Description
Next-generation of galaxy surveys will provide vast datasets to improve our knowledge of the universe once we extract the maximum information content. However, the late-time matter distribution is non-Gaussian, limiting the information captured by two-point statistics. One-point statistics can extract a key part of the non-Gaussian information from galaxy clustering, and combining it with weak lensing promises to simultaneously constrain galaxy bias and cosmology. Studies with the one-point probability distribution function (PDF) have proven to contain valuable information for improving the constraints on the cosmological parameters. In particular the weak lensing convergence PDF is sensitive to the physics of the dark universe, specifically dark matter and dark energy. Therefore, we aim to exploit the correlation between background source galaxy shapes and foreground galaxy density to quantify the cosmological information in the joint weak lensing convergence and galaxy clustering PDF. We will present the modelling framework used in that analysis and its validation with lensing and clustering catalogues from N-body simulations with Euclid and LSST characteristics.
