Bayesian forward modelling of cosmic shear data

We present a Bayesian hierarchical modelling approach to infer the cosmic matter density field, and lensing power spectra, from shear data. This method uses physical model of structure formation physically plausible structures, which accounts for non-Gaussian features gravitationally evolved distribution light-cone effects. test validate our framework with realistic simulated data, demonstrating that recovers unbiased correct spectrum. While cosmology is fixed in this test, employs prior spectrum, we demonstrate results are sensitive true spectrum when differs prior. In case, field samples generated deviates prior, The also across sky, but as currently implemented, it cannot determine radial since isotropy not imposed. summary, provides inference dark allowing us extract information beyond two-point statistics exploiting full content cosmological fields.