Filamentary star-forming gas clouds: turbulence and magnetic fields

Abstract

We present a statistical analysis of the turbulent line-widths of molecular cloud complexes extracted from high-resolution regions from our ``Cloud Factory'' galactic scale ISM simulation suite. The complexes are at similar evolutionary states but the turbulence is self-consistently generated by different physical mechanisms: a) The ISM dynamics are dominated purely by the large-scale potential of the galactic disc, differential rotation, and random supernovae feedback; b) The galactic potential and supernovae feedback are as above but gas self-gravity is turned on; c) The galactic potential and the self-gravity are turned on but now a burst of supernovae feedback tied to sites of star formation is triggered. To compare to observations, we perform radiative transfer simulations that predict the $^{12}$CO J=1-0 line emission of the representative cloud complexes. Using the synthetic images we then apply the Principal Component Analysis (PCA) reduction technique and estimate a structure linewidth-size relation for each of the physical scenarios. The statistical analysis suggests that, even though purely gravitational effects are necessary to reproduce the standard observational laws and can recreate quiescent regions, they are not sufficient in most cases. We show that the extra injection of energy from clustered supernovae events plays a key role in establishing the global turbulent field and the local dynamics and morphology of molecular clouds in Milky Way-like galaxies. Once this is included, our Cloud Factory simulations generate molecular clouds matching observed scaling laws self-consistently, without the turbulence being put in by hand. We notice and characterise clustering of structure function parameters resulting from clouds in different physical ambiences, which include global diffuse (inner-arm) and dense (spiral-arm) environments, and embedded and outer-cloud supernovae feedback. For quiescent cloud complexes with low (isolated) stellar feedback, we present continuous time-evolving trajectories in the structure function parameter space, driven by gravitational collapse and supersonic turbulent flows at different scales. We observe several signs of intermittency that lead to variations in velocity structure functions depending on analysis scales, especially in our cloud complexes dominated by strong feedback from clustered supernova explosions. All these findings suggest that our PCA-based statistical study is a formidable method to diagnostic local and global surrounding conditions, evolutionary stages and physical mechanisms governing (real and synthetic) molecular clouds. We also present our new open source \pcafactory{} package that collects all the tools developed to set up this work. In addition to this, we assess the role of magnetic fields in reproducing neutral Hydrogen Line self-absorption features (HISA) typical from galactic-disc observations. We use large-scale magnetised and non-magnetised feedback-dominated regions from our Cloud Factory simulation suite and our customised radiative transfer tools to compute H\textsc{i} Line emission and search for absorption features. Although still qualitative results, we find several obscured zones close to the galactic plane in the magnetised case, whereas for the non-magnetised case these features are uncommon and faint due to the large scale-heights produced by strong (uncontrolled) bursts of supernovae. This suggests that magnetic fields can stabilize gas velocity fluctuations and reduce scale-heights, which consequently leads to more realistic scenarios with more and deeper HISA features.

Date of Award	1 Aug 2020
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Gary Fuller (Supervisor) & Rowan Smith (Supervisor)