Colour-Based Disentangling of Mira Variables and Ultra-Cool Dwarfs

Aleksandra Avdeeva, Kefeng Tan, Santosh Joshi, Dana Kovaleva, Harinder P. Singh, Ali Luo, Oleg Malkov
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Abstract

Despite having different astronomical characteristics, the studies of mira variables and ultra-cool dwarfs frequently show similar red colors, which could cause leading to photometric misclassification. This study uses photometric data from the WISE, 2MASS, and Pan-STARRS surveys to construct color-based selection criteria for red dwarfs, brown dwarfs, and Mira variables. On analyzing the color indices, we developed empirical rules that separate these objects with an overall classification accuracy of approximately 91%-92%. While the differentiation between red dwarfs and both Mira variables and brown dwarfs is effective, challenges remain in distinguishing Mira variables from brown dwarfs due to overlapping color indices. The robustness of our classification technique was validated by a bootstrap analysis, highlighting the significance of color indices in large photometric surveys for stellar classification.
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基于颜色的米拉变星和超冷矮星分辨研究
尽管米拉变星和超冷矮星具有不同的天文特征,但对它们的研究却经常显示出相似的红色,这可能会导致光度分类错误。本研究利用WISE、2MASS和Pan-STARRS巡天的测光数据,构建了基于颜色的红矮星、褐矮星和米拉变星的选择标准。通过对颜色指数的分析,我们制定了经验规则,将这些天体区分开来,总体分类准确率约为91%-92%。虽然红矮星与米拉变星和褐矮星之间的区分是有效的,但由于颜色指数的重叠,在区分米拉变星和褐矮星方面仍然存在挑战。我们的分类技术的稳健性通过自举分析得到了验证,突出了大型测光巡天中颜色指数对恒星分类的重要性。
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