SE3D: Testing the recovery of stellar population, dust and structural properties on mock-observed toy model and simulated galaxies

TL;DR

SE3D is a new radiative transfer modelling framework that accurately recovers galaxy properties from mock observations, revealing insights into galaxy evolution and highlighting model limitations.

Contribution

The paper introduces SE3D, a novel framework for recovering galaxy properties from observations, and evaluates its performance on toy models and simulated galaxies.

Findings

SE3D recovers stellar mass, dust mass, and SFR within 0.1 dex.

Radial and azimuthal structures have minor impact on recovery accuracy.

Discrepancies in dust-to-stellar mass ratio evolution compared to observations.

Abstract

The translation from direct observables to physical properties of galaxies is a key step in reconstructing their evolutionary histories. Star-dust geometry and inhomogeneous stellar populations can induce spatial variations in the mass-to-light ratio, complicating this process. In this paper, we present tests of SE3D, a novel modelling framework built around a radiative transfer emulator, aimed at tackling this problem. We test the ability to recover known intrinsic properties of toy model and TNG50 simulated galaxies by jointly fitting mock observations of their multi-wavelength photometric and structural properties. We find an encouraging performance ($\lesssim$ 0.1 dex) for several key characteristics, including the bulk stellar mass, dust mass and SFR, as well as their respective radial extents. We point out limitations, and investigate the impact of various sources of model mismatch. Among them, mismatch in the shapes of star formation histories contributes most, with radial and azimuthal structure and stellar metallicity distributions playing a progressively more minor role. We also analyse the evolution from z=2 to z=0 of resolved stellar and dust properties of TNG galaxies, as measured intrinsically and expressed in their distribution across UVJ and IRX-$\beta$ diagnostic diagrams. We test different methods to assign dust to the simulation, and find a persistent lack of Mdust/Mstar evolution and a more limited dynamic range across the diagnostic diagrams compared to observations.