Lack-of-correlation anomaly in CMB large scale polarisation maps

We present an assessment of the CMB large scale anomalies in polarisation using the two-point correlation function as a test case. We employ the state of the art of large scale polarisation datasets: the first based on a Planck 2018 HFI 100 and 143 GHz cross-spectrum analysis, based on SRoll2 processing, and the second from a map-based approach derived through a joint treatment of Planck 2018 LFI and WMAP-9yr. We consider the well-known $S_{1/2}$ estimator, which measures the distance of the two-point correlation function from zero at angular scales larger than $60^{\circ}$, and rely on realistic simulations for both datasets to assess confidence intervals. By focusing on the pure polarisation field described by either the $Q$ and $U$ Stokes parameters or by the local $E-$modes, we show that the first description is heavily influenced by the quadrupole (which is poorly constrained in both datasets) while the second one is more suited for an analysis containing higher multipoles up to $\ell \sim 10$, limit above which both datasets become markedly noise dominated. We find that both datasets exhibit a lack-of-correlation anomaly in pure polarisation, similar to the one observed in temperature, which is better constrained by the less noisy Planck HFI 100$\times$143 data, where its significance lies at about $99.5\%$. We perform our analysis using realizations that are either constrained or non-constrained by the observed temperature field, and find similar results in the two cases.