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Upcoming deep imaging surveys such as the Vera C. Rubin Observatory LegacySurvey of Space and Time will be confronted with challenges that come withincreased depth. One of the leading systematic errors in deep surveys is theblending of objects due to higher surface density in the more crowded images; aconsiderable fraction of the galaxies which we hope to use for cosmologyanalyses will overlap each other on the observed sky. In order to investigatethese challenges, we emulate blending in a mock catalogue consisting ofgalaxies at a depth equivalent to 1.3 yr of the full 10-yr Rubin Observatorythat includes effects due to weak lensing, ground-based seeing, and theuncertainties due to extraction of catalogues from imaging data. The emulatedcatalogue indicates that approximately 12 per cent of the observed galaxies are``unrecognized'' blends that contain two or more objects but are detected asone. Using the positions and shears of half a billion distant galaxies, wecompute shear--shear correlation functions after selecting tomographic samplesin terms of both spectroscopic and photometric redshift bins. We examine thesensitivity of the cosmological parameter estimation to unrecognized blendingemploying both jackknife and analytical Gaussian covariance estimators. An$\sim0.025$ decrease in the derived structure growth parameter $S_8 = \sigma_8(\Omega_{\rm m}/0.3)^{0.5}$ is seen due to unrecognized blending in bothtomographies with a slight additional bias for the photo-$z$-based tomography.This bias is greater than the $2\sigma$ statistical error in measuring $S_8$.

Galaxy blending effects in deep imaging cosmic shear probes of cosmology