Automated classification of ASAS variables (Eyer+, 2005)

Details Automated classification of ASAS variables (Eyer+, 2005) Automated classification of ASAS variables (Eyer+, 2005)

Nov 2006

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006ycat..83580030e&link_type=abstract

VizieR On-line Data Catalog: J/MNRAS/358/30. Originally published in: 2005MNRAS.358...30E

Computer Science

Stars: Variable, Photometry

Scientific paper

With the advent of surveys generating multi-epoch photometry and the discovery of large numbers of variable stars, the classification of these stars has to be automatic. We have developed such a classification procedure for about 1700 stars from the variable star catalogue of the All-Sky Automated Survey 1-2 (ASAS 1-2) by selecting the periodic stars and by applying an unsupervised Bayesian classifier using parameters obtained through a Fourier decomposition of the light curve. For irregular light curves we used the period and moments of the magnitude distribution for the classification. In the case of ASAS 1-2, 83 per cent of variable objects are red giants. A general relation between the period and amplitude is found for a large fraction of those stars. The selection led to 302 periodic and 1429 semiperiodic stars, which are classified in six major groups: eclipsing binaries, 'sinusoidal curves', Cepheids, small amplitude red variables, SR and Mira stars. The type classification error level is estimated to be about 7 per cent.
(1 data file).

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