Speaker
Description
Accurate redshift estimation and physically motivated source sample selection are central challenges for precision weak lensing cosmology. In this talk, I will present our recent work on inferring physical properties of weak lensing galaxies in the Kilo-Degree Survey (KiDS-1000) using a generative model for the galaxy population. The framework enabling this work is pop-cosmos, a calibrated galaxy population model that allows principled Bayesian inference of individual galaxy redshifts and physical properties for millions of KiDS-1000 sources. Validation against spectroscopic samples demonstrates low bias and scatter in the inferred photometric redshifts, while physical property inference enables the construction of weak lensing catalogues that mitigate intrinsic alignment systematics. Overall, our results demonstrate how the pop-cosmos galaxy population model can deliver accurate redshifts and galaxy properties, crucial for connecting galaxy evolution physics and weak lensing cosmology with Rubin LSST and Euclid.