Bayesian hierarchical modelling of weak lensing - the golden goal

Understand

To accomplish correct Bayesian inference from weak lensing shear data requires a complete statistical description of the data.

• The natural framework to do this is a Bayesian Hierarchical Model, which divides the chain of reasoning into component steps.
• Starting with a catalogue of shear estimates in tomographic bins, we build a model that allows us to sample simultaneously from the the underlying tomographic shear fields and the relevant power spectra (E-mode, B-mode, and E-B, for auto- and cross-power spectra).
• The procedure deals easily with masked data and intrinsic alignments.