TRUFAS，一种基于小波的行星凌日快速检测算法
TRUFAS, a wavelet based algorithm for the rapid detection of planetary transits
摘要：
目的：我们描述了一个快速，强大的自动检测算法，TRUFAS，并将其应用于数据，预计从CoRoT任务。研究方法：提出的在光变曲线中检测行星凌日的方法分为两个步骤：1）对去趋势光变曲线进行连续小波变换，后验选择用于凌日检测的最佳尺度，以及2）在所选择的小波变换中进行周期搜索。光变曲线的去趋势是基于傅立叶滤波或离散小波变换。TRUFAS要求数据中至少存在3个过境事件。结果如下：所提出的算法被证明是可靠和快速地识别已被包括在一组标准的999光变曲线，模拟CoRoT数据的过境。光变曲线的预处理和小波变换尺度的选择对TRUFAS的结果影响很小。结论：TRUFAS是一种强大而快速的凌日检测算法，特别适合分析来自太空或地面实验的大量数据，这些数据具有足够长的持续时间，使目标行星产生多个凌日事件。
英文摘要：
Aims: We describe a fast, robust and automatic detection algorithm, TRUFAS, and apply it to data that are being expected from the CoRoT mission. Methods: The procedure proposed for the detection of planetary transits in light curves works in two steps: 1) a continuous wavelet transformation of the detrended light curve with posterior selection of the optimum scale for transit detection, and 2) a period search in that selected wavelet transformation. The detrending of the light curves are based on Fourier filtering or a discrete wavelet transformation. TRUFAS requires the presence of at least 3 transit events in the data. Results: The proposed algorithm is shown to identify reliably and quickly the transits that had been included in a standard set of 999 light curves that simulate CoRoT data. Variations in the pre-processing of the light curves and in the selection of the scale of the wavelet transform have only little effect on TRUFAS' results. Conclusions: TRUFAS is a robust and quick transit detection algorithm, especially well suited for the analysis of very large volumes of data from space or ground-based experiments, with long enough durations for the target-planets to produce multiple transit events.
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