Density, Velocity, and Magnetic Field Structure in Turbulent Molecular Cloud Models

Abstract

We use three-dimensional (3D) numerical magnetohydrodynamic simulations to follow the evolution of cold, turbulent, gaseous systems with parameters chosen to represent conditions in giant molecular clouds (GMCs). We present results of three model cloud simulations in which the mean magnetic field strength is varied (B 0 = 1.4− 14 µG for GMC parameters), but an identical initial turbulent velocity field is introduced. We describe the energy evolution, showing that (i) turbulence decays rapidly, with the turbulent energy reduced by a factor two after 0.4-0.8 flow crossing times (∼ 2 − 4 Myr for GMC parameters), and (ii) the magnetically supercritical cloud models gravitationally collapse after time ≈ 6 Myr, while the magnetically subcritical cloud does not collapse.We compare density, velocity, and magnetic field structure in three sets of model "snapshots" with matched values of the Mach number M ≈ 9, 7, 5. We show that the distributions of volume density and column density are both approximately log-normal, with mean mass-weighted volume density a factor 3 − 6 times the unperturbed value, but mean mass-weighted column density only a factor 1.1 − 1.4 times the unperturbed value. We introduce a spatial binning algorithm to investigate the dependence of kinetic quantities on spatial scale for regions of column density contrast (ROCs) on the plane of the sky. We show that the average velocity dispersion for the distribution of ROCs is only weakly correlated with scale, similar to mean size-linewidth distributions for clumps within GMCs. We find that ROCs are often superpositions of spatially unconnected regions that cannot easily be separated using velocity information; we argue that the same difficulty may affect observed GMC clumps. We suggest that it may be possible to deduce the mean 3D size-linewidth relation using the lower envelope of the 2D sizelinewidth distribution. We analyze magnetic field structure, and show that in the high density regime n H 2 > ∼ 10 3 cm −3 , total magnetic field strengths increase with density with logarithmic slope ∼ 1/3 − 2/3. We find that mean line-of-sight magnetic field strengths may vary widely across a projected cloud, and are not positively correlated with column density. We compute simulated interstellar polarization maps at varying observer orientations, and determine that the Chandrasekhar-Fermi formula multiplied by a factor ∼ 0.5 yields a good estimate of the plane-of sky magnetic field strength, provided the dispersion in polarization angles is < ∼ 25 • .

Molecular cloud formation as seen in synthetic H i and molecular gas observations

“…Early studies simply investigated line-ofsight (LOS) projections of the density field from numerical simulations, and perhaps investigated the column density in the velocity coordinate (line profiles and channel maps) (e.g., Ballesteros-Paredes et al 1999;Pichardo et al 2000;Ostriker et al 2001;Ballesteros-Paredes & Mac Low 2002), although without performing synthetic observations based on integration of the radiative transfer (RT) equation for the various lines involved. A further step was made by Ballesteros-Paredes & Mac Low (2002) who, in order to study the internal structure of molecular clouds, created synthetic CO and CS line profiles in local thermal equilibrium from numerical simulations of isothermal molecular clouds.…”

Young Star Clusters in the Small Magellanic Cloud: Impact of Local and Global Conditions on Star Formation

“…The formation of shocks in the gas, due to the initial supersonic turbulence, should rapidly remove kinetic energy from the gas (Ostriker et al 2001). Therefore to further confirm the origin of NGC 346, we observed many sub-clusters with the University College London Echelle Spectrograph (UCLES) at the Anglo-Australian Telescope.…”

Galaxy evolution: modelling the role of non-thermal pressure in the interstellar medium

“…We demonstrate that non-thermal pressure components can be instrumental in solving the depletion time discrepancy in two respects: they reduce the quasi-steady state density and the corresponding star formation rates and cooling times, and they stabilize the gas by adding longer relaxation times in cases where star formation flickers on and off. The regulating effect has been shown previously for cosmic rays (Salem & Bryan 2014;Booth et al 2013;Hanasz et al 2013) and turbulence (Ostriker et al 2001;Braun & Schmidt 2012) but the two were not considered together and in any case were not yet formulated in a way which is applicable to large scale cosmological simulations.…”

“…Nonhomogeneity in the ISM is expected (see for example Ostriker et al 2001) and implies that the external pressure boundary conditions should vary in space and time. We demonstrate that this principle applies also in the case of …”