Photometric Classifications of Evolved Massive Stars: Preparing for the Era of Webb and Roman with Machine Learning
Photometric Classifications of Evolved Massive Stars: Preparing for the Era of Webb and Roman with Machine Learning
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DOI：
10.3847/1538-4357/abf1f2
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发表时间：
2021-02
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通讯作者：
T. Dorn-Wallenstein;J. Davenport;D. Huppenkothen;E. Levesque
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作者：
T. Dorn-Wallenstein;J. Davenport;D. Huppenkothen;E. Levesque
在未来几年，下一代天基红外天文台将显著增加我们对罕见大质量恒星的样本，这是利用现代统计工具和方法在全新环境中测试大质量恒星演化的巨大机会。这样的工作只有在观测到的物体能够被可靠地分类的情况下才有可能。对于更遥远的目标，光谱观测是不可行的，因此我们希望确定机器学习方法是否可以使用宽带红外测光法对大质量恒星进行分类。我们发现支持向量机分类器能够对大质量恒星进行粗分类，并以较高的精度对热星、冷星和发射线星对应的标签进行分类，同时拒绝污染的低质量巨星。值得注意的是，76%的发射线恒星可以在不需要窄带或光谱观测的情况下恢复。我们对约2500个没有现有标签的物体样本进行分类，并识别出14个候选发射在线物体。不幸的是，尽管我们样本中的光度测量精度很高，但我们样本中恒星标签的异质性来源严重阻碍了我们的分类器区分更粒度的恒星类别。最终，目前还不存在大质量恒星的大而均匀的标记样本。如果不大力对进化的大质量恒星进行分类——这在大型全天空光谱调查的现有数据下是可行的——现有数据集标记上的缺陷将阻碍利用下一代空间天文台的努力。
In the coming years, next-generation space-based infrared observatories will significantly increase our samples of rare massive stars, representing a tremendous opportunity to leverage modern statistical tools and methods to test massive stellar evolution in entirely new environments. Such work is only possible if the observed objects can be reliably classified. Spectroscopic observations are infeasible with more distant targets, and so we wish to determine whether machine-learning methods can classify massive stars using broadband infrared photometry. We find that a Support Vector Machine classifier is capable of coarsely classifying massive stars with labels corresponding to hot, cool, and emission-line stars with high accuracy, while rejecting contaminating low-mass giants. Remarkably, 76% of emission-line stars can be recovered without the need for narrowband or spectroscopic observations. We classify a sample of ∼2500 objects with no existing labels and identify 14 candidate emission-line objects. Unfortunately, despite the high precision of the photometry in our sample, the heterogeneous origins of the labels for the stars in our sample severely inhibit our classifier from distinguishing classes of stars with more granularity. Ultimately, no large and homogeneously labeled sample of massive stars currently exists. Without significant efforts to robustly classify evolved massive stars—which is feasible given existing data from large all-sky spectroscopic surveys—shortcomings in the labeling of existing data sets will hinder efforts to leverage the next generation of space observatories.