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In this paper, we provide closed form expressions for the probability density functions (PDF) of the interference power in a network whose transmitters are arranged according to the Poisson Point Process (PPP). These expressions apply for…

Information Theory · Computer Science 2018-03-29 Hussein A. Ammar , Youssef Nasser , Hassan Artail

Solar wind turbulence is often perceived as weakly compressible and the density fluctuations remain poorly understood both theoretically and observationally. Compressible magnetohydrodynamic simulations provide useful insights into the…

Space Physics · Physics 2023-04-12 Senbei Du , Hui Li , Zhaoming Gan , Xiangrong Fu

The local streamline topology classification method of Chong et al. (1990) is adapted and extended to describe the geometry of infinitesimal vortex lines. Direct numerical simulation (DNS) data of forced isotropic turbulence reveals that…

Fluid Dynamics · Physics 2023-06-22 Bajrang Sharma , Rishita Das , Sharath S. Girimaji

Generalized universality, as recently proposed, postulates a universal non-Gaussian form of the probability density function (PDF) of certain global observables for a wide class of highly correlated systems of finite volume N. Studying the…

Statistical Mechanics · Physics 2009-11-11 G. Mack , G. Palma , L. Vergara

We propose the tensorizing flow method for estimating high-dimensional probability density functions from the observed data. The method is based on tensor-train and flow-based generative modeling. Our method first efficiently constructs an…

Machine Learning · Computer Science 2022-12-02 Yinuo Ren , Hongli Zhao , Yuehaw Khoo , Lexing Ying

Based on the canonical correlation analysis we derive series representations of the probability density function (PDF) and the cumulative distribution function (CDF) of the information density of arbitrary Gaussian random vectors as well as…

Information Theory · Computer Science 2022-07-13 Jonathan Huffmann , Martin Mittelbach

We introduce a new functional representation of probability density functions (PDFs) of non-negative random variables via a product of a monomial factor and linear combinations of decaying exponentials with complex exponents. This…

Probability · Mathematics 2018-02-13 Gregory Beylkin , Lucas Monzon , Ignas Satkauskas

Molecular clouds exhibit lognormal probability density functions (PDF) of mass densities, which are thought to arise as a consequence of isothermal, supersonic turbulence. Star formation is then widely assumed to occur in perturbations in…

Astrophysics of Galaxies · Physics 2018-10-10 Evan Scannapieco , Mohammadtaher Safarzadeh

Experimental data in Particle and Nuclear physics, Particle Astrophysics and Radiation Protection Dosimetry are obtained from experimental facilities comprising a complex array of sensors, electronics and software. Computer simulation is…

Data Analysis, Statistics and Probability · Physics 2025-03-06 Nikolay D. Gagunashvili

We elaborate the statistical field theory of Turbulence suggested in the previous paper \cite{M20a}. We clarify and simplify the basic Energy pumping equation of that theory and study mathematical properties of singular field configuration…

High Energy Physics - Theory · Physics 2020-10-13 Alexander Migdal

We consider the tails of probability density function (PDF) for the velocity that satisfies Burgers equation driven by a Gaussian large-scale force. The saddle-point approximation is employed in the path integral so that the calculation of…

chao-dyn · Physics 2015-06-24 E. Balkovsky , G. Falkovich , I. Kolokolov , V. Lebedev

The growth by condensation of small water droplets in a three-dimensional homogeneous isotropic turbulent flow is considered. Within a simple model of advection and condensation, the dynamics and growth of millions of droplets are…

Chaotic Dynamics · Physics 2008-07-15 Alessandra S. Lanotte , Agnese Seminara , Federico Toschi

A probability density function (pdf) encodes the entire stochastic knowledge about data distribution, where data may represent stochastic observations in robotics, transition state pairs in reinforcement learning or any other empirically…

Machine Learning · Computer Science 2018-09-18 Dmitry Kopitkov , Vadim Indelman

We revisit the relation between the variance of three-dimensional (3D) density ($\sigma^{2}_{\rho}$) and that of the projected two-dimensional (2D) column density ($\sigma^{2}_{\Sigma}$) in turbulent media, which is of great importance in…

Astrophysics of Galaxies · Physics 2024-06-26 Heesun Yoon , Jungyeon Cho

We study two limiting cases of turbulence forcing in numerical experiments: solenoidal (divergence-free) forcing, and compressive (curl-free) forcing, and compare our results to observations reported in the literature. We solve the…

Solar and Stellar Astrophysics · Physics 2010-07-16 C. Federrath , J. Roman-Duval , R. Klessen , W. Schmidt , M. -M. Mac Low

Lagrangian stochastic methods are widely used to model turbulent flows. Scarce consideration has, however, been devoted to the treatment of the near-wall region and to the formulation of a proper wall-boundary condition. With respect to…

Fluid Dynamics · Physics 2024-02-07 Guilhem Balvet , Jean-Pierre Minier , Yelva Roustan , Martin Ferrand

One key issue in the probability density function (PDF) approach for disperse two-phase turbulent flows is to close the diffusion term in the phase space. This study aimed to derive a kinetic equation for particle dispersion in turbulent…

Statistical Mechanics · Physics 2020-07-15 De-yu Zhong , Guang-qian Wang , Tie-jian Li , Ming-xi Zhang , You Xia

We compare experimental data and numerical simulations for the dynamics of inertial particles with finite density in turbulence. In the experiment, bubbles and solid particles are optically tracked in a turbulent flow of water using an…

Chaotic Dynamics · Physics 2008-08-28 R. Volk , E. Calzavarini , G. Verhille , D. Lohse , N. Mordant , J. -F. Pinton , F. Toschi

The amplification of magnetic fields in a highly conducting fluid is studied numerically. During growth, the magnetic field is spatially intermittent: it does not uniformly fill the volume, but is concentrated in long thin folded…

Chaotic Dynamics · Physics 2009-11-10 A. A. Schekochihin , S. C. Cowley , J. L. Maron , J. C. McWilliams

Turbulence is a complex phenomenon that has a chaotic nature with multiple spatio-temporal scales, making predictions of turbulent flows a challenging topic. Nowadays, an abundance of high-fidelity databases can be generated by experimental…

Fluid Dynamics · Physics 2022-08-12 Mustafa Z. Yousif , Linqi Yu , Sergio Hoyas , Ricardo Vinuesa , HeeChang Lim