Determination of Polarization Angles in CMB Experiments and Application to CMB Component Separation Analyses

TL;DR

This paper presents a fast, iterative maximum likelihood method to accurately determine polarization angles in CMB experiments, reducing systematics that obscure primordial B-mode signals, and demonstrates its effectiveness in component separation analyses.

Contribution

Introduces a novel iterative likelihood-based method for estimating polarization angles, improving calibration accuracy in CMB polarization measurements.

Findings

The method accurately estimates polarization angles for each frequency.

Applying the method reduces systematic residuals in component separation.

Systematic residuals are mitigated to about 1% at the power spectrum level.

Abstract

The new generation of CMB polarization experiments will reach limits of sensitivity never achieved before to detect the primordial B-mode signal. However, all these efforts will be futile if we lack a tight control of systematics. Here, we focus on the systematic that arises from the uncertainty on the calibration of polarization angles. Miscalibrated polarization angles induce a mixing of E- and B-modes that obscures the primordial B-mode signal. We introduce an iterative angular power spectra maximum likelihood-based method to calculate polarization angles from the multi-frequency signal. The basis behind this methodology grounds on nulling the EB power spectra. To simplify the likelihood, we assume that the rotation angles are small (<6 deg) and, the maximum likelihood solution for the rotation angles is obtained by applying an iterative process where the covariance matrix does not depend on the angles per iteration, i.e., the rotation angles are fixed to the estimated angles in the previous iteration. With these assumptions, we obtain an analytical linear system which leads to a very fast computational implementation. We show that with this methodology we are able to determine the rotation angle for each frequency with sufficiently good accuracy. To prove the latter point we perform component separation analyses using the parametric component separation method B-SeCRET with two different approaches. In the first approach we apply the B-SeCRET pipeline to the signal de-rotated with the estimation of the angles, while in the second, the rotation angles are treated as model parameters using the estimation of the angles as a prior information. We obtain that the rotation angles estimations improve after applying the second approach, and show that the systematic residuals due to the non-null calibration polarization angles are mitigated to the order of a 1% at the power spectrum level.