Seeing in the dark -- I. Multi-epoch alchemy

TL;DR

This paper demonstrates that existing analysis techniques can effectively correct PSF effects in ground-based weak lensing surveys, enabling reliable cosmic shear measurements despite atmospheric and instrumental distortions.

Contribution

It introduces a method combining co-added SDSS imaging and a rounding kernel to null out PSF anisotropies, addressing a key systematic in weak lensing analysis.

Findings

PSF correction reduces spurious shear to negligible levels

Identifies a new systematic bias from masking in shear auto-correlations

Discusses conditions for applying this method to future surveys

Abstract

Weak lensing by large-scale structure is an invaluable cosmological tool given that most of the energy density of the concordance cosmology is invisible. Several large ground-based imaging surveys will attempt to measure this effect over the coming decade, but reliable control of the spurious lensing signal introduced by atmospheric turbulence and telescope optics remains a challenging problem. We address this challenge with a demonstration that point-spread function (PSF) effects on measured galaxy shapes in current ground-based surveys can be corrected with existing analysis techniques. In this work, we co-add existing Sloan Digital Sky Survey imaging on the equatorial stripe in order to build a data set with the statistical power to measure cosmic shear, while using a rounding kernel method to null out the effects of the anisotropic PSF. We build a galaxy catalogue from the combined imaging, characterise its photometric properties, and show that the spurious shear remaining in this catalogue after the PSF correction is negligible compared to the expected cosmic shear signal. We identify a new source of systematic error in the shear-shear auto-correlations arising from selection biases related to masking. Finally, we discuss the circumstances in which this method is expected to be useful for upcoming ground-based surveys that have lensing as one of the science goals, and identify the systematic errors that can reduce its efficacy.