$B$-sure I: Minkowski functionals as robustness test for tensor-to-scalar ratio detection from CMB observations

TL;DR

This paper evaluates Minkowski functionals as a robustness test for detecting primordial B-mode signals in CMB data, finding they are often insufficient to identify foreground residuals that bias tensor-to-scalar ratio estimates.

Contribution

It introduces a novel application of Minkowski functionals to assess foreground contamination effects on B-mode polarization detection in CMB observations.

Findings

Minkowski functionals often fail to detect non-Gaussianity from foreground residuals.

In about 26% of simulations, MFs flagged non-Gaussianity, but missed it in 74%.

More advanced statistics are needed for reliable null tests in future CMB experiments.

Abstract

The detection of primordial $B$-mode polarisation of the Cosmic Microwave Background (CMB) is a major observational goal in modern Cosmology, offering a potential window into inflationary physics through the measurement of the tensor-to-scalar ratio $r$. However, the presence of Galactic foregrounds poses significant challenges, possibly biasing the $r$ estimate. In this study we explore the viability of using Minkowski functionals (MFs) as a robustness test to validate a potential $r$ detection by identifying non-Gaussian features associated with foregrounds contamination. To do so, we simulate sky maps as observed by a LiteBIRD-like CMB experiment, with realistic instrumental and foregrounds modelling. The CMB $B$-mode signal is recovered through blind component separation algorithms, and the obtained (biased) value of $r$ is used to generate Gaussian realisation of CMB signal. Their MFs are then compared with those computed on maps contaminated by foreground residual left by component separation, looking for a detection of non-Gaussianity. Our results demonstrate that, with the experimental configuration considered here, MFs can not be reliably adopted as a robustness test of an eventual $r$ detection, as we find that in the majority of the cases MFs are not able to raise significant warnings about the non-Gaussianity induced by the presence of foreground residuals. In the most realistic and refined scenario we adopted, the test is able to flag non-Gaussianity in $\sim 26\%$ of the simulations, meaning that there is no warning on the biased tensor-to-scalar ratio in $\sim 74\%$ of cases. These results suggest that more advanced statistics than MFs must be considered to look for non-Gaussian signatures of foregrounds, in order to be able to perform reliable null tests in future CMB missions.