Searching for WDMS Candidates In SDSS-DR10 With Automatic Method

Abstract

The Sloan Digital Sky Survey (SDSS) has released the latest data (DR10) which covers the first APOGEE spectra. The massive spectra can be used for large sample research inscluding the structure and evolution of the Galaxy and multi-wave-band identi cation. In addition, the spectra are also ideal for searching for rare and special objects like white dwarf main-sequence star (WDMS). WDMS consist of a white dwarf primary and a low-mass main-sequence (MS) companion which has positive significance to the study of evolution and parameter of close binaries. WDMS is generally discovered by repeated imaging of the same area of sky, measuring light curves for objects or through photometric selection with follow-up observations. These methods require significant manual processing time with low accuracy and the real-time processing requirements can not be satisfied. In this paper, an automatic and efficient method for searching for WDMS candidates is presented. The method Genetic Algorithm (GA) is applied in the newly released SDSS-DR10 spectra. A total number of 4 140 WDMS candidates are selected by the method and 24 of them are new discoveries which prove that our approach of finding special celestial bodies in massive spectra data is feasible. In addition, this method is also applicable to mining other special celestial objects in sky survey telescope data. We report the identfication of 24 new WDMS with spectra. A compendium of positions, mjd, plate and fiberid of these new discoveries is presented which enrich the spectral library and will be useful to the research of binary evolution models.