Isotropy analyses of the Planck convergence map

TL;DR

This study analyzes the Planck convergence map to identify potential anomalies in the weak lensing signatures, finding mostly good agreement with the standard cosmological model but noting some outliers possibly due to residual contamination.

Contribution

First comprehensive analysis of Planck convergence map variance revealing localized anomalies and their relation to expected cosmological features.

Findings

Identified 8 sky patches with >2σ disagreement with simulations.

No significant large-scale discrepancies found.

Outliers near ecliptic poles may indicate residual contamination.

Abstract

The presence of matter in the path of relic photons causes distortions in the angular pattern of the cosmic microwave background (CMB) temperature fluctuations, modifying their properties in a slight but measurable way. Recently, the Planck Collaboration released the estimated convergence map, an integrated measure of the large-scale matter distribution that produced the weak gravitational lensing (WL) phenomenon observed in Planck CMB data. We perform exhaustive analyses of this convergence map calculating the variance in small and large regions of the sky, but excluding the area masked due to galactic contaminations, and compare them with the features expected in the set of simulated convergence maps, also released by the Planck collaboration. Our goal is to search for sky directions or regions where the WL imprints anomalous signatures to the variance estimator revealed through a $\chi^2$ analyses at a statistically significant level. In the local analysis of the Planck convergence map we identified 8 patches of the sky in disagreement, in more than 2$\sigma$, with what is observed in the average of the simulations. In contrast, in the large regions analysis we found no statistically significant discrepancies, but, interestingly, the regions with the highest $\chi^2$ values are surrounding the ecliptic poles. Thus, our results show a good agreement with the features expected by the $\Lambda$CDM concordance model, as given by the simulations. Yet, the outliers regions found here could suggest that the data still contain residual contamination, like noise, due to over- or under-estimation of systematic effects in the simulation data set.