Mathematics – Probability
Scientific paper
May 2000
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2000aas...196.2603m&link_type=abstract
American Astronomical Society, 196th AAS Meeting, #26.03; Bulletin of the American Astronomical Society, Vol. 32, p.710
Mathematics
Probability
Scientific paper
Strongly supersonic, mildly super-Alfvénic turbulence has been proposed to be the best model for the structure of star-forming molecular clouds. We characterize 3D numerical models of decaying and uniformly driven, isothermal, supersonic, super-Alfénic turbulence in order to compare it with observations of molecular clouds and determine the properties of the observed turbulence. We study a number of different statistical descriptions of the turbulence. The Δ -variance proposed by Stutzki et al. is an averaged wavelet transform revealing structure at different scales. Observations tend to show power-law, self-similar behavior for the Δ -variance, which we can reproduce only with strongly supersonic, weakly magnetized models driven from the largest available scales. The shapes of velocity difference probability distribution functions also only agree with observations in the case of large-scale driving and weak magnetic fields. Study of the distribution of shock velocities in the turbulence reveals that decaying turbulence differs markedly from continuously driven turbulence. We find decaying turbulence to have an exponential tail of high-velocity shocks, with the number of shocks per velocity interval over time t excellently fit by the function t-ktv for shock jump v and initial driving wavenumber k. This form can be derived from an analytic extension of mapping closure techniques. Driven turbulence, on the other hand, has an inverse square-root distribution of high-velocity shocks. The power dissipation per unit velocity can be readily derived for both of these types of turbulence, enabling direct comparison to observations. Inclusion of self-gravity adds a number of strong, dissipative accretion shocks, but does not change the overall behavior.
Heitsch Fabian
Mac Low Mordecai-Mar
Ossenkopf Volker
Smith Masson D.
Zuev Julia M.
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