Most cosmic shear analyses to date have relied on summary statistics (eg ξ+ and ξ−). These
types of analyses are necessarily suboptimal, as the use of summary statistics is lossy. In
this paper, we forward-model the convergence field of the Universe as a lognormal random
field conditioned on the observed shear data. This new map-based inference framework
enables us to recover the joint posterior of the cosmological parameters and the
convergence field of the Universe. Our analysis properly accounts for the covariance in the …