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
Abstract We present an efficient Bayesian method for estimating individual photometric redshifts and galaxy properties under a pretrained 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 …