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    A Circular Statistical Method for Extracting Rotation Measures

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    We propose a new method for the extraction of Rotation Measure from spectral polarization data. The method is based on maximum likelihood analysis and takes into account the circular nature of the polarization data. The method is unbiased and statistically more efficient than the standard χ2\chi^2 procedure. We also find that the method is computationally much faster than the standard χ2\chi^2 procedure if the number of data points are very large.Comment: 17 pages, 5 figure
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