Iterative destriping and photometric calibration for Planck-HFI, polarized, multi-detector map-making

TL;DR

This paper introduces an iterative destriping and calibration method for Planck-HFI data to produce accurate polarized sky maps, effectively reducing residual errors and achieving high calibration precision.

Contribution

It presents a novel iterative scheme combining destriping and absolute calibration for Planck-HFI data, improving map accuracy and residual control in polarized measurements.

Findings

Residuals are negligible for intensity maps at l > 50

Residuals for Q and U maps are smaller than white noise at l > 50

Calibration precision is around a few 10^-4 with minimal systematic bias

Abstract

We present an iterative scheme designed to recover calibrated I, Q, and U maps from Planck-HFI data using the orbital dipole due to the satellite motion with respect to the Solar System frame. It combines a map reconstruction, based on a destriping technique, juxtaposed with an absolute calibration algorithm. We evaluate systematic and statistical uncertainties incurred during both these steps with the help of realistic, Planck-like simulations containing CMB, foreground components and instrumental noise, and assess the accuracy of the sky map reconstruction by considering the maps of the residuals and their spectra. In particular, we discuss destriping residuals for polarization sensitive detectors similar to those of Planck-HFI under different noise hypotheses and show that these residuals are negligible (for intensity maps) or smaller than the white noise level (for Q and U Stokes maps), for l > 50. We also demonstrate that the combined level of residuals of this scheme remains comparable to those of the destriping-only case except at very low l where residuals from the calibration appear. For all the considered noise hypotheses, the relative calibration precision is on the order of a few 10e-4, with a systematic bias of the same order of magnitude.