pop-cosmos: Scaleable inference of galaxy properties and redshifts with
a data-driven population model
pop-cosmos: Scaleable inference of galaxy properties and redshifts with
a data-driven population model
We present an efficient Bayesian method for estimating individual photometric redshifts and galaxy properties under a pre-trained population model (pop-cosmos) that was calibrated using purely photometric data. This model specifies a prior distribution over 16 stellar population synthesis (SPS) parameters using a score-based diffusion model, and includes a data model …