Density probability distribution in one-dimensional polytropic gas dynamics

We discuss the generation and statistics of the density fluctuations in highly compressible polytropic turbulence, based on a simple model and one-dimensional numerical simulations. Observing that density structures tend to form in a hierarchical manner, we assume that density fluctuations follow a random multiplicative process. When the polytropic exponent $\gamma$ is equal to unity, the local Mach number is independent of the density, and our assumption leads us to expect that the probability density function (PDF) of the density field is a lognormal. This isothermal case is found to be singular, with a dispersion $\sigma_s^2$ which scales like the square turbulent Mach number $\tilde M^2$, where $s\equiv \ln \rho$ and $\rho$ is the fluid density. This leads to much higher fluctuations than those due to shock jump relations. Extrapolating the model to the case $\gamma \not =1$, we find that, as the Mach number becomes large, the density PDF is expected to asymptotically approach a power-law regime, at high densities when $\gamma<1$, and at low densities when $\gamma>1$. This effect can be traced back to the fact that the pressure term in the momentum equation varies exponentially with $s$, thus opposing the growth of fluctuations on one side of the PDF, while being negligible on the other side. This also causes the dispersion $\sigma_s^2$ to grow more slowly than $\tilde M^2$ when $\gamma\not=1$. In view of these results, we suggest that Burgers flow is a singular case not approached by the high-$\tilde M$ limit, with a PDF that develops power laws on both sides.Comment: 9 pages + 12 postscript figures. Submitted to Phys. Rev.

A method for reconstructing the variance of a 3D physical field from 2D observations: Application to turbulence in the ISM

We introduce and test an expression for calculating the variance of a physical field in three dimensions using only information contained in the two-dimensional projection of the field. The method is general but assumes statistical isotropy. To test the method we apply it to numerical simulations of hydrodynamic and magnetohydrodynamic turbulence in molecular clouds, and demonstrate that it can recover the 3D normalised density variance with ~10% accuracy if the assumption of isotropy is valid. We show that the assumption of isotropy breaks down at low sonic Mach number if the turbulence is sub-Alfvenic. Theoretical predictions suggest that the 3D density variance should increase proportionally to the square of the Mach number of the turbulence. Application of our method will allow this prediction to be tested observationally and therefore constrain a large body of analytic models of star formation that rely on it.Comment: 8 pages, 9 figures, accepted for publication in MNRA

The pressure distribution in thermally bistable turbulent flows

We present a systematic numerical study of the effect of turbulent velocity fluctuations on the thermal pressure distribution in thermally bistable flows. The simulations employ a random turbulent driving generated in Fourier space rather than star-like heating. The turbulent fluctuations are characterized by their rms Mach number M and the energy injection wavenumber, k_for. Our results are consistent with the picture that as either of these parameters is increased, the local ratio of turbulent crossing time to cooling time decreases, causing transient structures in which the effective behavior is intermediate between the thermal-equilibrium and adiabatic regimes. As a result, the effective polytropic exponent gamma_ef ranges between ~0.2 to ~1.1. The fraction of high-density zones with P>10^4 Kcm^-3 increases from roughly 0.1% at k_for=2 and M=0.5 to roughly 70% for k_for=16 and M=1.25. A preliminary comparison with the pressure measurements of Jenkins (2004) favors our case with M=0.5 and k_for=2. In all cases, the dynamic range of the pressure summed over the entire density range, typically spans 3-4 orders of magnitude. The total pressure histogram widens as the Mach number is increased, and develops near-power-law tails at high (resp.low) pressures when gamma_ef<~ 0.5 (resp. gamma_ef>~ 1), which occurs at k_for=2 (resp.k_for=16) in our simulations. The opposite side of the pressure histogram decays rapidly, in an approx. lognormal form. Our results show that turbulent advection alone can generate large pressure scatters, with power-law high-P tails for large-scale driving, and provide validation for approaches attempting to derive the shape of the pressure histogram through a change of variable from the known form of the density histogram, such as that performed by MacLow et al.(2004).Comment: to be published in Ap

A method for reconstructing the PDF of a 3D turbulent density field from 2D observations

We introduce a method for calculating the probability density function (PDF) of a turbulent density field in three dimensions using only information contained in the projected two-dimensional column density field. We test the method by applying it to numerical simulations of hydrodynamic and magnetohydrodynamic turbulence in molecular clouds. To a good approximation, the PDF of log(normalised column density) is a compressed, shifted version of the PDF of log(normalised density). The degree of compression can be determined observationally from the column density power spectrum, under the assumption of statistical isotropy of the turbulence.Comment: 5 pages, 2 figures, accepted for publication in MNRAS Letter

Cooling Flows of Self-Gravitating, Rotating, Viscous Systems

We obtain self-similar solutions that describe the dynamics of a self-gravitating, rotating, viscous system. We use simplifying assumptions; but explicitly include viscosity and the cooling due to the dissipation of energy. By assuming that the turbulent dissipation of energy is as power law of the density and the speed v_{rms} and for a power-law dependence of viscosity on the density, pressure, and rotational velocity, we investigate turbulent cooling flows. It has been shown that for the cylindrically and the spherically cooling flows the similarity indices are the same, and they depend only on the exponents of the dissipation rate and the viscosity model. Depending on the values of the exponents, which the mechanisms of the dissipation and viscosity determine them, we may have solutions with different general physical properties. The conservation of the total mass and the angular momentum of the system strongly depends on the mechanisms of energy dissipation and the viscosity model.Comment: 19 pages, 5 figures, To appear in ApJ (scheduled for the v574, July 20, 2002