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Unsupervised classification of eclipsing binary light curves through k-medoids clustering

机译:通过K-METOIDS聚类未经监督的二元光曲线分类

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摘要

This paper proposes k-medoids clustering method to reveal the distinct groups of 1318 variable stars in the Galaxy based on their light curves, where each light curve represents the graph of brightness of the star against time. To overcome the deficiencies of subjective traditional classification, we separate the stars more scientifically according to their geometrical configuration and show that our approach outperforms the existing classification schemes in astronomy. It results in two optimum groups of eclipsing binaries corresponding to bright, massive systems and fainter, less massive systems.
机译:本文提出了K-yemoids聚类方法,以揭示基于其光曲线的星系中的1318个变量恒星的不同组,其中每个光曲线代表明星的亮度与时间的图表。为了克服主观传统分类的缺陷,我们根据他们的几何配置将恒星分开,并表明我们的方法优于天文学中现有的分类方案。它导致两组最佳的蚀射出二进制文件,对应于明亮,大规模的系统和较大,较小的大量系统。

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