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In this work we introduce correlated random walks on $\Z$. When picking suitably at random the coefficient of correlation, and taking the average over a large number of walks, we obtain a discrete Gaussian process, whose scaling limit is…

Probability · Mathematics 2007-05-23 Enriquez Nathanael

Stochastic models with fractional Brownian motion as source of randomness have become popular since the early 2000s. Fractional Brownian motion (fBm) is a Gaussian process, whose covariance depends on the so-called Hurst parameter $H\in…

Probability · Mathematics 2026-01-22 Anna P. Kwossek , Andreas Neuenkirch , David J. Prömel

We consider a (one-dimensional) branching Brownian motion process with a general offspring distribution having at least two moments, and in which all particles have a drift towards the origin where they are immediately absorbed. It is…

Probability · Mathematics 2018-09-13 Oren Louidor , Santiago Saglietti

In this article, it is suggested that a pedagogical point of departure in the teaching of classical mechanics is the Liouville theorem. The theorem is interpreted to define the condition that describe the conservation of information in…

Statistical Mechanics · Physics 2022-07-14 Andreas Henriksson

We present certain mathematical aspects of an information method which was formulated in an attempt to investigate diffusion phenomena. We imagine a regular dynamical hamiltonian systems under the random perturbation of thermal (molecular)…

Statistical Mechanics · Physics 2007-05-23 Qiuping A. Wang , Wei Li

We present an innovating sensitivity analysis for stochastic differential equations: We study the sensitivity, when the Hurst parameter~$H$ of the driving fractional Brownian motion tends to the pure Brownian value, of probability…

Probability · Mathematics 2017-02-14 Alexandre Richard , Denis Talay

The approach to the theory of a relativistic random process is considered by the path integral method as Brownian motion taking into account the boundedness of speed. An attempt was made to build a relativistic analogue of the Wiener…

General Relativity and Quantum Cosmology · Physics 2024-05-30 E. A. Kurianovich , A. I. Mikhailov , I. V. Volovich

The stochastic rotational invariance of an integration by parts formula inspired by the Bismut approach to Malliavin calculus is proved in the framework of the Lie symmetry theory of stochastic differential equations. The non-trivial effect…

Probability · Mathematics 2025-06-16 Susanna Dehò , Francesco C. De Vecchi , Paola Morando , Stefania Ugolini

Motivated by subdiffusive motion of bio-molecules observed in living cells we study the stochastic properties of a non-Brownian particle whose motion is governed by either fractional Brownian motion or the fractional Langevin equation and…

Statistical Mechanics · Physics 2016-09-08 Jae-Hyung Jeon , Ralf Metzler

We obtain a maximum principle for stochastic control problem of general controlled stochastic differential systems driven by fractional Brownian motions (of Hurst parameter $H>1/2$). This maximum principle specifies a system of equations…

Optimization and Control · Mathematics 2012-03-15 Yuecai Han , Yaozhong Hu , Jian Song

Fractional Brownian motion is a non-Markovian Gaussian process $X_t$, indexed by the Hurst exponent $H$. It generalises standard Brownian motion (corresponding to $H=1/2$). We study the probability distribution of the maximum $m$ of the…

Statistical Mechanics · Physics 2015-11-25 Mathieu Delorme , Kay Joerg Wiese

The Langevin equation with multiplicative noise and state-dependent transport coefficient has to be always complemented with the proper interpretation rule of the noise, such as the Ito and Stratonovich conventions. Although the…

Statistical Mechanics · Physics 2013-12-05 Takeshi Kuroiwa , Kunimasa Miyazaki

A short review of the classical theory of Brownian motion is presented. A new method is proposed for derivation of the Fokker-Planck equations, describing the probability density evolution, from stochastic differential equations. It is also…

Statistical Mechanics · Physics 2011-04-07 Roumen Tsekov

Fractional Brownian motion is a non-Markovian Gaussian process indexed by the Hurst exponent $H\in [0,1]$, generalising standard Brownian motion to account for anomalous diffusion. Functionals of this process are important for practical…

Statistical Mechanics · Physics 2021-11-24 Tridib Sadhu , Kay Jörg Wiese

The stochastic theory of non-relativistic quantum mechanics presented here relies heavily upon the theory of stochastic processes, with its definitions, theorems and specific vocabulary as well. Its main hypothesis states indeed that the…

Quantum Physics · Physics 2014-04-01 Maurice J. M. L. O. Godart

We report in this paper a thorough study on the the dynamical mechanics of the fractional Brownian motion systems. Where several non-trivial properties are revealed such as the abundant non-Markovian effects resulted from the fractional…

Statistical Mechanics · Physics 2015-02-24 Chun-Yang Wang , Shu-Qin Lv , Ming Yi

A stochastic Langevin equation is derived, describing the thermal motion of a molecule immersed in a rested fluid of identical molecules. The fluctuation-dissipation theorem is proved and a number of correlation characteristics of the…

Statistical Mechanics · Physics 2014-11-11 Roumen Tsekov

Dynamical random walk of classical particle in thermodynamically equilibrium fluctuating medium, - Gaussian random potential field, - is considered in the framework of explicit stochastic representation of deterministic interactions. We…

Statistical Mechanics · Physics 2013-02-05 Yu. E. Kuzovlev

Under certain mild conditions, some limit theorems for functionals of two independent Gaussian processes are obtained. The results apply to general Gaussian processes including fractional Brownian motion, sub-fractional Brownian motion and…

Probability · Mathematics 2018-01-30 Jian Song , Fangjun Xu , Qian Yu

In this article we show a robustness theorem for controlled stochastic differential equations driven by approximations of Brownian motion. Often, Brownian motion is used as an idealized model of a diffusion where approximations such as…

Optimization and Control · Mathematics 2023-12-07 Somnath Pradhan , Zachary Selk , Serdar Yüksel
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