TY - JOUR
T1 - IQ Collaboratory. III. The Empirical Dust Attenuation Framework-Taking Hydrodynamical Simulations with a Grain of Dust
AU - Hahn, ChangHoon
AU - Starkenburg, Tjitske K.
AU - Angles-Alcazar, Daniel
AU - Choi, Ena
AU - Dave, Romeel
AU - Dickey, Claire
AU - Iyer, Kartheik G.
AU - Maller, Ariyeh H.
AU - Somerville, Rachel S.
AU - Tinker, Jeremy L.
AU - Yung, L. Y. Aaron
N1 - Funding Information:
It is a pleasure to thank Michael Blanton, Nicholas T. Faucher, Marla Geha, Shy Genel, Jenny E. Green, Daniel Kelson, Mariska Kriek, Peter Melchior, Desika Narayanan, Samir Salim, and Katherine Suess for valuable discussions and comments. This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of High Energy Physics, under contract No. DE-AC02-05CH11231. C.H. is supported by the AI Accelerator program of the Schmidt Futures Foundation.
Funding Information:
The data used in this work were, in part, hosted on facilities supported by the Scientific Computing Core at the Flatiron Institute, a division of the Simons Foundation, and the analysis was largely done using those facilities. The IQ (Isolated & Quiescent) Collaboratory thanks the Flatiron Institute for hosting the collaboratory and its meetings. The Flatiron Institute is supported by the Simons Foundation. Funding for the Sloan Digital Sky Survey IV has been provided by the Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science, and the Participating Institutions. SDSS acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. The SDSS website is www.sdss.org . The SDSS is managed by the Astrophysical Research Consortium for the Participating Institutions.
Funding Information:
This research was supported in part through the computational resources and staff contributions provided by the Quest high-performance computing facility at Northwestern University, which is jointly supported by the Office of the Provost, the Office for Research, and Northwestern University Information Technology.
Publisher Copyright:
© 2022. The Author(s). Published by the American Astronomical Society.
PY - 2022/2/17
Y1 - 2022/2/17
N2 - We present the empirical dust attenuation (EDA) framework—a flexible prescription for assigning realistic dust attenuation to simulated galaxies based on their physical properties. We use the EDA to forward model synthetic observations for three state-of-the-art large-scale cosmological hydrodynamical simulations: SIMBA, IllustrisTNG, and EAGLE. We then compare the optical and UV color–magnitude relations, (g − r) − Mr and (far-UV −near-UV) − Mr, of the simulations to a Mr < − 20 and UV complete Sloan Digital Sky Survey galaxy sample using likelihood-free inference. Without dust, none of the simulations match observations, as expected. With the EDA, however, we can reproduce the observed color–magnitude with all three simulations. Furthermore, the attenuation curves predicted by our dust prescription are in good agreement with the observed attenuation–slope relations and attenuation curves of star-forming galaxies. However, the EDA does not predict star-forming galaxies with low AV since simulated star-forming galaxies are intrinsically much brighter than observations. Additionally, the EDA provides, for the first time, predictions on the attenuation curves of quiescent galaxies, which are challenging to measure observationally. Simulated quiescent galaxies require shallower attenuation curves with lower amplitude than star-forming galaxies. The EDA, combined with forward modeling, provides an effective approach for shedding light on dust in galaxies and probing hydrodynamical simulations. This work also illustrates a major limitation in comparing galaxy formation models: by adjusting dust attenuation, simulations that predict significantly different galaxy populations can reproduce the same UV and optical observations.
AB - We present the empirical dust attenuation (EDA) framework—a flexible prescription for assigning realistic dust attenuation to simulated galaxies based on their physical properties. We use the EDA to forward model synthetic observations for three state-of-the-art large-scale cosmological hydrodynamical simulations: SIMBA, IllustrisTNG, and EAGLE. We then compare the optical and UV color–magnitude relations, (g − r) − Mr and (far-UV −near-UV) − Mr, of the simulations to a Mr < − 20 and UV complete Sloan Digital Sky Survey galaxy sample using likelihood-free inference. Without dust, none of the simulations match observations, as expected. With the EDA, however, we can reproduce the observed color–magnitude with all three simulations. Furthermore, the attenuation curves predicted by our dust prescription are in good agreement with the observed attenuation–slope relations and attenuation curves of star-forming galaxies. However, the EDA does not predict star-forming galaxies with low AV since simulated star-forming galaxies are intrinsically much brighter than observations. Additionally, the EDA provides, for the first time, predictions on the attenuation curves of quiescent galaxies, which are challenging to measure observationally. Simulated quiescent galaxies require shallower attenuation curves with lower amplitude than star-forming galaxies. The EDA, combined with forward modeling, provides an effective approach for shedding light on dust in galaxies and probing hydrodynamical simulations. This work also illustrates a major limitation in comparing galaxy formation models: by adjusting dust attenuation, simulations that predict significantly different galaxy populations can reproduce the same UV and optical observations.
U2 - 10.3847/1538-4357/ac4253
DO - 10.3847/1538-4357/ac4253
M3 - Article
VL - 926
SP - 1
EP - 20
JO - Astrophysical Journal
JF - Astrophysical Journal
SN - 0004-637X
IS - 2
M1 - 122
ER -