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

Context. Bridging theory and observations is a key task in modern astrophysics, aimed at improving our understanding of the formation and evolution of galaxies. With the advent of state-of-the-art observational facilities, the accurate modeling of galaxy observables via radiative transfer simulations coupled to hydrodynamic simulations of galaxy formation must be performed. Aims. We present a novel pipeline, dubbed RTGen, based on the Monte Carlo radiative transfer code RADMC-3D. We explore the impact of the physical assumptions and modeling of dust and gas phases on the resulting galaxy observables. In particular, we thoroughly addressed the impact of the dust abundance, composition, and grain size. We also implemented approximate models for the atomic-to-molecular transition and studied the resulting emission from molecular gas. Methods. We applied a Monte Carlo radiative transfer a posteriori to determine the dust temperature in six different hydrodynamic simulations of isolated galaxies. Afterwards, we applied ray tracing to compute the spectral energy distribution (SED), as well as to derive the continuum images and spectral line profiles. Results. We find that our pipeline is able to predict accurate SEDs for the studied galaxies, along with the continuum and CO luminosity images. These results are in good qualitative agreement with literature results from both observations and theoretical studies. In particular, we find the dust modeling to have an important impact on the convergence of the resulting predicted galaxy observables and that an adequate modeling of dust grain composition and size is required. Conclusions. We conclude that our novel framework is ready to perform high-accuracy studies of the observables of the interstellar medium (ISM), reaching a convergence of a few tens of percent under the studied baseline configuration. This will enable robust studies of galaxy formation and, in particular, the nature of massive clumps in high-redshift galaxies thanks to the generation of reliable and accurate mock images mimicking observations from state-of-the-art facilities, such as JWST and ALMA.