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arXiv · 2204.02053

Escaping the maze: a statistical sub-grid model for cloud-scale density structures in the interstellar medium

Abstract

The interstellar medium (ISM) is a turbulent, highly structured multi-phase medium. State-of-the-art cosmological simulations of the formation of galactic discs usually lack the resolution to accurately resolve those multi-phase structures. However, small-scale density structures play an important role in the life cycle of the ISM, and determine the fraction of cold, dense gas, the amount of star formation and the amount of radiation and momentum leakage from cloud-embedded sources. Here, we derive a $statistical\, model$ to calculate the unresolved small-scale ISM density structure from coarse-grained, volume-averaged quantities such as the $gas\, clumping\, factor$, $\mathcal{C}$, and mean density $\left<ρ\right>_V$. Assuming that the large-scale ISM density is statistically isotropic, we derive a relation between the three-dimensional clumping factor, $\mathcal{C}_ρ$, and the clumping factor of the $4π$ column density distribution on the cloud surface, $\mathcal{C}_Σ$, and find $\mathcal{C}_Σ=\mathcal{C}_ρ^{2/3}$. Applying our model to calculate the covering fraction, i.e., the $4π$ sky distribution of optically thick sight-lines around sources inside interstellar gas clouds, we demonstrate that small-scale density structures lead to significant differences at fixed physical ISM density. Our model predicts that gas clumping increases the covering fraction by up to 30 per cent at low ISM densities compared to a uniform medium. On the other hand, at larger ISM densities, gas clumping suppresses the covering fraction and leads to increased scatter such that covering fractions can span a range from 20 to 100 per cent at fixed ISM density. All data and example code is publicly available at GitHub.

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Tobias Buck, Christoph Pfrommer, Philipp Girichidis, Bogdan Corobean. 2022-04-05. Escaping the maze: a statistical sub-grid model for cloud-scale density structures in the interstellar medium. https://doi.org/10.1093/mnras%2Fstac952

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