Simulations of Supersonic Turbulence in Magnetized Molecular Clouds

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We report first results from three-dimensional numerical simulations of supersonic magnetohydrodynamic (MHD) turbulence with the Piecewise Parabolic Method on Local Stencil (PPML, Popov & Ustyugov 2008). PPML is a multi-dimensional higher-order Godunov scheme that preserves monotonicity of solutions in the vicinity of strong discontinuities, and maintains zero divergence of the magnetic field through a constrained transport approach. The method is very accurate, extremely low-dissipation, and perfectly stable for super-Alfv'enic turbulence, where many other MHD schemes experience difficulties.
We solve the equations of ideal MHD in a periodic domain on Cartesian grids of up to 1024^3 points. Our models describe driven turbulence at Mach 10 and assume an isothermal equation of state to mimic the conditions in molecular clouds. We start with uniform gas density and uniform magnetic field aligned with one of the coordinate directions and apply large-scale solenoidal force to develop a saturated turbulent state in a statistical equilibrium. Depending on the initial field strength, B_0, a saturation is reached within three-to-six dynamical times of driving. We then collect the turbulence statistics and compare those for different models.
As predicted by Kritsuk et al. (2007), for weak initial fields we get Kolmogorov spectra for the density-weighted velocities ρ^{1/3}u. With stronger fields, the spectra tend to get shallower, but the -5/3 scaling still appears to hold (even in these highly compressible, magnetized flows) for a combination of kinetic and magnetic variables constructed in the spirit of Politano & Pouquet (1998). We compare PDFs, structure functions, and power spectra from runs with different B_0 and discuss the signature of magnetic field in the statistical properties of molecular cloud turbulence and their role in overall flow dynamics.
This research was partially supported by NSF grants AST0607675, AST0808184, and by NRAC allocation MCA07S014. We utilized computing resources provided by NICS, TACC, and SDSC.

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