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 pretrained population model ( pop-cosmos ) that was calibrated using purely photometric data. This model specifies a prior distribution over 16 stellar population synthesis (SPS) par...

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Bibliographic Details
Main Authors: Stephen Thorp, Justin Alsing, Hiranya V. Peiris, Sinan Deger, Daniel J. Mortlock, Boris Leistedt, Joel Leja, Arthur Loureiro
Format: Article
Language:English
Published: IOP Publishing 2024-01-01
Series:The Astrophysical Journal
Subjects:
Astrostatistics techniques
Redshift surveys
Galaxy photometry
Bayesian statistics
Affine invariant
Spectral energy distribution
Online Access:https://doi.org/10.3847/1538-4357/ad7736

Internet

https://doi.org/10.3847/1538-4357/ad7736

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