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 Physics , 1999, DOI: 10.1103/PhysRevLett.83.2572 Abstract: A rigorous study is carried out for the randomly forced Burgers equation in the inviscid limit. No closure approximations are made. Instead the probability density functions of velocity and velocity gradient are related to the statistics of quantities defined along the shocks. This method allows one to compute the anomalies, as well as asymptotics for the structure functions and the probability density functions. It is shown that the left tail for the probability density function of the velocity gradient has to decay faster than $|\xi|^{-3}$. A further argument confirms the prediction of E et al., Phys. Rev. Lett. {\bf 78}, 1904 (1997), that it should decay as $|\xi|^{-7/2}$.
 Physics , 2003, Abstract: The probability density functions measured by Lewis and Swinney for turbulent Couette-Taylor flow, observed by Bodenschatz and co-workers in the Lagrangian measurement of particle accelerations and those obtained in the DNS by Gotoh et al. are analyzed in excellent agreement with the theoretical formulae derived with the multifractal analysis, a unified self-consistent approach based on generalized entropy, i.e., the Tsallis or the Renyi entropy. This analysis rests on the invariance of the Navier-Stokes equation under a scale transformation for high Reynolds number, and on the assumption that the distribution of the exponent $\alpha$, introduced in the scale transformation, is multifractal and that its distribution function is given by taking extremum of the generalized entropy with the appropriate constraints. It also provides analytical formula for the scaling exponents of the velocity structure function which explains quite well the measured quantities in experiments and DNS.
 A. K. Aringazin Physics , 2003, Abstract: Within the framework of one-dimensional Laval-Dubrulle-Nazarenko type model for the Lagrangian acceleration in developed turbulence studied in the work [A.K. Aringazin and M.I. Mazhitov, cond-mat/0305186] we focus on the effect of correlation between the multiplicative noise and the additive one which models the relationship between the stretching and vorticity, and can be seen as a skewness of the probability density function of some acceleration component. The skewness of the acceleration distribution in the laboratory frame of reference should be zero in the ideal case of statistically homogeneous and isotropic developed turbulent flows but when considering acceleration component aligned to fluid particle trajectories it is of much importance in understanding of the cascade picture in the three-dimensional turbulence related to Kolmogorov four-fifths law. We illustrate the effect of nonzero cross correlation parameter $\lambda$. With $\lambda=-0.005$ the transverse ($x$) acceleration probability density function turns out to be in good agreement with the recent experimental data by Mordant, Crawford, and Bodenschatz. In the Random Intensity of Noise (RIN) approach, we study the conditional probability density function and conditional mean acceleration assuming the additive noise intensity to be dependent on velocity fluctutions.
 Physics , 2011, DOI: 10.1088/0169-5983/44/3/031402 Abstract: The probability density functions (PDFs) for energy dissipation rates, created from time-series data of grid turbulence in a wind tunnel, are analyzed in a high precision by the theoretical formulae for PDFs within multifractal PDF theory which is constructed under the assumption that there are two main elements constituting fully developed turbulence, i.e., coherent and incoherent elements. The tail part of PDF, representing intermittent coherent motion, is determined by Tsallis-type PDF for singularity exponents essentially with one parameter with the help of new scaling relation whose validity is checked for the case of the grid turbulence. For the central part PDF representing both contributions from the coherent motion and the fluctuating incoherent motion surrounding the former, we introduced a trial function specified by three adjustable parameters which amazingly represent scaling behaviors in much wider area not restricted to the inertial range. From the investigation of the difference between two difference formulae approximating velocity time-derivative, it is revealed that the connection point between the central and tail parts of PDF extracted by theoretical analyses of PDFs is actually the boundary of the two kinds of instabilities associated respectively with coherent and incoherent elements.
 Physics , 1995, DOI: 10.1103/PhysRevE.52.5681 Abstract: High-resolution numerical experiments, described in this work, show that velocity fluctuations governed by the one-dimensional Burgers equation driven by a white-in-time random noise with the spectrum $\overline{|f(k)|^2}\propto k^{-1}$ exhibit a biscaling behavior: All moments of velocity differences $S_{n\le 3}(r)=\overline{|u(x+r)-u(x)|^n}\equiv\overline{|\Delta u|^n}\propto r^{n/3}$, while $S_{n>3}\propto r^{\zeta_n}$ with $\zeta_n\approx 1$ for real $n>0$ (Chekhlov and Yakhot, Phys. Rev. E {\bf 51}, R2739, 1995). The probability density function, which is dominated by coherent shocks in the interval $\Delta u<0$, is ${\cal P}(\Delta u,r)\propto (\Delta u)^{-q}$ with $q\approx 4$.
