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 satellite instruments with a typical full-sky 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.
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