A unified catalogue-level reanalysis of stage-III cosmic shear surveys. Issue 4 (28th January 2023)

• Record Type: Journal Article
• Authors: Longley, Emily P; Chang, Chihway; Walter, Christopher W; Zuntz, Joe; Ishak, Mustapha; Mandelbaum, Rachel; Miyatake, Hironao; Nicola, Andrina; Pedersen, Eske M; Pereira, Maria E S; Prat, Judit; Sánchez, J; Secco, Lucas F; Tröster, Tilman; Troxel, Michael; Wright, Angus H
• Is Part Of: Monthly notices of the Royal Astronomical Society. Volume 520:Issue 4(2023)
• Page Start: 5016
• Page End: 5041
• Publication Date: 2023-01-28
• Subjects: gravitational lensing: weak -- catalogues -- surveys -- cosmological parameters -- cosmology: observations; Astronomy -- Periodicals; Periodicals; 520.5
• DOI: 10.1093/mnras/stad246
• Languages: English
• ISSNs: 0035-8711

Abstract

ABSTRACT: Cosmological parameter constraints from recent galaxy imaging surveys are reaching percent-level accuracy on the effective amplitude of the lensing signal, S 8 . The upcoming Legacy Survey of Space and Time (LSST) of the Vera C. Rubin Observatory will produce subpercent level measurements of cosmological parameters, providing a milestone test of the ΛCDM model. To supply guidance to the upcoming LSST analysis, it is important to understand thoroughly the results from different recent galaxy imaging surveys and assess their consistencies. In this work, we perform a unified catalogue-level reanalysis of three cosmic shear data sets: the first year data from the Dark Energy Survey (DES-Y1), the 1000 deg 2 data set from the Kilo-Degree Survey (KiDS-1000), and the first year data from the Hyper Suprime-Cam Subaru Strategic Program (HSC-Y1). We utilize a pipeline developed and rigorously tested by the LSST Dark Energy Science Collaboration to perform the reanalysis and assess the robustness of the results to analysis choices. We find the S 8 constraint to be robust to two different small-scale modelling approaches, and varying choices of cosmological priors. Our unified analysis allows the consistency of the surveys to be rigorously tested, and we find the three surveys to be statistically consistent. Due to the partially overlapping footprint, we model the cross-covariance between KiDS-1000 and HSC-Y1 approximately when combining all three data sets, resulting in a 1.6–1.9 per cent constraint on S 8 given different assumptions on the cross-covariance.