Detection and Removal of B-mode Dust Foregrounds with Signatures of Statistical Anisotropy

TL;DR

This paper explores using statistical anisotropy signatures of galactic dust B-modes to distinguish them from primordial inflationary signals in CMB polarization data, proposing methods to detect residual dust contamination and improve foreground cleaning.

Contribution

It extends anisotropy estimators to forecast their effectiveness in identifying dust residuals and demonstrates their potential for constructing dust B-mode maps for cleaning.

Findings

Detect residual dust levels of r~0.001 at 2σ with anisotropy estimators.

Anisotropy estimators can serve as powerful null-tests for dust contamination.

Method shows potential for constructing dust B-mode maps to aid in foreground removal.

Abstract

Searches for inflationary gravitational wave signals in the CMB B-mode polarisation are expected to reach unprecedented power over the next decade. A major difficulty in these ongoing searches is that galactic foregrounds such as dust can easily mimic inflationary signals. Though typically foregrounds are separated from primordial signals using the foregrounds' different frequency dependence, in this paper we investigate instead the extent to which the galactic dust B-modes' statistical anisotropy can be used to distinguish them from inflationary B-modes, building on the work of Kamionkowski and Kovetz (2014). In our work, we extend existing anisotropy estimators and apply them to simulations of polarised dust to forecast their performance for future experiments. Considering the application of this method as a null-test for dust contamination to CMB-S4, we find that we can detect residual dust levels corresponding to $r\sim0.001$ at $2\sigma$, which implies that statistical anisotropy estimators will be a powerful diagnostic for foreground residuals (though our results show some dependence on the dust simulation used). Finally, considering applications beyond a simple null test, we demonstrate how anisotropy statistics can be used to construct an estimate of the dust B-mode map, which could potentially be used to clean the B-mode sky.