The DESI PRObabilistic Value -added Bright Galaxy Survey (PROVABGS) mock challenge

ChangHoon Hahn*, K. J. Kwon, Rita Tojeiro, Malgorzata Siudek, Rebecca E. A. Canning, Mar Mezcua, Jeremy L. Tinker, David Brooks, Peter Doel, Kevin Fanning, Enrique Gaztañaga, Robert Kehoe, Martin Landriau, Aaron Meisner, John Moustakas, Claire Poppett, Gregory Tarle, Benjamin Weiner, Hu Zou

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)
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The PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) catalog will provide measurements of galaxy properties, such as stellar mass (M*), star formation rate (SFR), stellar metallicity (Z), and stellar age (tage), for >10 million galaxies of the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey. Full posterior distributions of the galaxy properties will be inferred using state-of-the-art Bayesian spectral energy distribution (SED) modeling of DESI spectroscopy and Legacy Surveys photometry. In this work, we present the SED model, the neural emulator for the model, and the Bayesian inference framework of PROVABGS. Furthermore, we apply the PROVABGS SED modeling on realistic synthetic DESI spectra and photometry, constructed using the L-Galaxies semi-analytic model. We compare the inferred galaxy properties to the true values of the simulation using a hierarchical Bayesian framework to quantify accuracy and precision. Overall, we accurately infer the true M*, SFR, Z, and tage of the simulated galaxies. However, the priors on galaxy properties induced by the SED model have a significant impact on the posteriors, which we characterize in detail. This work also demonstrates that a joint analysis of spectra and photometry significantly improves the constraints on galaxy properties over photometry alone and is necessary to mitigate the impact of the priors. With the methodology presented and validated in this work, PROVABGS will maximize information extracted from DESI observations and extend current galaxy studies to new regimes and unlock cutting-edge probabilistic analyses. 
Original languageEnglish
Article number16
Number of pages23
JournalAstrophysical Journal
Issue number1
Early online date1 Mar 2023
Publication statusPublished - 1 Mar 2023


  • Cosmology: observations
  • Galaxies: evolution
  • Galaxies: statistics


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