TL;DR
This paper develops a formalism for estimating cosmic shear power spectra in Fourier space, addressing complications from survey geometry and noise, and demonstrates its application to recent survey data.
Contribution
It introduces fast, accurate methods for estimating noise bias and covariance matrices for shear power spectra, accounting for survey geometry and systematics.
Findings
Validated methods on Hyper Suprime-Cam data
Quantified systematics in shear measurements
Provided publicly available power spectra and covariance data
Abstract
Cosmic shear is one of the most powerful probes of Dark Energy, targeted by several current and future galaxy surveys. Lensing shear, however, is only sampled at the positions of galaxies with measured shapes in the catalog, making its associated sky window function one of the most complicated amongst all projected cosmological probes of inhomogeneities, as well as giving rise to inhomogeneous noise. Partly for this reason, cosmic shear analyses have been mostly carried out in real-space, making use of correlation functions, as opposed to Fourier-space power spectra. Since the use of power spectra can yield complementary information and has numerical advantages over real-space pipelines, it is important to develop a complete formalism describing the standard unbiased power spectrum estimators as well as their associated uncertainties. Building on previous work, this paper contains a…
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