Identifying Carbon stars from the LAMOST pilot survey with the efficient manifold ranking algorithm

Identifying Carbon stars from the LAMOST pilot survey with the efficient manifold ranking algorithm
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DOI:
10.1088/1674-4527/15/10/005
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发表时间:
2015-10
影响因子:
1.8
通讯作者:
Jian-min Si;Yin-Bi Li;A. Luo;Liangping Tu;Zhixin Shi;Jian-Na Zhang;P. Wei;Gang Zhao;Yihong Wu;Fuchao Wu;Yongheng Zhao
Jian-min Si;Yin-Bi Li;A. Luo;Liangping Tu;Zhixin Shi;Jian-Na Zhang;P. Wei;Gang Zhao;Yihong Wu;Fuchao Wu;Yongheng Zhao
中科院分区:
物理与天体物理3区
文献类型:
--
作者:
Jian-min Si;Yin-Bi Li;A. Luo;Liangping Tu;Zhixin Shi;Jian-Na Zhang;P. Wei;Gang Zhao;Yihong Wu;Fuchao Wu;Yongheng Zhao

文献摘要

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碳星是优秀的星系运动示踪剂,可以作为可行的标准烛光,因此在大量光谱中对其进行自动搜索是值得的。本文将高效流形排序算法应用于大空域多目标光纤光谱望远镜(LAMOST)先导巡天中的碳星搜索,并通过4个测试实验对算法的性能和鲁棒性进行了全面验证。通过这个算法,我们一共发现了183颗碳星,其中158颗是新发现的。根据不同的光谱特征,我们的碳星分为58颗C-H星、11颗C-H星候选星、56颗C-R星、10颗C-R星候选星、30颗C-N星候选星、3颗C-N星候选星和4颗C-J星。还有10个天体由于光谱质量低而没有光谱类型,还有一个由白矮星和碳星组成的复合光谱。应用支持向量机算法,在J -H与H - Ks颜色图中得到线性最优分类平面,可用于区分C-H和C-N星的J -H和H - Ks颜色。此外,我们确定了18颗具有相对高固有运动的矮碳星,并通过与星系演化探测器的数据交叉匹配,发现3颗具有FUV探测的碳星可能有光学不可见的伴星。最后,我们利用Northern Sky Variability Survey、Catalina Sky Survey和LINEAR Variability数据库对4颗变碳星进行了探测。根据用正弦函数拟合光曲线得出的周期和振幅,其中三颗可能是半规则变星,一颗可能是米拉变星。
Carbon stars are excellent kinematic tracers of galaxies and can serve as a viable standard candle, so it is worthwhile to automatically search for them in a large amount of spectra. In this paper, we apply the efficient manifold ranking algorithm to search for carbon stars from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) pilot survey, whose performance and robustness are verified comprehensively with four test experiments. Using this algorithm, we find a total of 183 carbon stars, and 158 of them are new findings. According to different spectral features, our carbon stars are classified as 58 C-H stars, 11 C-H star candidates, 56 C-R stars, ten C-R star candidates, 30 C-N stars, three C-N star candidates, and four C-J stars. There are also ten objects which have no spectral type because of low spectral quality, and a composite spectrum consisting of a white dwarf and a carbon star. Applying the support vector machine algorithm, we obtain the linear optimum classification plane in the J – H versus H – Ks color diagram which can be used to distinguish C-H from C-N stars with their J – H and H – Ks colors. In addition, we identify 18 dwarf carbon stars with their relatively high proper motions, and find three carbon stars with FUV detections likely have optical invisible companions by cross matching with data from the Galaxy Evolution Explorer. In the end, we detect four variable carbon stars with the Northern Sky Variability Survey, the Catalina Sky Survey and the LINEAR variability databases. According to their periods and amplitudes derived by fitting light curves with a sinusoidal function, three of them are likely semiregular variable stars and one is likely a Mira variable star.