ROBO: a Model and a Code for the Study of the Interstellar Medium

TL;DR

ROBO is a comprehensive model and code for simulating the physical evolution of the interstellar medium, including gas and dust, with applications in large-scale cosmological and galaxy formation simulations.

Contribution

The paper introduces ROBO, a detailed ISM model with new reaction rates and dust processes, integrated with neural networks for efficient large-scale simulations.

Findings

The model accurately describes the physical state of gas and dust in the ISM.

Neural networks trained on ROBO data replicate results with high precision.

The database supports future applications in cosmological and galaxy evolution simulations.

Abstract

We present ROBO, a model and its companion code for the study of the interstellar medium (ISM). The aim is to provide an accurate description of the physical evolution of the ISM and to set the ground for an ancillary tool to be inserted in NBody-Tree-SPH (NB-TSPH) simulations of large scale structures in cosmological context or of the formation and evolution of individual galaxies. The ISM model consists of gas and dust. The gas chemical composition is regulated by a network of reactions that includes a large number of species (hydrogen and deuterium based molecules, helium, and metals). New reaction rates for the charge transfer in $\mathrm H^+$ and $\mathrm H_2$ collisions are presented. The dust contains the standard mixture of carbonaceous grains (graphite grains and PAHs) and silicates of which the model follows the formation and destruction by several processes. The model takes into account an accurate treatment of the cooling process, based on several physical mechanisms, and cooling functions recently reported in the literature. The model is applied to a wide range of the input parameters and the results for important quantities describing the physical state of the gas and dust are presented. The results are organized in a database suited to the artificial neural networks (ANNs). Once trained, the ANNs yield the same results obtained by ROBO, with great accuracy. We plan to develop ANNs suitably tailored for applications to NB-TSPH simulations of cosmological structures and/or galaxies.