Learning the Universe: Physically Motivated Priors for Dust Attenuation Curves

Understanding the impact of dust on the spectral energy distributions (SEDs) of galaxies is crucial for inferring their physical properties and for studying the nature and evolution of interstellar dust. In this study, we analyze dust attenuation curves of ∼6400 galaxies (M⋆ ∼ 109─1011.5 M⊙) at z = 0.07 from the IllustrisTNG50 & TNG100 simulations. Using radiative transfer post-processing, we generate synthetic attenuation curves and fit them with a versatile parametric model that encompasses both known extinction and attenuation curves (e.g., Calzetti, MW, SMC, and LMC) and more exotic forms. We present the distributions of the best-fitting parameters—UV slope (c1), optical-to-near-IR (NIR) slope (c2), far-UV (FUV) slope (c3), 2175 Å bump strength (c4), and normalization (AV)—accounting for scatter from orientation effects. Key correlations emerge between AV and the star formation rate surface density ΣSFR, as well as the UV slope c1. Furthermore, the UV and FUV slopes (c1, c3) and the visual attenuation and bump strength (AV, c4) exhibit robust internal correlations (anticorrelation in the latter case). The optical-to-NIR slope exhibits minimal variations. Using these insights from simulations, we provide a set of scaling relations that predict a galaxy’s median (averaged over line of sight) dust attenuation curve based solely on its ΣSFR and/or AV. These predictions agree well with observed attenuation curves from the GALEX─Sloan Digital Sky Survey─Wide-field Infrared Survey Explorer Legacy Catalog, although there are minor differences in bump strength. This study delivers the most comprehensive library of synthetic attenuation curves for local galaxies, and provides a foundation for physically motivated priors for SED fitting and galaxy inference studies, such as those performed as part of the Learning the Universe Collaboration.