The impact of intrinsic alignment on current and future cosmic shear surveys

TL;DR

This study forecasts how intrinsic galaxy alignments affect cosmic shear measurements in current and upcoming surveys, highlighting the importance of mitigation strategies to reduce biases in dark energy parameter estimation.

Contribution

It provides the first detailed forecasts of IA impact on multiple surveys using realistic simulations and explores effective mitigation schemes, including galaxy selection strategies.

Findings

Euclid is significantly impacted by IA due to its shallow depth.

Mitigation schemes effectively remove IA biases across most surveys.

Excluding red galaxies reduces IA contamination with minimal loss of statistical power.

Abstract

Intrinsic alignment (IA) of source galaxies is one of the major astrophysical systematics for ongoing and future weak lensing surveys. This paper presents the first forecasts of the impact of IA on cosmic shear measurements for current and future surveys (DES, Euclid, LSST, WFIRST) using simulated likelihood analyses and realistic covariances that include higher-order moments of the density field in the computation. We consider a range of possible IA scenarios and test mitigation schemes, which parameterize IA by the fraction of red galaxies, normalization, luminosity and redshift dependence of the IA signal (for a subset we consider joint IA and photo-z uncertainties). Compared to previous studies we find smaller biases in time-dependent dark energy models if IA is ignored in the analysis; the amplitude and significance of these biases vary as a function of survey properties (depth, statistical uncertainties), luminosity function, and IA scenario: Due to its small statistical errors and relatively shallow observing strategy Euclid is significantly impacted by IA. LSST and WFIRST benefit from their increased survey depth, while the larger statistical errors for DES decrease IA's relative impact on cosmological parameters. The proposed IA mitigation scheme removes parameter biases due to IA for DES, LSST, and WFIRST even if the shape of the IA power spectrum is only poorly known; successful IA mitigation for Euclid requires more prior information. We explore several alternative IA mitigation strategies for Euclid; in the absence of alignment of blue galaxies we recommend the exclusion of red (IA contaminated) galaxies in cosmic shear analyses. We find that even a reduction of 20% in the number density of galaxies only leads to a 4-10% loss in cosmological constraining power.