Dark Energy Survey Year 1 Results: The Impact of Galaxy Neighbours on Weak Lensing Cosmology with im3shape

TL;DR

This study uses realistic simulations to assess how galaxy neighbours affect shape measurements and cosmological inferences in weak lensing, revealing biases that can be mitigated but impact cosmological parameters.

Contribution

It identifies four mechanisms of neighbour influence on shear estimation, quantifies their bias, and demonstrates how removing close neighbours reduces bias at the cost of galaxy density.

Findings

Neighbour bias can cause a 3-9% multiplicative shear bias.

Removing close neighbours reduces bias but decreases galaxy density by 30%.

Ignoring neighbour effects biases the cosmological parameter S8 by 2 sigma.

Abstract

We use a suite of simulated images based on Year 1 of the Dark Energy Survey to explore the impact of galaxy neighbours on shape measurement and shear cosmology. The hoopoe image simulations include realistic blending, galaxy positions, and spatial variations in depth and PSF properties. Using the im3shape maximum-likelihood shape measurement code, we identify four mechanisms by which neighbours can have a non-negligible influence on shear estimation. These effects, if ignored, would contribute a net multiplicative bias of $m \sim 0.03 - 0.09$ in the DES Y1 im3shape catalogue, though the precise impact will be dependent on both the measurement code and the selection cuts applied. This can be reduced to percentage level or less by removing objects with close neighbours, at a cost to the effective number density of galaxies $n_\mathrm{eff}$ of 30%. We use the cosmological inference pipeline of DES Y1 to explore the cosmological implications of neighbour bias and show that omitting blending from the calibration simulation for DES Y1 would bias the inferred clustering amplitude $S_8\equiv \sigma_8 (\Omega _\mathrm{m} /0.3)^{0.5}$ by $2 \sigma$ towards low values. Finally, we use the hoopoe simulations to test the effect of neighbour-induced spatial correlations in the multiplicative bias. We find the impact on the recovered $S_8$ of ignoring such correlations to be subdominant to statistical error at the current level of precision.