CoRoT数据简化示例
CoRoT Data Reduction By Example
摘要：
迄今为止，为CoRoT N2数据产品公布的数据简化技术主要针对太阳系外行星的探测。由于整个数据集已经发布，因此需要特定的算法来正确处理来自CoRoT的光变曲线。虽然只有未标记的数据点必须选择进行科学处理，但某些标记可能会重新考虑。通过应用一维毛毛雨算法可以实现数据的减少以及提高信噪比。间隙可以由线性内插数据填充，而不会损害频谱。从CoRoT颜色通道导出的幅值可以用于导出关于目标的附加信息。根据需要，频域中的各种滤波器可以去除红噪声背景或高频噪声。自相关函数或最小二乘周期图是识别周期信号的合适方法。这里描述的方法并不严格限于CoRoT数据，也可以应用于开普勒数据或即将到来的柏拉图任务。
英文摘要：
Data reduction techniques published so far for the CoRoT N2 data product were targeted primarily on the detection of extrasolar planets. Since the whole dataset has been released, specific algorithms are required to process the lightcurves from CoRoT correctly. Though only unflagged datapoints must be chosen for scientific processing, some flags might be reconsidered. The reduction of data along with improving the signal-to-noise ratio can be achieved by applying a one dimensional drizzle algorithm. Gaps can be filled by linear interpolated data without harming the frequency spectrum. Magnitudes derived from the CoRoT color channels might be used to derive additional information about the targets. Depending on the needs, various filters in the frequency domain remove either the red noise background or high frequency noise. The autocorrelation function or the least squares periodogram are appropriate methods to identify periodic signals.The methods described here are not strictly limited to CoRoT data but may also be applied on Kepler data or the upcoming Plato mission.
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