Density Probability Distribution Functions in Supersonic Hydrodynamic and MHD Turbulence

TL;DR

This paper investigates the probability distribution functions of mass density in supersonic turbulence, revealing similarities and variability in hydrodynamic and MHD cases, and highlighting the limitations of using PDFs to infer magnetic field strength.

Contribution

It provides new insights into the relationship between density PDFs and Mach number in both driven and decaying turbulence, using advanced simulations with Athena.

Findings

Similar mean-Mach relations in driven hydrodynamic and MHD turbulence

Large scatter indicates high variability in the density PDF

Decaying turbulence PDFs differ significantly from driven cases

Abstract

We study the probability distribution function (PDF) of the mass density in simulations of supersonic turbulence with properties appropriate for molecular clouds. For this study we use Athena, a new higher-order Godunov code. We find there are surprisingly similar relationships between the mean of the time-averaged PDF and the turbulent Mach number for driven hydrodynamic and strong-field MHD turbulence. There is, however, a large scatter about these relations, indicating a high level of temporal and spatial variability in the PDF. Thus, the PDF of the mass density is unlikely to be a good measure of magnetic field strength. We also find the PDF of decaying MHD turbulence deviates from the mean-Mach relation found in the driven case. This implies that the instantaneous Mach number alone is not enough to determine the statistical properties of turbulence that is out of equilibrium. The scatter about the mean-Mach relation for driven turbulence, along with the large departure of decaying turbulence PDFs from those of driven turbulence, may illuminate one factor contributing to the large observed cloud-to-cloud variation in the star formation rate per solar mass.