 Victor Yakhot Physics , 1997, DOI: 10.1103/PhysRevE.57.1737 Abstract: We consider a few cases of homogeneous and isotropic turbulence differing by the mechanisms of turbulence generation. The advective terms in the Navier-Stokes and Burgers equations are similar. It is proposed that the longitudinal structure functions $S_{n}(r)$ in homogeneous and isotropic three- dimensional turbulence are governed by a one-dimensional equation of motion, resembling the 1D-Burgers equation, with the strongly non-local pressure contributions accounted for by galilean-invariance-breaking terms. The resulting equations, not involving parameters taken from experimental data, give both scaling exponents and amplitudes of the structure functions in an excellent agreement with experimental data. The derived probability density function $P(\Delta u,r)\neq P(-\Delta u,r)$ but $P(\Delta u,r)=P(-\Delta u,-r)$, in accord with the symmetry properties of the Navier-Stokes equations. With decrease of the displacement $r$, the probability density, which cannot be represented in a scale-invariant form, shows smooth variation from the gaussian at the large scales to close-to-exponential function, thus demonstrating onset of small-scale intermittency. It is shown that accounting for the sub-dominant contributions to the structure functions $S_{n}(r)\propto r^{\xi_{n}}$ is crucial for derivation of the amplitudes of the moments of velocity difference.
 Physics , 2012, Abstract: We consider long simulations of 2D Kolmogorov turbulence body-forced by $\sin4y \ex$ on the torus $(x,y) \in [0,2\pi]^2$ with the purpose of extracting simple invariant sets or `exact recurrent flows' embedded in this turbulence. Each recurrent flow represents a sustained closed cycle of dynamical processes which underpins the turbulence. These are used to reconstruct the turbulence statistics in the spirit of Periodic Orbit Theory derived for certain types of low dimensional chaos. The approach is found to be reasonably successful at a low value of the forcing where the flow is close to but not fully in its asymptotic (strongly) turbulent regime. Here, a total of 50 recurrent flows are found with the majority buried in the part of phase space most populated by the turbulence giving rise to a good reproduction of the energy and dissipation probability density functions. However, at higher forcing amplitudes now in the asymptotic turbulent regime, the generated turbulence data set proves insufficiently long to yield enough recurrent flows to make viable predictions. Despite this, the general approach seems promising providing enough simulation data is available since it is open to extensive automation and naturally generates dynamically important exact solutions for the flow.
 Keang-Po Ho Physics , 2003, DOI: 10.1364/OL.28.001350 Abstract: The asymptotic probability density function of nonlinear phase noise, often called the Gordon-Mollenauer effect, is derived analytically when the number of fiber spans is very large. The nonlinear phase noise is the summation of infinitely many independently distributed noncentral chi-square random variables with two degrees of freedom. The mean and standard deviation of those random variables are both proportional to the square of the reciprocal of all odd natural numbers. The nonlinear phase noise can also be accurately modeled as the summation of a noncentral chi-square random variable with two degrees of freedom and a Gaussian random variable.
 Statistics , 2015, Abstract: We show a general relation between the spatially disjoint product of probability density functions and the sum of their Fisher information metric tensors. We then utilise this result to give a method for constructing the probability density functions for an arbitrary Riemannian Fisher information metric tensor. We note further that this construction is extremely unconstrained, depending only on certain continuity properties of the probability density functions and a select symmetry of their domains.
 Physics , 2008, DOI: 10.1016/j.aop.2008.06.004 Abstract: Fox's H-function provide a unified and elegant framework to tackle several physical phenomena. We solve the space fractional diffusion equation on the real line equipped with a delta distribution initial condition and identify the corresponding H-function by studying the small $x$ expansion of the solution. The asymptotic expansions near zero and infinity are expressed, for rational values of the index $\alpha$, in terms of a finite series of generalized hypergeometric functions. In $x$-space, the $\alpha=1$ stable law is also derived by solving the anomalous diffusion equation with an appropriately chosen infinitesimal generator for time translations. We propose a new classification scheme of stable laws according to which a stable law is now characterized by a generating probability density function. Knowing this elementary probability density function and bearing in mind the infinitely divisible property we can reconstruct the corresponding stable law. Finally, using the asymptotic behavior of H-function in terms of hypergeometric functions we can compute closed expressions for the probability density functions depending on their parameters $\alpha, \beta, c, \tau$. Known cases are then reproduced and new probability density functions are presented.
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