为探测类地行星凌日模拟类太阳变化。II）三点建模、谐波函数拟合、迭代非线性滤波和滑动矩形波滤波的性能
Modelling solar-like variability for the detection of Earth-like planetary transits. II) Performance of the three-spot modelling, harmonic function fitting, iterative non-linear filtering and sliding boxcar filtering
摘要：
我们提出了一个比较的四种方法的过滤太阳一样的变化，以提高效率的检测类地行星过境的盒形过境发现算法。这些滤波方法中的两种是谐波拟合方法和迭代非线性滤波器，分别与Box最小二乘（BLS）和Box最大似然算法相结合，在CoRoT联盟内部组织的第一次检测盲测期间表现出最佳性能。第三种方法，3点模型，是一个简化的物理模型的太阳一样的变化和第四个是一个简单的滑动boxcar过滤器。我们应用蒙特卡罗方法模拟了大量的150天的光变曲线（如CoRoT长期运行）不同的行星半径，轨道周期，时代的第一次过境和标准偏差的光子散粒噪声。恒星的变化是由太阳总辐照度的变化给出的，在接近太阳活动周期23的最大值时观测到。在过滤太阳变率之后，通过BLS算法搜索凌日。我们发现，在选择合适的窗口时，迭代非线性滤波器是类太阳恒星光变曲线的最佳滤波方法。由于该滤波器的性能关键取决于其窗口的长度，我们指出，窗口必须尽可能长，根据恒星的磁活动水平。我们展示了一个自动的方法来选择从光变曲线的功率谱的滤波窗口的扩展。迭代非线性滤波器，当与其窗口的适当选择一起使用时，具有比拟合类似太阳的变化的更复杂和计算密集的方法（如200谐波拟合或3点模型）更好的性能。
英文摘要：
We present a comparison of four methods of filtering solar-like variability to increase the efficiency of detection of Earth-like planetary transits by means of box-shaped transit finder algorithms. Two of these filtering methods are the harmonic fitting method and the iterative non-linear filter that, coupled respectively with the Box Least-Square (BLS) and Box Maximum-Likelihood algorithms, demonstrated the best performance during the first detection blind test organized inside the CoRoT consortium. The third method, the 3-spot model, is a simplified physical model of Sun-like variability and the fourth is a simple sliding boxcar filter. We apply a Monte Carlo approach by simulating a large number of 150-day light curves (as for CoRoT long runs) for different planetary radii, orbital periods, epochs of the first transit and standard deviations of the photon shot noise. Stellar variability is given by the Total Solar Irradiance variations as observed close to the maximum of solar cycle 23. After filtering solar variability, transits are searched for by means of the BLS algorithm. We find that the iterative non-linear filter is the best method to filter light curves of solar-like stars when a suitable window can be chosen. As the performance of this filter depends critically on the length of its window, we point out that the window must be as long as possible, according to the magnetic activity level of the star. We show an automatic method to choose the extension of the filter window from the power spectrum of the light curves. The iterative non-linear filter, when used with a suitable choice of its window, has a better performance than more complicated and computationally intensive methods of fitting solar-like variability, like the 200-harmonic fitting or the 3-spot model.
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