论文标题
通过虚拟天文台工具来识别新的热门二进制系统
Identification of new hot subdwarf binary systems by means of Virtual Observatory tools
论文作者
论文摘要
热分尺寸的二元分数的估计是阐明提议在红色巨型分支阶段解释氢信封丢失的不同演化方案的关键。在本文中,我们分析了最新且全面的目录中包含的热分子的光谱能量分布,目的是识别同伴。我们的方法表明,该研究中使用的光度标准优越的性能,根据其光谱能量分布将202个对象错误地分类为二进制,并找到269个新二进制文件。在3186个对象的初始样本中,我们将2469分为单个对象,将615分为二进制热点。其余的物体(102)未分类,因为它们的光谱能量分布不足,而质量质量差较差。计算了192张单打和42个二进制文件的有效温度,发光度和半径。它们,尤其是二元样品,构成了一个出色的数据集,以进一步进行更仔细的光谱分析,可以为最短的周期系统提供化学组成,质量,年龄,旋转特性或反射效应的详细值。在本文中获得的结果将用作即将上映的工作的参考,我们旨在使用基于人工智能的技术概括二进制和单个热门subdwarf分类。
The estimation of the binary fraction of hot subdwarfs is key to shed light on the different evolution scenarios proposed to explain the loss of the hydrogen envelope during the red giant branch phase. In this paper we analyse the spectral energy distribution of the hot subdwarfs included in a recent and comprehensive catalogue with the aim of identifying companions. Our methodology shows a performance superior to the photometric criteria used in that study, identifying 202 objects wrongly classified as binaries according to their spectral energy distributions, and finding 269 new binaries. Out of an initial sample of 3186 objects, we classified 2469 as single and 615 as binary hot subdwarfs. The rest of the objects (102) were not classified because of their inadequate spectral energy distribution fitting due, in turn, to poor quality photometry. Effective temperatures, luminosities and radii were computed for 192 singles and 42 binaries. They, in particular the binary sample, constitute an excellent dataset to further perform a more careful spectroscopic analysis that could provide detailed values for the chemical composition, masses, ages, rotation properties or reflection effects for the shortest-period systems. The results obtained in this paper will be used as a reference for a forthcoming work where we aim to generalize binary and single hot subdwarf classification using Artificial Intelligence-based techniques.