Forecast B-modes detection at large scales in presence of noise and foregrounds

TL;DR

This paper assesses the detectability of primordial B-mode polarization in the CMB considering noise and foregrounds, emphasizing the importance of component separation and providing a software tool for performance comparison.

Contribution

It introduces a method to estimate errors from component separation and propagates them to B-mode detection, along with a flexible software tool for comparing instrumental and methodological configurations.

Findings

Proper component separation is essential for B-mode detection.

Sensitivity depends on noise levels, foreground residuals, and frequency choices.

The software tool enables performance comparison of different experimental setups.

Abstract

We investigate the detectability of the primordial CMB polarization B-mode power spectrum on large scales in the presence of instrumental noise and realistic foreground contamination. We have worked out a method to estimate the errors on component separation and to propagate them up to the power spectrum estimation. The performances of our method are illustrated by applying it to the instrumental specifications of the Planck satellite and to the proposed configuration for the next generation CMB polarization experiment COrE. We demonstrate that a proper component separation step is required in order achieve the detection of B-modes on large scales and that the final sensitivity to B-modes of a given experiment is determined by a delicate balance between noise level and residual foregrounds, which depend on the set of frequencies exploited in the CMB reconstruction, on the signal-to-noise of each frequency map, and on our ability to correctly model the spectral behavior of the foreground components. We have produced a flexible software tool that allows the comparison of performances on B-mode detection of different instrumental specifications (choice of frequencies, noise level at each frequency, etc.) as well as of different proposed approaches to component separation.