Transit shapes and self-organizing maps as a tool for ranking planetary candidates: application to Kepler and K2
Transit shapes and self-organizing maps as a tool for ranking planetary candidates: application to Kepler and K2
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DOI：
10.1093/mnras/stw2881
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发表时间：
2017-03-01
影响因子：
4.8
通讯作者：
Santerne, A.
中科院分区：
文献类型：
--
作者：
Armstrong, D. J.;Pollacco, D.;Santerne, A.
行星搜寻调查的一个关键步骤是在望远镜资源有限的情况下选择最佳候选者进行后续观测。这通常是由人的“目测”，一个耗时和统计尴尬的过程。在这里，我们提出了一种新的快速机器学习技术，可以将真正的行星信号与天体物理误报分开。我们使用自组织映射（SOM）来研究开普勒和K2已知和候选行星的凌日形状。我们发现，SOM能够区分已知的行星与已知的误报，成功率为87.0%，仅使用过境形状。此外，它们不要求在使用前处置任何候选物，这意味着它们可以在使命寿命的早期使用。开发了一种使用SOM对候选物进行分类的方法，并将其应用于开普勒兴趣对象（KOI）列表中以前未分类的成员以及K2使命的候选物。该方法非常快，在典型的笔记本电脑上运行整个KOI列表只需几分钟。我们使用新的SOM或在本工作中创建的SOM来公开执行分类的PYTHON代码。SOM技术代表了一种新的行星候选名单排名方法，可以单独使用，也可以作为更大的自动审查代码的一部分。
A crucial step in planet hunting surveys is to select the best candidates for follow-up observations, given limited telescope resources. This is often performed by human ' eyeballing ', a time consuming and statistically awkward process. Here, we present a new, fast machine learning technique to separate true planet signals from astrophysical false positives. We use self-organizing maps (SOMs) to study the transit shapes of Kepler and K2 known and candidate planets. We find that SOMs are capable of distinguishing known planets from known false positives with a success rate of 87.0 per cent, using the transit shape alone. Furthermore, they do not require any candidate to be dispositioned prior to use, meaning that they can be used early in a mission's lifetime. A method for classifying candidates using a SOM is developed, and applied to previously unclassified members of the Kepler Objects of Interest (KOI) list as well as candidates from the K2 mission. The method is extremely fast, taking minutes to run the entire KOI list on a typical laptop. We make PYTHON code for performing classifications publicly available, using either new SOMs or those created in this work. The SOM technique represents a novel method for ranking planetary candidate lists, and can be used both alone or as part of a larger autovetting code.