用PLATO发现行星：恒星活动过滤算法的比较
Discovering planets with PLATO: Comparison of algorithms for stellar activity filtering
AI总结：
本文比较了四种恒星活动过滤算法及Wotan中两种算法在PLATO模拟光变曲线上的行星凌星探测性能，发现N&L总体最优，但特定场景下其他算法更佳，并指出精细过滤对行星特征描述至关重要。
摘要：
背景。迄今为止，恒星活动是通过凌星光度法探测小型系外行星的主要限制之一。由于这种活动在年轻恒星中增强，传统的过滤算法在探测此类系外行星时可能严重表现不佳。目的。本文旨在比较四个由独立研究小组专门为年轻活动恒星的光变曲线（LC）活动过滤而开发的算法的相对性能，这些算法用于在搜索行星凌星信号之前进行过滤：Notch和LOCoR（N&L）、Young Stars Detrending（YSD）、K2 Systematics Correction（K2SC）和VARLET。我们还将Wotan中实现的两个性能最佳的算法纳入比较，即Tukey双权算法和Huber样条算法。方法。我们对不同类型的行星凌星进行了一系列注入-回收测试，从木星大小到地球大小的行星，分别在圆轨道和偏心轨道上运行。测试在100条模拟的宁静和活跃类太阳恒星的光变曲线上进行，这些恒星将由ESA空间望远镜PLATO观测。结果。我们发现N&L在许多情况下是最佳选择，因为它漏掉的凌星数量最少。然而，如果行星轨道周期与恒星自转周期非常接近，它的表现不佳，尤其是对于小行星，此时双权算法和VARLET算法表现更好。对于数据量大的光变曲线，YSD和Huber样条的组合结果获得最高的回收百分比。过滤算法使我们能够非常精确地估计已探测行星的轨道周期和凌星中心时间，而行星与恒星的半径比在大多数情况下被低估，尤其是在掠射凌星或偏心轨道的情况下。考虑到行星存在的精细过滤对于恰当的行星特征描述是必不可少的。
英文摘要：
Context. To date, stellar activity is one of the main limitations in detecting small exoplanets via transit photometry. Since this activity is enhanced in young stars, traditional filtering algorithms may severely under-perform in detecting such exoplanets. Aims.This paper aims to compare the relative performances of four algorithms developed by independent research groups specifically for the filtering of activity in the light curves (LCs) of young active stars, prior to the search for planetary transit signals: Notch and LOCoR(N&L), Young Stars Detrending(YSD), K2 Systematics Correction(K2SC) and VARLET. We include in the comparison also the two best-performing algorithms implemented in Wotan, namely the Tukey's biweight and the Huber Spline. Methods. We performed a series of injection-retrieval tests of planetary transits of different types, from Jupiter down to Earth-sized planets, moving both on circular and eccentric orbits. The tests were carried out over 100 simulated LCs of both quiet and active solar-like stars that will be observed by the ESA space telescope PLATO. Results. We found that N&L is the best choice in many cases, since it misses the lowest number of transits. However, it under-performs if the planetary orbital period closely matches the stellar rotation period, especially in the case of small planets for which the biweight and VARLET algorithms work better. For LCs with a large number of data, the combined results of YSD and Huber Spline yield the highest recovery percentage. Filtering algorithms allow us to get a very precise estimate of the orbital period and the mid-transit time of the detected planets, while the planet-to-star radius is under-estimated most of the time, especially in the case of grazing transits or eccentric orbits. A refined filtering taking into account the presence of the planet is compulsory for a proper planetary characterization.
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