Cloud properties across spatial scales in simulations of the interstellar medium

Abstract

Molecular clouds (MCs) are structures of dense gas in the interstellar medium (ISM) that extend from ten to a few hundred parsecs and form the main gas reservoir available for star formation. Hydrodynamical simulations of a varying complexity are a promising way to investigate MCs evolution and their properties. However, each simulation typically has a limited range in resolution and different cloud extraction algorithms are used, which complicates the comparison between simulations. In this work, we aim to extract clouds from different simulations covering a wide range of spatial scales. We compare their properties, such as size, shape, mass, internal velocity dispersion, and virial state. We applied the Hop cloud detection algorithm on (M)HD numerical simulations of stratified ISM boxes and isolated galactic disk simulations that were produced using Flash Ramses and Arepo We find that the extracted clouds are complex in shape, ranging from round objects to complex filamentary networks in all setups. Despite the wide range of scales, resolution, and sub-grid physics, we observe surprisingly robust trends in the investigated metrics. The mass spectrum matches in the overlap between simulations without rescaling and with a high-mass power-law index of -1 for logarithmic bins of mass, in accordance with theoretical predictions. The internal velocity dispersion scales with the size of the cloud as $ $ for large clouds ($R pc $). For small clouds we find larger sigma compared to the power-law scaling, as seen in observations, which is due to supernova-driven turbulence. Almost all clouds are gravitationally unbound with the virial parameter scaling as $ vir $, which is slightly flatter compared to observed scaling but in agreement given the large scatter. We note that the cloud distribution towards the low-mass end is only complete if the more dilute gas is also refined, rather than only the collapsing regions.