The DESI PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) Mock Challenge

Abstract

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 (t age), 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 t age 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. https://github.com/changhoonhahn/provabgs/

PopSED: Population-level Inference for Galaxy Properties from Broadband Photometry with Neural Density Estimation

“…In this work, the SFHs of galaxies are described using the PROVABGS model (Alsing et al 2020;Hahn et al 2023b), which is trained on the galaxies in the Illustris hydrodynamical simulation (Genel et al 2014;Vogelsberger et al 2014;Nelson et al 2015). The SFH is modeled by a linear combination of } and one burst component δ(t − t burst ):…”

“…The SFH bases s i SFH { } are generated based on the SFHs of Illustris galaxies using the non-negative matrix factorization (Lee & Seung 1999;Cichocki & Phan 2009). As shown in Hahn et al (2023b), the four bases are sufficient to capture the SFH of Illustris galaxies. Among the SFH bases, s 1 SFH corresponds to the most recent star formation, whereas s 4 SFH corresponds to the oldest star formation (see Figure 5 and Appendix A in Hahn et al 2023b).…”

“…As shown in Hahn et al (2023b), the four bases are sufficient to capture the SFH of Illustris galaxies. Among the SFH bases, s 1 SFH corresponds to the most recent star formation, whereas s 4 SFH corresponds to the oldest star formation (see Figure 5 and Appendix A in Hahn et al 2023b). Such SFH bases are nonnegative by construction and are physically intuitive to interpret.…”

“…In the original PROVABGS, the ZH is described as a linear combination of two ZH bases extracted from Illustris. Because photometric data alone are quite uninformative in inferring the ZH (e.g., Hahn et al 2023b), we simplify the ZH to be a constant stellar metallicity Z Z log   ( ) over time, as many other works assume (e.g., Carnall et al 2019;Leja et al 2019a).…”

The DESI Bright Galaxy Survey: Final Target Selection, Design, and Validation

“…The BGS will also provide an extraordinary resource for advancing our understanding of the physical processes that drive galaxy formation and evolution. With spectra and photometry for each of its >10 million galaxies, BGS will enable measurements of their physical properties (Hahn et al 2023) and provide the most precise measurements of galaxy property statistics at low redshifts, e.g., the stellar mass function (Li & White 2009;Moustakas et al 2013), the starforming sequence (Noeske et al 2007), and the massmetallicity relation (Tremonti et al 2004). It will also enable studies of galaxy groups (Eke et al 2004), the connection between galaxies and dark matter (Tinker et al 2011;Zu & Mandelbaum 2015;Xu et al 2018), and the environmentdependent luminosity function (McNaught-Roberts et al 2014;Eardley et al 2015;Fang et al 2019).…”