Lensing reconstruction from PLANCK sky maps: inhomogeneous noise

TL;DR

This paper examines how inhomogeneous noise affects cosmic microwave background lens reconstruction using Planck satellite data, comparing optimal and suboptimal methods for accurate analysis.

Contribution

It introduces and compares three approaches to lens reconstruction considering noise inhomogeneity, including an optimal but computationally intensive method and two efficient suboptimal alternatives.

Findings

The suboptimal methods are within 5% of the optimal approach for Planck data.

One method prevents bias from noise model uncertainties.

Inhomogeneous noise induces a mean-field that must be accounted for.

Abstract

We discuss the effects of inhomogeneous sky-coverage on CMB lens reconstruction, focusing on application to the recently launched Planck satellite. We discuss the mean-field which is induced by noise inhomogeneities, as well as three approaches to lens reconstruction in this context: an optimal maximum-likelihood approach which is computationally expensive to evaluate, and two suboptimal approaches which are less intensive. The first of these is only sub-optimal at the five per-cent level for Planck, and the second prevents biasing due to uncertainties in the noise model.