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In these lecture notes, we explore the mathematical preliminaries and foundational concepts that connect stochastic processes with partial differential equations. We begin by investigating Brownian motion, which serves as a model for random…

Probability · Mathematics 2025-09-15 Helder Rojas

Laplace's first law of errors, which states that the frequency of an error can be represented as an exponential function of the error magnitude, was overlooked for many decades but was recently shown to describe the statistical behavior of…

Statistical Mechanics · Physics 2025-01-13 Lucianno Defaveri , Eli Barkai

Einstein's theory of Brownian motion is revisited in order to formulate generalized kinetic theory of anomalous diffusion. It is shown that if the assumptions of analyticity and the existence of the second moment of the displacement…

Statistical Mechanics · Physics 2009-11-10 Sumiyoshi Abe , Stefan Thurner

One century after Einstein's work, Brownian Motion still remains both a fundamental open issue and a continous source of inspiration for many areas of natural sciences. We first present a discussion about stochastic and deterministic…

Chaotic Dynamics · Physics 2009-11-10 Fabio Cecconi , Massimo Cencini , Massimo Falcioni , Angelo Vulpiani

We describe the mathematical theory of diffusion and heat transport with a view to including some of the main directions of recent research. The linear heat equation is the basic mathematical model that has been thoroughly studied in the…

Analysis of PDEs · Mathematics 2017-06-27 Juan Luis Vázquez

Thermal diffusion has been studied for over 150 years. Despite of the long history and the increasing importance of the phenomenon, the physics of thermal diffusion remains poorly understood. In this paper Ludwig's thermal diffusion is…

Mathematical Physics · Physics 2013-07-18 Yong-Jung Kim

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

Heat fluctuations over a time \tau in a non-equilibrium stationary state and in a transient state are studied for a simple system with deterministic and stochastic components: a Brownian particle dragged through a fluid by a harmonic…

Statistical Mechanics · Physics 2007-05-23 R. van Zon , E. G. D. Cohen

Einstein's kinetic theory of the Brownian motion, based upon light water molecules continuously bombarding a heavy pollen, provided an explanation of diffusion from the Newtonian mechanics. Since the discovery of quantum mechanics it has…

Mathematical Physics · Physics 2010-09-07 Laszlo Erdos

K. G\"odel [G1] discovered his celebrated solution to Einstein equations in 1949. Additional contributions were made by Kundt [K] and Hawking-Ellis ([H-E],5.7). On the other hand, a general Lorentz invariant operator, associated to the…

Probability · Mathematics 2007-05-23 Jacques Franchi

Diffusion of small particles is omnipresent in a plentiful number of processes occurring in Nature. As such, it is widely studied and exerted in almost all branches of sciences. It constitutes such a broad and often rather complex subject…

Statistical Mechanics · Physics 2023-01-11 Jakub Spiechowicz , Ivan G. Marchenko , Peter Hänggi , Jerzy Łuczka

This is a guide to the mathematical theory of Brownian motion and related stochastic processes, with indications of how this theory is related to other branches of mathematics, most notably the classical theory of partial differential…

Probability · Mathematics 2018-02-28 Jim Pitman , Marc Yor

Brownian motion is a foundational physical process characterized by a mean squared displacement that scales linearly in time in thermal equilibrium, known as diffusion. At short times, the mean squared displacement becomes ballistic,…

Statistical Mechanics · Physics 2026-02-10 Jason Boynewicz , Michael C. Thumann , Mark G. Raizen

The method employed by Einstein to derive his famous relation between the diffusion coefficient and the friction coefficient of a Brownian particle is used to derive a generalized Einstein relation for the mutual diffusion coefficient of a…

Fluid Dynamics · Physics 2017-09-13 B. U. Felderhof

Inspired by many examples in nature, stochastic resetting of random processes has been studied extensively in the past decade. In particular, various models of stochastic particle motion were considered where upon resetting the particle is…

Statistical Mechanics · Physics 2022-11-23 Ofir Tal-Friedman , Yael Roichman , Shlomi Reuveni

Analytical (rational) mechanics is the mathematical structure of Newtonian deterministic dynamics developed by D'Alembert, Langrange, Hamilton, Jacobi, and many other luminaries of applied mathematics. Diffusion as a stochastic process of…

Mathematical Physics · Physics 2012-09-03 Hao Ge , Hong Qian

Treating the motion of a dust particle suspended in a liquid as a random walk, Einstein in 1905 derived an equation describing the diffusion of the particle's probability distribution in configuration space. Fokker and Planck extended this…

Astrophysics · Physics 2009-11-11 Edmund Bertschinger

In this article, we investigate the asymptotic behavior of the solution to a one-dimensional stochastic heat equation with random nonlinear term generated by a stationary, ergodic random field. We extend the well-known central limit theorem…

Probability · Mathematics 2018-09-12 Lu Xu

A stochastic action principle for stochastic dynamics is revisited. We present first numerical diffusion experiments showing that the diffusion path probability depend exponentially on average Lagrangian action. This result is then used to…

Statistical Mechanics · Physics 2020-11-25 Q. A. Wang , F. Tsobnang , S. Bangoup , F. Dzangue , A. Jeatsa , A. Le Méhauté

For the stochastic heat equation with multiplicative noise we consider the problem of estimating the diffusivity parameter in front of the Laplace operator. Based on local observations in space, we first study an estimator that was derived…

Statistics Theory · Mathematics 2024-02-22 Josef Janák , Markus Reiß
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