论文标题
KELT调查中的长期高幅度红色变量
Long-Period High-Amplitude Red Variables in the KELT Survey
论文作者
论文摘要
我们提供了4,132个Mira样变量（长时间的红色变量和高振幅）的样本，在极少的望远镜（KELT）调查中。其中814是新检测。我们使用2种颜色来识别候选渐近巨型分支（AGB）恒星。我们测试了样品和使用Lomb-Scargle之间的光度变异性，以确定可变样品的周期性。我们选择了使用随机森林分类器的变量高幅度和强烈的周期性行为。在4,132个Mira样变量的样本中，我们估计70％是Miras，而30％是半规则（SR）变量。我们还采用（W_ {RP} -W_ {K_S}）与（J -K_S）颜色（Lebzelter等人，2018）的方法来区分O -Rich和C-富含C的Miras，并发现它是2种颜色的改进。
We present a sample of 4,132 Mira-like variables (red variables with long periods and high amplitudes) in the Kilodegree Extremely Little Telescope (KELT) survey. Of these, 814 are new detections. We used 2MASS colors to identify candidate asymptotic giant branch (AGB) stars. We tested for photometric variability among the sample and used Lomb-Scargle to determine the periodicity of the variable sample. We selected variables with high amplitudes and strong periodic behavior using a Random Forest classifier. Of the sample of 4,132 Mira-like variables, we estimate that 70% are Miras, and 30% are semi-regular (SR) variables. We also adopt the method of using (W_{RP} - W_{K_s}) vs. (J - K_s) colors (Lebzelter et al. 2018) in distinguishing between O-rich and C-rich Miras and find it to be an improvement over 2MASS colors.
