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In probability density function (PDF) methods of turbulent flows, the joint PDF of several flow variables is computed by numerically integrating a system of stochastic differential equations for Lagrangian particles. A mathematically exact…

Fluid Dynamics · Physics 2010-06-17 J. Bakosi

The topic of this PhD thesis is the derivation of evolution equations for probability density functions (pdfs) describing the non-Markovian response to dynamical systems under Gaussian coloured (smoothly-correlated) noise. These pdf…

Mathematical Physics · Physics 2022-02-01 K. I. Mamis

In this paper the conditions are investigated for the occurrence of the so-called macroscopic irreversibility property and the related phenomenon of decay to kinetic equilibrium which may characterize the $1-$body probability density…

Classical Physics · Physics 2017-03-16 Massimo Tessarotto , Claudio Cremaschini

We study a class of nonlinear kinetic Fokker-Planck type equations modeling quantum particles which obey the Bose-Einstein and Fermi-Dirac statistics, respectively. We establish the existence of classical solutions in the perturbative…

Analysis of PDEs · Mathematics 2007-08-01 Lukas Neumann , Christof Sparber

Stochastic differential equations are commonly used to describe the evolution of stochastic processes. The state uncertainty of such processes is best represented by the probability density function (PDF), whose evolution is governed by the…

Machine Learning · Computer Science 2026-03-03 Chun-Wei Kong , Luca Laurenti , Jay McMahon , Morteza Lahijanian

Integrated Computational Materials Engineering (ICME) models have been a crucial building block for modern materials development, relieving heavy reliance on experiments and significantly accelerating the materials design process. However,…

Computational Engineering, Finance, and Science · Computer Science 2022-03-10 Anh Tran , Jing Sun , Dehao Liu , Tim Wildey , Yan Wang

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

We measure evolution of spectra, spatial correlation functions and probability density functions (PDFs) of waves appearance for a set of one-dimensional NLS-like equations of focusing type, namely for the classical integrable Nonlinear…

Optics · Physics 2015-03-20 Dmitry Agafontsev , Vladimir Zakharov

The solution for non-linear, complex partial differential Equations (PDEs) is achieved through numerical approximations, which yield a linear system of equations. This approach is prevalent in Computational Fluid Dynamics (CFD), but it…

Fluid Dynamics · Physics 2024-09-06 Ferdin Sagai Don Bosco , Dhamotharan S , Rut Lineswala , Abhishek Chopra

We develop a moment equation closure minimization method for the inexpensive approximation of the steady state statistical structure of nonlinear systems whose potential functions have bimodal shapes and which are subjected to correlated…

Chaotic Dynamics · Physics 2015-10-08 Han Kyul Joo , Themistoklis P. Sapsis

The Fokker-Planck Equation (FPE) is a fundamental tool for the investigation of kinematic aspects of a wide range of systems. For systems governed by the non-additive entropy $S_q$, the Plastino-Plastino Equation (PPE) is the correct…

High Energy Physics - Phenomenology · Physics 2023-09-13 Eugenio Megias , Airton Deppman , Roman Pasechnik , Constantino Tsallis

Stochastic partial differential equations (SPDEs) represent a very active research field with numerous recent developments and breakthrough results. There are several well-established approaches and methods used to construct solutions for…

Probability · Mathematics 2019-08-27 Christian Kuehn , Alexandra Neamtu

In quantum mechanics, the probability distribution function (PDF) and full counting statistics (FCS) play a fundamental role in characterizing the fluctuations of quantum observables, as they encode the complete information about these…

Quantum Physics · Physics 2025-10-29 Lata Kh Joshi , Filiberto Ares , Manoj K. Joshi , Christian F. Roos , Pasquale Calabrese

The Fokker-Planck equations describe time evolution of probability densities of stochastic dynamical systems and are thus widely used to quantify random phenomena such as uncertainty propagation. For dynamical systems driven by non-Gaussian…

Dynamical Systems · Mathematics 2015-06-04 Xu Sun , Jinqiao Duan

Random processes play a crucial role in scientific research, often characterized by distribution functions or probability density functions (PDFs). These PDFs serve as essential approximations of the actual and frequently undisclosed…

Methodology · Statistics 2023-06-06 Nico Schick

This Letter provides a theoretical interpretation of numerically generated probability density functions (PDFs) of intermittent plasma transport events. Specifically, nonlinear gyrokinetic simulations of ion-temperature-gradient turbulence…

Plasma Physics · Physics 2010-11-10 Johan Anderson , Pavlos Xanthopoulos

We present a quantum algorithm based on repeated measurement to solve initial-value problems for nonlinear ordinary differential equations (ODEs), which may be generated from partial differential equations in plasma physics. We map a…

Quantum Physics · Physics 2025-04-30 Joseph Andress , Alexander Engel , Yuan Shi , Scott Parker

This paper deals with uncertainty propagation of general stochastic hybrid systems (GSHS) where the continuous state space is a compact Lie group. A computational framework is proposed to solve the Fokker-Planck (FP) equation that describes…

Optimization and Control · Mathematics 2022-03-08 Weixin Wang , Taeyoung Lee

We investigate the single-point velocity probability density function (PDF) in three-dimensional fully developed homogeneous isotropic turbulence within the framework of PDF equations focussing on deviations from Gaussianity. A joint…

Fluid Dynamics · Physics 2011-02-18 Michael Wilczek , Anton Daitche , Rudolf Friedrich

This paper is concerned with stochastic systems whose state is a diffusion process governed by an Ito stochastic differential equation (SDE). In the framework of a nominal white-noise model, the SDE is driven by a standard Wiener process.…

Optimization and Control · Mathematics 2023-05-23 Igor G. Vladimirov