of Belgium, Ringlaan 3, 1180 Brussel, Belgium
11 Instituto de Astrofísica de Andalucía-CSIC, Apdo 3004, 18080 Granada, Spain
12 GEPI, Observatoire de Paris, CNRS, Université Paris Diderot, 5 place Jules Janssen, 92195 Meudon Cedex, France
13 Universidade de São Paulo, Instituto de Astronomia, Geofísica e Ciências Atmosféricas - IAG, Departamento de Astronomia, Rua do Matão 1226, 05508-900 São Paulo, Brazil
14 Department of Astronomy, University of Vienna, Türkenschanzstrasse 17, 1180 Wien, Austria
15 Konkoly Observatory, 1525 Budapest, PO Box 67., Hungary
16 INAF – Osservatorio Astronomico di Roma via Frascati 33, 00040 Monteporzio C. (RM), Italy
Accepted: 12 March 2009
Aims. In this work, we describe the pipeline for the fast supervised classification of light curves observed by the CoRoT exoplanet CCDs. We present the classification results obtained for the first four measured fields, which represent a one-year in-orbit operation.
Methods. The basis of the adopted supervised classification methodology has been described in detail in a previous paper, as is its application to the OGLE database. Here, we present the modifications of the algorithms and of the training set to optimize the performance when applied to the CoRoT data.
Results. Classification results are presented for the observed fields IRa01, SRc01, LRc01, and LRa01 of the CoRoT mission. Statistics on the number of variables and the number of objects per class are given and typical light curves of high-probability candidates are shown. We also report on new stellar variability types discovered in the CoRoT data. The full classification results are publicly available.
Key words: stars: variables: general / stars: binaries: general / techniques: photometric / methods: statistical / methods: data analysis
The CoRoT space mission, launched on 27 December 2006, has been developed and is operated by the CNES, with the contribution of Austria, Belgium, Brazil , ESA, Germany, and Spain.
© ESO, 2009