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Comparing the statistics of interstellar turbulence in simulations and observations - Solenoidal versus compressive turbulence forcing

TLDR
In this paper, the authors study two limiting cases of turbulence forcing in numerical experiments: solenoidal (divergence-free) forcing and compressive (curl-free), and compare their results to observations.
Abstract
Context. Density and velocity fluctuations on virtually all scales observed with modern telescopes show that molecular clouds (MCs) are turbulent. The forcing and structural characteristics of this turbulence are, however, still poorly understood.Aims. To shed light on this subject, we study two limiting cases of turbulence forcing in numerical experiments: solenoidal (divergence-free) forcing and compressive (curl-free) forcing, and compare our results to observations.Methods. We solve the equations of hydrodynamics on grids with up to 10243  cells for purely solenoidal and purely compressive forcing. Eleven lower-resolution models with different forcing mixtures are also analysed.Results. Using Fourier spectra and Δ -variance, we find velocity dispersion-size relations consistent with observations and independent numerical simulations, irrespective of the type of forcing. However, compressive forcing yields stronger compression at the same rms Mach number than solenoidal forcing, resulting in a three times larger standard deviation of volumetric and column density probability distributions (PDFs). We compare our results to different characterisations of several observed regions, and find evidence of different forcing functions. Column density PDFs in the Perseus MC suggest the presence of a mainly compressive forcing agent within a shell, driven by a massive star. Although the PDFs are close to log-normal, they have non-Gaussian skewness and kurtosis caused by intermittency. Centroid velocity increments measured in the Polaris Flare on intermediate scales agree with solenoidal forcing on that scale. However, Δ -variance analysis of the column density in the Polaris Flare suggests that turbulence is driven on large scales, with a significant compressive component on the forcing scale. This indicates that, although likely driven with mostly compressive modes on large scales, turbulence can behave like solenoidal turbulence on smaller scales. Principal component analysis of G216-2.5 and most of the Rosette MC agree with solenoidal forcing, but the interior of an ionised shell within the Rosette MC displays clear signatures of compressive forcing.Conclusions. The strong dependence of the density PDF on the type of forcing must be taken into account in any theory using the PDF to predict properties of star formation. We supply a quantitative description of this dependence. We find that different observed regions show evidence of different mixtures of compressive and solenoidal forcing, with more compressive forcing occurring primarily in swept-up shells. Finally, we emphasise the role of the sonic scale for protostellar core formation, because core formation close to the sonic scale would naturally explain the observed subsonic velocity dispersions of protostellar cores.

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Citations
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Journal ArticleDOI

A new class of accurate, mesh-free hydrodynamic simulation methods

TL;DR: In this paper, a Lagrangian method for hydrodynamics is proposed to simultaneously capture advantages of both SPH and grid-based/adaptive mesh refinement (AMR) schemes.
Journal ArticleDOI

The Star Formation Rate of Turbulent Magnetized Clouds: Comparing Theory, Simulations, and Observations

TL;DR: In this paper, the role of turbulence and magnetic fields in star formation in molecular clouds is studied, and it is shown that the SFR depends on four basic parameters: (1) virial parameter αvir; (2) sonic Mach number ; (3) turbulent forcing parameter b, which is a measure for the fraction of energy driven in compressive modes; and (4) plasma with the Alfven Mach number.
Journal ArticleDOI

Turbulent molecular clouds

TL;DR: In this article, the authors review the observational and theoretical knowledge of molecular clouds trying to confront the two approaches wherever possible, and emphasize the dynamical processes with special focus to turbulence and its impact on cloud evolution.
References
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Journal ArticleDOI

The Piecewise Parabolic Method (PPM) for Gas Dynamical Simulations

TL;DR: This work recognizes the need for additional dissipation in any higher-order Godunov method of this type, and introduces it in such a way so as not to degrade the quality of the results.
Journal ArticleDOI

Theory of Star Formation

TL;DR: In this paper, an overall theoretical framework and the observations that motivate it are outlined, outlining the key dynamical processes involved in star formation, including turbulence, magnetic fields, and self-gravity.
Journal Article

A class of distributions which includes the normal ones

TL;DR: In this paper, a nouvelle classe de fonctions de densite dependant du parametre de forme λ, telles que λ=0 corresponde a la densite normale standard.
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