Cosmic Shear E/B-mode Estimation with Binned Correlation Function Data
Matthew R. Becker (UChicago/KICP)

TL;DR
This paper develops optimal linear estimators for separating E- and B-modes in binned cosmic shear correlation data, enabling better data analysis, contamination detection, and high-precision cosmological parameter estimation.
Contribution
It introduces methods to minimize E/B-mode mixing in binned shear data and demonstrates their application for data compression and contamination localization.
Findings
Optimal estimators reduce E/B-mode mixing.
Ambiguous mode subspace contains significant cosmological information.
Wavelet-like estimators can locate B-mode contamination.
Abstract
In this work I study the problem of E/B-mode separation with binned cosmic shear two-point correlation function data. Motivated by previous work on E/B-mode separation with shear two-point correlation functions and the practical considerations of data analysis, I consider E/B-mode estimators which are linear combinations of the binned shear correlation function data points. I demonstrate that these estimators mix E- and B-modes generally. I then show how to define estimators which minimize this E/B-mode mixing and give practical recipes for their construction and use. Using these optimal estimators, I demonstrate that the vector space composed of the binned shear correlation function data points can be decomposed into approximately ambiguous, E- and B-mode subspaces. With simple Fisher information estimates, I show that a non-trivial amount of information on typical cosmological…
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