Monday, June 30, 2014 - 11:00am
Lukas Konstandin (ZAH/ITA):
"Resolving the statistical properties of supersonic turbulence in numerical simulations"
Abstract. Observations show that supersonic turbulence is prevalent in star forming clouds. The density and velocity field in these clouds indicate complex, chaotic, and filamentary structures, where turbulent motions interact with shocks. Therefore, understanding the properties of turbulence is a prerequisite for developing a comprehensive theory of star formation in the ISM. We have studied three-dimensional numerical simulations of driven, isothermal, turbulence with r.m.s. Mach numbers ranging from the subsonic to the highly supersonic regime. We focused on the influence of two extreme cases for the driving mechanism by applying a purely solenoidal (divergence-free) and a purely compressive (curl-free) forcing field to drive the turbulence. Incompressible and compressible turbulence theories predict a power-law for the energy-density power spectrum in the inertial range, where the scaling exponent plays a key role to distinguish between the different cases. I will introduce a hierarchical Bayesian method for estimating the parameters of the power spectrum and compare it with classical linear regression methods. The Bayesian measurements reveal that the scaling exponents span the whole range of theoretical predictions depending on the definition of the fitting/inertial range. In addition, I will talk about the interplay between the highly turbulent velocity field and the resulting statistical properties of the density distribution.