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Probability density functions (PDFs) of scale-dependent energy fluctuations, $P[\delta E(\ell)]$, are studied in high-resolution direct numerical simulations of Navier-Stokes and incompressible magnetohydrodynamic (MHD) turbulence. MHD…

Fluid Dynamics · Physics 2009-11-13 Mahdi Momeni , Wolf-Christian Müller

We consider 1D Burgers equation driven by large-scale white-in-time random force. The tails of the velocity gradients probability distribution function (PDF) are analyzed by saddle-point approximation in the path integral describing the…

Chaotic Dynamics · Physics 2013-10-01 A. I. Chernykh , M. G. Stepanov

We develop a stochastic model for the velocity gradients dynamics along a Lagrangian trajectory. Comparing with different attempts proposed in the literature, the present model, at the cost of introducing a free parameter known in…

Fluid Dynamics · Physics 2018-02-23 Rodrigo M. Pereira , Luca Moriconi , Laurent Chevillard

Numerical evidence of non-diffusive transport in three-dimensional, resistive pressure-gradient-driven plasma turbulence is presented. It is shown that the probability density function (pdf) of test particles' radial displacements is…

Plasma Physics · Physics 2009-11-10 D. del-Castillo-Negrete , B. A. Carreras , V. E. Lynch

We introduce the position-dependent probability distribution function (PDF) of the smoothed matter field as a cosmological observable. In comparison to the PDF itself, the spatial variation of the position-dependent PDF is simpler to model…

Cosmology and Nongalactic Astrophysics · Physics 2021-04-29 Drew Jamieson , Marilena Loverde

This letter provides the first prediction of the probability density function (PDF) of flux $R$ in plasma sheath sheath region in magnetic fusion devices which is characterized by dynamical equations with exponential non-linearities. By…

Plasma Physics · Physics 2015-05-13 Johan Anderson , Eun-jin Kim

Traditional Bayesian approaches for model uncertainty quantification rely on notoriously difficult processes of marginalization over each network parameter to estimate its probability density function (PDF). Our hypothesis is that internal…

Machine Learning · Computer Science 2021-03-03 Rishabh Singh , Jose C. Principe

We use the physics of ellipsoidal collapse to model the probability distribution function of the smoothed dark matter density field in real and redshift space. We provide a simple approximation to the exact collapse model which shows…

Astrophysics · Physics 2008-08-05 Tsz Yan Lam , Ravi K. Sheth

Grid turbulence is investigated using cross-correlation digital Particle Image Velocimetry (PIV) over a range of Taylor Reynolds Number (Re{\lambda}) from 5 to 44. Instantaneous velocity is measured directly and vorticity and velocity…

Fluid Dynamics · Physics 2021-03-16 Philippa O'Neill , David Nicolaides , Damon Honnery , Julio Soria

The way particles interact with turbulent structures, particularly in regions of high vorticity and strain rate, has been investigated in simulations of homogeneous turbulence and in simple flows which have a periodic or persistent…

Fluid Dynamics · Physics 2012-05-28 Michael W. Reeks

Predicting the dynamics of turbulent fluid flows has long been a central goal of science and engineering. Yet, even with modern computing technology, accurate simulation of all but the simplest turbulent flow-fields remains impossible: the…

Fluid Dynamics · Physics 2025-01-30 Nikita Gourianov , Peyman Givi , Dieter Jaksch , Stephen B. Pope

We study the quasilinear evolution of the one-point probability density functions (PDFs) of the smoothed density and velocity fields in a cosmological gravitating system beginning with Gaussian initial fluctuations. Our analytic results are…

Astrophysics · Physics 2009-10-22 Lev Kofman , Edmund Bertschinger , James M. Gelb , Adi Nusser , Avishai Dekel

The joint probability distribution function (PDF) of the density within multiple concentric spherical cells is considered. It is shown how its cumulant generating function can be obtained at tree order in perturbation theory as the Legendre…

Cosmology and Nongalactic Astrophysics · Physics 2014-11-19 Francis Bernardeau , Christophe Pichon , Sandrine Codis

The Velocity Gradients Technique (VGT) and the Probability Density Functions (PDFs) of mass density are tools to study turbulence, magnetic fields, and self-gravity in molecular clouds. However, self-absorption can significantly make the…

Astrophysics of Galaxies · Physics 2021-01-20 Yue Hu , A. Lazarian

The gravitational evolution of the cosmic one-point Probability Distribution Function (PDF) can be estimated using an analytic approximation that combines gravitational Perturbation Theory (PT) with the Edgeworth expansion around a Gaussian…

Astrophysics · Physics 2007-05-23 P. Fosalba , E. Gaztanaga , E. Elizalde

The decay of homogeneous isotropic turbulence in a variable viscosity fluid with a viscosity ratio up to 15 is analyzed by means of highly resolved direct numerical simulations (DNS) at low Reynolds numbers. The question addressed by the…

Fluid Dynamics · Physics 2018-09-21 Michael Gauding , Luminita Danaila , Emilien Varea

Using a probabilistic neural network and Lagrangian observations from the Global Drifter Program, we model the single particle transition probability density function (pdf) of ocean surface drifters. The transition pdf is represented by a…

Atmospheric and Oceanic Physics · Physics 2023-07-12 Martin T. Brolly

Context: Statistical properties of the cosmic density fields are to a large extent encoded in the shape of the one-point density probability distribution functions (PDF). In order to successfully exploit such observables, a detailed…

Cosmology and Nongalactic Astrophysics · Physics 2022-07-20 Francis Bernardeau

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.…

Soft Condensed Matter · Physics 2007-05-23 Toshihico Arimitsu , Naoko Arimitsu

Stimulated by the need of describing useful notions related to information measures, we introduce the `pdf-related distributions'. These are defined in terms of transformation of absolutely continuous random variables through their own…

Probability · Mathematics 2024-05-02 Antonio Di Crescenzo , Luca Paolillo , Alfonso Suarez-Llorens
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