RM CLEAN性能测试及卡方值评价
Performance test of RM CLEAN and its evaluation with chi-square value
摘要：
RM CLEAN是一种从观测到的极化谱重建宇宙磁场和极化源沿视线分布的标准方法。这种方法类似于孔径综合射电望远镜图像的CLEAN算法，但不清楚RM CLEAN在什么情况下工作得很好。在本文中，我们评估RM CLEAN的性能，通过模拟位于同一LOS的两个紧凑的源的光谱偏振观测，系统地改变相对初始偏振角和法拉第深度。特别是，我们专注于如果这两个偏振源可以解决在法拉第深度空间和如何以及源参数可以估计。我们证实了以前的研究，即两个源不能解决时，他们是密切位于法拉第深度空间的相对初始偏振角的特定值。此外，我们还计算了偏振光谱模拟数据与RM CLEAN数据之间拟合的卡方值。然后我们发现，卡方值并不总是显着大，即使RM CLEAN给出错误的结果。
英文摘要：
RM CLEAN is a standard method to reconstruct the distribution of cosmic magnetic fields and polarized sources along the line of sight (LOS) from observed polarization spectrum. This method is similar to the CLEAN algorithm for aperture synthesis radio telescope images but it is rather unclear in what cases RM CLEAN works well. In this paper, we evaluate the performance of RM CLEAN by simulating spectro-polarimetric observations of two compact sources located in the same LOS, varying the relative initial polarization angle and Faraday depth systematically. Especially, we focus on if the two polarized sources can be resolved in the Faraday depth space and how well the source parameters can be estimated. We confirm the previous studies that two sources cannot be resolved when they are closely located in the Faraday depth space for specific values of the relative initial polarization angle. Further, we calculate the chi-square value for the fit between the mock data of polarization spectrum and the one from RM CLEAN. Then we find that the chi-squared value is not always significantly large even when RM CLEAN gives wrong results.
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