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arXiv 1001.0507astro-ph.SR
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开普勒航天任务星震学计划中变星的自动分类

Automated classification of variable stars in the asteroseismology program of the Kepler space mission

J. Blomme, J. Debosscher, J. De Ridder, C. Aerts, R. L. Gilliland, J. Christensen-Dalsgaard, H. Kjeldsen, T. M. Brown, W. J. Borucki, D. Koch, J. M. Jenkins, D.… 展开作者

J. Blomme, J. Debosscher, J. De Ridder, C. Aerts, R. L. Gilliland, J. Christensen-Dalsgaard, H. Kjeldsen, T. M. Brown, W. J. Borucki, D. Koch, J. M. Jenkins, D. W. Kurtz, D. Stello, I. R. Stevens, M. D. Suran, A. Derekas

摘要:

我们提出的监督分类方法的应用程序的开普勒Q1长节奏光变曲线的子样本的2288颗恒星在asteroseismology计划的任务测量的第一个结果。这些方法最初是在CoRoT和盖亚空间任务的框架内开发的,能够以可靠的方式识别最常见的恒星变化类型。许多新的变星已经被发现,其中很大一部分是在发射前未知的食/椭球双星。比较我们的分类从开普勒数据和发射前类的基础上从地面的数据,表明后者需要显着的改进。开普勒数据的噪声特性进行了比较的CoRoT卫星的系外行星计划。我们发现开普勒在点对点散射中将CoRoT提高了2到2.3倍。

英文摘要:

We present the first results of the application of supervised classification methods to the Kepler Q1 long-cadence light curves of a subsample of 2288 stars measured in the asteroseismology program of the mission. The methods, originally developed in the framework of the CoRoT and Gaia space missions, are capable of identifying the most common types of stellar variability in a reliable way. Many new variables have been discovered, among which a large fraction are eclipsing/ellipsoidal binaries unknown prior to launch. A comparison is made between our classification from the Kepler data and the pre-launch class based on data from the ground, showing that the latter needs significant improvement. The noise properties of the Kepler data are compared to those of the exoplanet program of the CoRoT satellite. We find that Kepler improves on CoRoT by a factor 2 to 2.3 in point-to-point scatter.

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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