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P.R. Wozniak, S.J. Williams, W.T. Vestrand, V. Gupta (LANL)
We present a catalog of 8,678 slow varying stars with near infrared colors corresponding to the evolved AGB population. Objects were selected from the Northern Sky Variability Survey (NSVS) covering the entire sky above declination \delta=-38\arcdeg in a single unfiltered photometric band corresponding to a V-band magnitude range of ~8--15.5 mag. After quality cuts, the number of measurements for a typical star is approximately 150, but it ranges up to ~1000 for high declination stars. We show that the use of Support Vector Machines, a modern Machine Learning algorithm, can reliably distinguish Mira (M) variables from other types of red variables, namely semi-regular (SR) and irregular (L). We also identify a region of parameter space which is dominated by carbon stars. Our classification is based on period, amplitude and three independent colors possible with photometry from the NSVS and the Two Micron All Sky Survey (2MASS). The overall classification accuracy is ~90% despite the relatively short survey base-line of 1 year and limited set of features. There are 6,474 stars in our sample without identifications in General Catalog of Variable Stars (GCVS) and, as such, are most likely new discoveries. Period-amplitude and period-color diagrams of both our previously known and newly identified Mira stars are in good agreement with the published studies based on smaller samples.
The author(s) of this abstract have provided an email address for comments about the abstract: wozniak@lanl.gov
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Bulletin of the American Astronomical Society, 36 5
© 2004. The American Astronomical Society.