explorationofsdssstellardatabasebyautoclass

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	explorationofsdssstellardatabasebyautoclass
	Yan Taisheng 2; Zhang Yanxia 2; Zhao Yongheng 2; Li Ji 1
刊名	sciencechinaphysicsmechanicsastronomy
	2011
卷号	54 期号:9 页码:1717
ISSN号	1674-7348
英文摘要	AutoClass is an unsupervised Bayesian classification approach which seeks a maximum posterior probability classification for determining the optimal classes in large data sets. Using stellar photometric data from the Sloan Digital Sky Survey (SDSS) data release 7 (DR7), we utilize AutoClass to select non-stellar objects from this sample in order to build a pure stellar sample. For this purpose, the differences between PSF (point spread function) magnitudes and model magnitudes in five wavebands are taken as the input of AutoClass. Through clustering analysis of this sample by AutoClass, 617 non-stellar candidates are found. These candidates are identified by NED and SIMBAD databases. Most of the identified sources (13 from SIMBAD and 28 from NED respectively) are extragalactic sources (e.g., galaxies, HII, radio sources, infrared sources), some are peculiar stars (e.g., supernovas), and very few are normal stars. The extragalactic sources and peculiar stars of the identified objects occupy 94.1%. The result indicates that this method is an effective and robust clustering algorithm to find non-stellar objects and peculiar stars from the total stellar sample.
语种	英语
内容类型	期刊论文
源URL	[http://ir.bao.ac.cn/handle/114a11/41076]
专题	中国科学院国家天文台
作者单位	1.河北师范大学 2.中国科学院国家天文台
推荐引用方式 GB/T 7714	Yan Taisheng,Zhang Yanxia,Zhao Yongheng,et al. explorationofsdssstellardatabasebyautoclass[J]. sciencechinaphysicsmechanicsastronomy,2011,54(9):1717.
APA	Yan Taisheng,Zhang Yanxia,Zhao Yongheng,&Li Ji.(2011).explorationofsdssstellardatabasebyautoclass.sciencechinaphysicsmechanicsastronomy,54(9),1717.
MLA	Yan Taisheng,et al."explorationofsdssstellardatabasebyautoclass".sciencechinaphysicsmechanicsastronomy 54.9(2011):1717.