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The purpose of this tutorial is to introduce the main concepts behind normal and anomalous diffusion. Starting from simple, but well known experiments, a series of mathematical modeling tools are introduced, and the relation between them is…

Chaotic Dynamics · Physics 2008-05-06 Loukas Vlahos , Heinz Isliker , Yannis Kominis , Kyriakos Hizanidis

In this article we propose a generalization of the theory of diffusion approximation for random ODE to a nonlinear system of random Schr\"{o}dinger equations. This system arises in the study of pulse propagation in randomly birefringent…

Analysis of PDEs · Mathematics 2012-12-14 A. de Bouard , M. Gazeau

Of stochastic differential equations, diffusion processes have been adopted in numerous applications, as more relevant and flexible models. This paper studies diffusion processes in a different setting, where for a given stationary…

Probability · Mathematics 2024-12-31 Saber Jafarizadeh

The Fleming-Viot process describes a system of $N$ particles diffusing on a graph with an absorbing site. Whenever one of the particles is absorbed, it is replaced by a new particle at the position of one of the $N-1$ remaining particles.…

Statistical Mechanics · Physics 2026-01-23 Éric Brunet , Bernard Derrida

Reaction-diffusion equations deliver a versatile tool for the description of reactions in inhomogeneous systems under the assumption that the characteristic reaction scales and the scales of the inhomogeneities in the reactant…

Statistical Mechanics · Physics 2009-11-11 M. G. W. Schmidt , F. Sagues , I. M. Sokolov

Mathematical models for the stochastic evolution of wave functions that combine the unitary evolution according to the Schroedinger equation and the collapse postulate of quantum theory are well understood for non-relativistic quantum…

We discuss general positivity conditions necessary for a definition of a relativistic diffusion on the phase space. We show that Lorentz covariant random vector fields on the forward cone $p^{2}\geq 0$ lead to a definition of a generator of…

Statistical Mechanics · Physics 2012-05-08 Z. Haba

Einstein's explanation of Brownian motion provided one of the cornerstones which underlie the modern approaches to stochastic processes. His approach is based on a random walk picture and is valid for Markovian processes lacking long-term…

Statistical Mechanics · Physics 2009-11-10 I. M. Sokolov , J. Klafter

Diffusion models are loosely modelled based on non-equilibrium thermodynamics, where \textit{diffusion} refers to particles flowing from high-concentration regions towards low-concentration regions. In statistics, the meaning is quite…

Machine Learning · Computer Science 2023-12-19 Inga Strümke , Helge Langseth

We consider a one-dimensional stochastic differential equation driven by a Wiener process, where the diffusion coefficient depends on an ergodic fast process. The averaging principle is satisfied: it is well-known that the slow component…

Probability · Mathematics 2021-04-30 Charles-Edouard Bréhier

Diffusive transport of a particle in spatially correlated random energy landscape having exponential density of states has been considered. We exactly calculate the diffusivity in the nondispersive quasi-equilibrium transport regime and…

Disordered Systems and Neural Networks · Physics 2018-02-14 S. V. Novikov

The interpretation proposed in quant-ph/9812011 is extended to the general case of a non-relativistic particle moving in an arbitrary external potential. It is shown that, even in this general case, "particle" solutions exist which do not…

Quantum Physics · Physics 2007-05-23 A. Raiteri

We show that relativistic fluids behave as non-Newtonian fluids. First, we discuss the problem of acausal propagation in the diffusion equation and introduce the modified Maxwell-Cattaneo-Vernotte (MCV) equation. By using the modified MCV…

High Energy Physics - Phenomenology · Physics 2015-05-20 Tomoi Koide

Diffusion models learn to reverse the progressive noising of a data distribution to create a generative model. However, the desired continuous nature of the noising process can be at odds with discrete data. To deal with this tension…

Machine Learning · Computer Science 2023-09-13 Griffin Floto , Thorsteinn Jonsson , Mihai Nica , Scott Sanner , Eric Zhengyu Zhu

Random walks are a fundamental model in applied mathematics and are a common example of a Markov chain. The limiting stationary distribution of the Markov chain represents the fraction of the time spent in each state during the stochastic…

Numerical Analysis · Computer Science 2018-01-08 Austin R. Benson , David F. Gleich , Lek-Heng Lim

Diffusion processes are a class of stochastic differential equations (SDEs) providing a rich family of expressive models that arise naturally in dynamic modelling tasks. Probabilistic inference and learning under generative models with…

Machine Learning · Computer Science 2024-02-28 Prakhar Verma , Vincent Adam , Arno Solin

A novel probabilistic framework for modelling anomalous diffusion is presented. The resulting process is Markovian, non-homogeneous, non-stationary, non-ergodic, and state-dependent. The fundamental law governing this process is driven by…

Mathematical Physics · Physics 2025-03-07 Nestor Barraza , Gabriel Pena , Juliana Gambini , Florencia Carusela

The system under study is a reaction-diffusion equation in a horizontal strip, coupled to a diffusion equation on its upper boundary via an exchange condition of the Robin type. This class of models was introduced by H. Berestycki, L. Rossi…

Analysis of PDEs · Mathematics 2016-03-16 Laurent Dietrich , Jean-Michel Roquejoffre

We consider diffusion processes with the help of Markov random walk models. Especially the process of diffusion of a relativistic particle in a relativistic equilibrium system is considered. We interpret one of the results as causal Zeno…

Statistical Mechanics · Physics 2009-10-26 Ji-Rong Ren , Ming-fan Li , Tao Zhu

Motivated by a probabilistic approach to Kahler-Einstein metrics we consider a general non-equilibrium statistical mechanics model in Euclidean space consisting of the stochastic gradient flow of a given (possibly singular) quasi-convex…

Mathematical Physics · Physics 2016-10-17 Robert J. Berman , Magnus Onnheim