2XMMi- DR3/SDSS-DR8互相关样本的统计研究
Statistical Study of 2XMMi-DR3/SDSS-DR8 Cross-correlation Sample
摘要：
交叉相关的XMM-Newton 2XMMi-DR 3目录与斯隆数字巡天（SDSS）数据发布8，我们获得了最大的X射线/光学目录之一，并探讨在多维光度参数空间中的各类X射线发射体的分布。类星体和星系占据着不同的区域，而恒星则散布在其中。但X射线活动星在光谱类型上有一定的分布规律。恒星的类型越早，发出的X射线就越强。在g-r-r-i图中，X射线活跃星的分布与大多数恒星相似。在SDSS光谱分类识别样本的基础上，采用随机森林算法进行自动分类。结果表明，类星体和星系的分类准确率之和超过93.0%，而X射线发射星的分类准确率仅为45.3%。换句话说，很容易区分类星体和星系，但很难区分X射线活动恒星和类星体和星系。如果我们想提高自动分类的准确性，有必要增加X射线发射星的数量，因为大多数X射线发射源是类星体和星系。这里获得的结果将用于大天区多目标光纤光谱望远镜（LAMOST，也称为郭守敬望远镜）进行的光谱调查，这是一个由中国科学院国家天文台运营的中国国家科学研究设施。
英文摘要：
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 X-ray emitting. X-ray active stars have a similar distribution to most of 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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
