PReBeaM for Planck: A Polarized Regularized Beam Deconvolution Map-Making Method

Abstract

We describe a maximum likelihood regularized beam deconvolution map-making algorithm for data from high resolution, polarization sensitive instruments, such as the Planck data set. The resulting algorithm, which we call PReBeaM, is pixel-free and solves for the map directly in spherical harmonic space, avoiding pixelization artifacts. While Fourier methods like ours are expected to work best when applied to smooth, large-scale asymmetric beam systematics (such as far-side lobe effects) we show that our m-truncated spherical harmonic representation of the beam results in negligible reconstruction error -- even for m as small as 4 for a polarized elliptically asymmetric beam. We describe a hybrid OpenMP/MPI parallelization scheme which allows us to store and manipulate the time-ordered data from instruments with arbitrary scanning strategy. Finally, we apply our technique to noisy data and show that it succeeds in removing visible power spectrum artifacts without generating excess noise on small scales.