Cosmology from the integrated shear 3-point correlation function: simulated likelihood analyses with machine-learning emulators
arXiv:2304.01187 · doi:10.1088/1475-7516/2023/07/040
Abstract
The integrated shear 3-point correlation function measures the correlation between the local shear 2-point function and the 1-point shear aperture mass in patches of the sky. Unlike other higher-order statistics, can be efficiently measured from cosmic shear data, and it admits accurate theory predictions on a wide range of scales as a function of cosmological and baryonic feedback parameters. Here, we develop and test a likelihood analysis pipeline for cosmological constraints using . We incorporate treatment of systematic effects from photometric redshift uncertainties, shear calibration bias and galaxy intrinsic alignments. We also develop an accurate neural-network emulator for fast theory predictions in MCMC parameter inference analyses. We test our pipeline using realistic cosmic shear maps based on -body simulations with a DES Y3-like footprint, mask and source tomographic bins, finding unbiased parameter constraints. Relative to -only, adding can lead to improvements on the constraints of parameters like (or ) and . We find no evidence in constraints of a significant mitigation of the impact of systematics. We also investigate the impact of the size of the apertures where is measured, and of the strategy to estimate the covariance matrix (-body vs. lognormal). Our analysis solidifies the strong potential of the statistic and puts forward a pipeline that can be readily used to improve cosmological constraints using real cosmic shear data.
21 pages, 11 figures, 3 tables. Comments welcome
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