Removal of Spectro-Polarimetric Fringes by 2D PCA

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Monday, February 25, 2019

We investigate the application of 2-dimensional Principal Component Analysis (2D PCA) to the problem of removal of polarization fringes from spectro-polarimetric data sets.

Graph depicting a Stokes Q map around the the HI H-alpha line at 656 nm
Original (top), reconstructed (center), and residual of the reconstruction (bottom) for one frame of a Stokes Q map around the the HI H-alpha line at 656 nm. The map (frequency ordered) was taken with the DST/SPINOR instrument, and contains a total of 60 frames. The Stokes Q signal was reconstructed after a selective Fourier filtering of the contribution from the fringe basis vectors, after a TP-PCA of the full map, and successive transformation of the PCA basis.

We show how the transformation of the PCA basis through a series of carefully chosen rotations allows to confine polarization fringes (and other stationary instrumental effects) to a reduced set of basis "vectors," which at the same time are largely devoid of the spectral signal from the observed target. It is possible to devise algorithms for the determination of the optimal series of rotations of the PCA basis, thus opening the possibility of automating the procedure of de-fringing of spectro-polarimetric data sets. We compare the performance of the proposed method with the more traditional Fourier filtering of Stokes spectra.

Publication Name: The Astrophysical Journal

First HAO Author's Name: Roberto Casini

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