STATISTICAL STUDY OF 2XMMi-DR3/SDSS-DR8 CROSS-CORRELATION SAMPLE
- Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, 20A Datun Road, Chaoyang District, 100012 Beijing (China)
Cross-correlating the XMM-Newton 2XMMi-DR3 catalog with the Sloan Digital Sky Survey (SDSS) Data Release 8, we obtain one of the largest X-ray/optical catalogs and explore the distribution of various classes of X-ray emitters in the multidimensional photometric parameter space. Quasars and galaxies occupy different zones while stars scatter in them. However, X-ray active stars have a certain distributing rule according to spectral types. The earlier the type of stars, the stronger its X-ray emitting. X-ray active stars have a similar distribution to most stars in the g - r versus r - i diagram. Based on the identified samples with SDSS spectral classification, a random forest algorithm for automatic classification is performed. The result shows that the classification accuracy of quasars and galaxies adds up to more than 93.0% while that of X-ray emitting stars only amounts to 45.3%. In other words, it is easy to separate quasars and galaxies, but it is difficult to discriminate X-ray active stars from quasars and galaxies. If we want to improve the accuracy of automatic classification, it is necessary to increase the number of X-ray emitting stars, since the majority of X-ray emitting sources are quasars and galaxies. The results obtained here will be used for the optical spectral survey performed by the Large sky Area Multi-Object fiber Spectroscopic Telescope (LAMOST, also named the Guo Shou Jing Telescope), which is a Chinese national scientific research facility operated by the National Astronomical Observatories, Chinese Academy of Sciences.
- OSTI ID:
- 22089688
- Journal Information:
- Astronomical Journal (New York, N.Y. Online), Vol. 145, Issue 2; Other Information: Country of input: International Atomic Energy Agency (IAEA); ISSN 1538-3881
- Country of Publication:
- United States
- Language:
- English
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