Inferring More from Less: Prospector as a Photometric Redshift Engine in the Era of JWST

• Published in: Astrophysical journal. Letters Vol. 944; no. 2; p. L58
• Main Authors: Wang, Bingjie, Leja, Joel, Bezanson, Rachel, Johnson, Benjamin D., Khullar, Gourav, Labbé, Ivo, Price, Sedona H., Weaver, John R., Whitaker, Katherine E.
• Format: Journal Article
• Language: English
• Published: Austin The American Astronomical Society 01-02-2023; IOP Publishing
• Subjects: Active galactic nuclei; Bayesian analysis; Bayesian statistics; Computational astronomy; Cosmic dust; Galaxies; Galaxy evolution; Galaxy formation; James Webb Space Telescope; Modelling; Photometry; Red shift; Redshift surveys; Space telescopes; Spectral energy distribution; Spectrophotometry; Star & galaxy formation; Star formation; Stars & galaxies; Statistical inference
• ISSN: 2041-8205; 2041-8213
• DOI: 10.3847/2041-8213/acba99

Abstract
The advent of the James Webb Space Telescope (JWST) signals a new era in exploring galaxies in the high-
z
universe. Current and upcoming JWST imaging will potentially detect galaxies at
z
∼ 20, creating a new urgency in the quest to infer accurate photometric redshifts (photo-
z
) for individual galaxies from their spectral energy distributions, as well as masses, ages, and star formation rates. Here we illustrate the utility of informed priors encoding previous observations of galaxies across cosmic time in achieving these goals. We construct three joint priors encoding empirical constraints of redshifts, masses, and star formation histories in the galaxy population within the
Prospector
Bayesian inference framework. In contrast with uniform priors, our model breaks an age–mass–redshift degeneracy, and thus reduces the mean bias error in masses from 0.3 to 0.1 dex, and in ages from 0.6 to 0.2 dex in tests done on mock JWST observations. Notably, our model recovers redshifts at least as accurately as the state-of-the-art photo-
z
code
EAzY
in deep JWST fields, but with two advantages: tailoring a model based on a particular survey is rendered mostly unnecessary given well-motivated priors; obtaining joint posteriors describing stellar, active galactic nuclei, gas, and dust contributions becomes possible. We can now confidently use the joint distribution to propagate full non-Gaussian redshift uncertainties into inferred properties of the galaxy population. This model, “
Prospector
-
β
,” is intended for fitting galaxy photometry where the redshift is unknown, and will be instrumental in ensuring the maximum science return from forthcoming photometric surveys with JWST. The code is made publicly available online as a part of
Prospector
9
9
The version used in this work corresponds to the state of the Git repository at commit
https://github.com/bd-j/prospector/commit/820ad72363a1f9c22cf03610bfe6e361213385cd
.
.