Impact & Mitigation of Polarized Extragalactic Foregrounds on Bayesian Cosmic Microwave Background Lensing

TL;DR

Future low-noise CMB polarization measurements will be less affected by extragalactic polarized foregrounds if foreground spectra are accurately modeled, and a new joint fitting method can mitigate potential biases.

Contribution

This paper demonstrates the insensitivity of Bayesian CMB lensing to polarized foregrounds with masking and introduces a joint fitting approach for bias mitigation in future experiments.

Findings

Bayesian lensing is insensitive to polarized foregrounds after masking.

Accurate foreground power spectra are crucial for bias mitigation.

A new joint fitting method reduces foreground-induced biases.

Abstract

Future low-noise cosmic microwave background (CMB) lensing measurements from e.g., CMB-S4 will be polarization dominated, rather than temperature dominated. In this new regime, statistically optimal lensing reconstructions outperform the standard quadratic estimator, but their sensitivity to extragalactic polarized foregrounds has not been quantified. Using realistic simulations of polarized radio and infrared point sources, we show for the first time that optimal Bayesian lensing from a CMB-S4-like experiment is insensitive to the expected level of polarized extragalactic foregrounds after masking, as long as an accurate foreground power spectrum is included in the analysis. For more futuristic experiments where these foregrounds could cause a detectable bias, we propose a new method to jointly fit for lensing and the Poisson foregrounds, generalizing the bias hardening from the standard quadratic estimator to Bayesian lensing.