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arXiv 1204.2113astro-ph.SR
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开普勒观测双星。III。局部线性嵌入下Kepler变换二元光变曲线的分类

Kepler Eclipsing Binary Stars. III. Classification of Kepler Eclipsing Binary Light Curves with Locally Linear Embedding

Gal Matijevic, Andrej Prsa, Jerome A. Orosz, William F. Welsh, Steven Bloemen, Thomas Barclay

摘要:

我们提出了一个自动分类的2165 \textit{Kepler}食二进制(EB)的光变曲线,伴随着第二个\textit{Kepler}数据发布。使用局部线性嵌入(一种通用的非线性降维工具)将光变曲线分类为形态类型(分离、半分离、过接触、椭球)。该方法与更广泛使用的主成分分析相关,产生输入数据的低维表示,同时保留局部几何形状,从而保留相邻数据点之间的相似性。我们使用这个属性,以减少一系列的步骤中的一维流形的维数和分类的光变曲线与一个单一的参数,这是一个衡量的“分离”的系统。这种完全自动化的分类与从数据发布中手动确定形态相关,并且还有效地突出显示任何错误分类的对象。一旦定义了低维投影空间,附加光变曲线的分类在可忽略的时间内运行,因此该方法可以用作流水线结构中的全自动分类器。分类器形成\textit{Kepler} EB流水线的一层,其预处理用于基于人工智能的参数估计器的光变曲线。

英文摘要:

We present an automated classification of 2165 \textit{Kepler} eclipsing binary (EB) light curves that accompanied the second \textit{Kepler} data release. The light curves are classified using Locally Linear Embedding, a general nonlinear dimensionality reduction tool, into morphology types (detached, semi-detached, overcontact, ellipsoidal). The method, related to a more widely used Principal Component Analysis, produces a lower-dimensional representation of the input data while preserving local geometry and, consequently, the similarity between neighboring data points. We use this property to reduce the dimensionality in a series of steps to a one-dimensional manifold and classify light curves with a single parameter that is a measure of "detachedness" of the system. This fully automated classification correlates well with the manual determination of morphology from the data release, and also efficiently highlights any misclassified objects. Once a lower-dimensional projection space is defined, the classification of additional light curves runs in a negligible time and the method can therefore be used as a fully automated classifier in pipeline structures. The classifier forms a tier of the \textit{Kepler} EB pipeline that pre-processes light curves for the artificial intelligence based parameter estimator.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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