Recovering unbiased CMB polarization maps using modern ground-based experiments with minimal assumptions about atmospheric emission

Abstract

We present a study of unbiased reconstruction of cosmic microwave background (CMB) polarization maps from data collected by modern ground-based observatories. Atmospheric emission is a major source of correlated noise in such experiments, complicating the recovery of faint cosmological signals. We consider estimators that require minimal assumptions about unpolarized atmospheric emission properties, instead exploiting hardware solutions commonly implemented in modern instruments, such as pairs of orthogonal antennas in each focal plane pixel, and polarization signal modulation via a continuously rotating half-wave plate (HWP). We focus on two techniques: (i) statistical down-weighting of low-frequency atmospheric signals, and (ii) pair-differencing (PD), which involves differencing signals collected by two detectors in the same focal plane pixel. We compare their performance against the idealized case where the atmospheric signal is perfectly known and cleanly subtracted. We show that PD can be derived from maximum likelihood principles under general assumptions about the atmospheric signal, optimizing map sensitivity. In the absence of instrumental systematics but with reasonable detector noise variations, PD yields polarized sky maps with noise levels only slightly worse than the ideal case. While down-weighting could match this performance, it requires highly accurate atmospheric models that are not readily available. PD performance is affected by instrumental systematics, particularly those leaking atmospheric signal to the difference time stream. However, effects like gain mismatch are efficiently mitigated by a rotating HWP, making PD a competitive, robust, and efficient solution for CMB polarization mapmaking without atmospheric modeling.