论文标题
主要组件分析以纠正数据系统学。案例研究：K2光曲线
Principal Component Analysis to correct data systematics. Case study: K2 light curves
论文作者
论文摘要
仪器数据受系统效应的影响，这些效应主导了错误，在搜索小信号时可能会相关。 K2任务是开普勒任务的随访，在两个反应轮失败之后，其稳定性在光曲线中的系统效率强劲上升并降低了光度法精度。在这项工作中，我们开发了一种通用方法，可以从一组光曲线中删除与时间相关的系统学，该曲线已应用于K2数据。该方法使用主组件分析来检索由于系统学的光曲线之间的相关性，并在不知道数据本身以外的任何信息的情况下消除其效果。我们已将该方法应用于Mikulski档案库中的所有K2广告系列，并测试了该程序的有效性及其在维护几个过渡和远程二进制文件上保存天体物理信号方面的能力。这项工作的一种产物是沿沿黄道平面的稳定来源的识别，该量可以用作即将到来的大气遥感系外行星大调查任务的光度校准器。
Instrumental data are affected by systematic effects that dominate the errors and can be relevant when searching for small signals. This is the case of the K2 mission, a follow up of the Kepler mission, that, after a failure on two reaction wheels, has lost its stability properties rising strongly the systematics in the light curves and reducing its photometric precision. In this work, we have developed a general method to remove time related systematics from a set of light curves, that has been applied to K2 data. The method uses the Principal Component Analysis to retrieve the correlation between the light curves due to the systematics and to remove its effect without knowing any information other than the data itself. We have applied the method to all the K2 campaigns available at the Mikulski Archive for Space Telescopes, and we have tested the effectiveness of the procedure and its capability in preserving the astrophysical signal on a few transits and on eclipsing binaries. One product of this work is the identification of stable sources along the ecliptic plane that can be used as photometric calibrators for the upcoming Atmospheric Remote-sensing Exoplanet Large-survey mission.
