Dust and gas modelling in radiative transfer simulations of disc-dominated galaxies with RADMC-3D

TL;DR

This paper introduces RTGen, a new pipeline using RADMC-3D for radiative transfer simulations of disc galaxies, emphasizing dust and gas modeling's impact on observable predictions.

Contribution

The novel RTGen pipeline integrates dust and gas physics in radiative transfer simulations, enabling high-accuracy galaxy observable predictions.

Findings

Accurately predicts spectral energy distributions of simulated galaxies.

Dust modeling significantly affects the convergence of galaxy observables.

Framework achieves few tens of percent convergence, suitable for high-precision studies.

Abstract

Bridging theory and observations is a key task to understand galaxy formation and evolution. With the advent of state-of-the-art observational facilities, an accurate modelling of galaxy observables through radiative transfer simulations coupled to hydrodynamic simulations of galaxy formation must be performed. We present a novel pipeline, dubbed RTGen, based on the Monte Carlo radiative transfer code RADMC-3D , and explore the impact of the physical assumptions and modelling of dust and gas phases on the resulting galaxy observables. In particular, we address the impact of the dust abundance, composition, and grain size, as well as model the atomic-to-molecular transition and study the resulting emission from molecular gas. We apply Monte Carlo radiative transfer a posteriori to determine the dust temperature in six different hydrodynamic simulations of isolated galaxies. Afterwards, we apply ray tracing to compute the spectral energy distribution, as well as continuum images and spectral line profiles. We find our pipeline to predict accurate spectral energy distribution distributions of the studied galaxies, as well as continuum and CO luminosity images, in good agreement with literature results from both observations and theoretical studies. In particular, we find the dust modelling to have an important impact on the convergence of the resulting predicted galaxy observables, and that an adequate modelling of dust grains composition and size is required. We conclude that our novel framework is ready to perform high-accuracy studies of the observables of the ISM, reaching few tens percent convergence under the studied baseline configuration. This will enable robust studies of galaxy formation, and in particular of the nature of massive clumps in high-redshift galaxies, through the generation of mock images mimicking observations from state-of-the-art facilities such as JWST and ALMA.