论文标题
在大型调查中恢复变量星:ea $ _ {\ rm up} $ algol-type类在Catalina调查中
Recovering variable stars in large surveys: EA$_{\rm up}$ Algol-type class in the Catalina Survey
论文作者
论文摘要
Algol Eclipsing Binaries(EAS)的发现和表征为更好地了解低质量恒星的结构和演变提供了机会。然而,由于观测值之间的分离通常大于日食的持续时间,因此大多数当前光度测验的节奏阻碍了EAS的检测,因此在Eclipses上很少发现测量值。即使将这些对象检测为变量,如果在搜索工具中未使用适当的过采样因子,则可能会错过它们的周期。在本文中,我们应用这种方法来查找Catalina实时瞬态调查(CRT)在EAS中分类的恒星周期,因为EAS具有未知时期(EA $ _ {\ rm UP} $)。结果,确定了$ \ sim 56 \%$的周期。八个对象被识别为低质量二进制系统,并用Wilson \&Devinney合成代码与蒙特卡洛马尔可夫链优化程序结合使用。计算的质量和半径与理论模型一致,没有显示膨胀半径的证据。本文是旨在在大型调查中识别可疑二进制系统的系列中的第一篇。
The discovery and characterization of Algol eclipsing binaries (EAs) provide an opportunity to contribute for a better picture of the structure and evolution of low-mass stars. However, the cadence of most current photometric surveys hinders the detection of EAs since the separation between observations is usually larger than the eclipse(s) duration and hence few measurements are found at the eclipses. Even when those objects are detected as variable, their periods can be missed if an appropriate oversampling factor is not used in the search tools. In this paper, we apply this approach to find the periods of stars cataloged in the Catalina Real-Time Transient Survey (CRTS) as EAs having unknown period (EA$_{\rm up}$). As a result, the periods of $\sim 56\%$ of them were determined. Eight objects were identified as low-mass binary systems and modeled with the Wilson \& Devinney synthesis code combined with a Monte-Carlo Markov Chain optimization procedure. The computed masses and radii are in agreement with theoretical models and show no evidence of inflated radii. This paper is the first of a series aiming to identify suspected binary systems in large surveys.