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Diffusion through semipermeable interfaces has a wide range of applications, ranging from molecular transport through biological membranes to reverse osmosis for water purification using artificial membranes. At the single-particle level,…

Statistical Mechanics · Physics 2023-01-25 Paul C Bressloff

We study the first passage time processes of anomalous diffusion on self similar curves in two dimensions. The scaling properties of the mean square displacement and mean first passage time of the ballistic motion, fractional Brownian…

Statistical Mechanics · Physics 2011-07-29 M. Ghasemi Nezhadhaghighi , M. A. Rajabpour , S. Rouhani

It is quite generally assumed that the overdamped Langevin equation provides a quantitative description of the dynamics of a classical Brownian particle in the long time limit. We establish and investigate a paradigm anomalous diffusion…

Statistical Mechanics · Physics 2016-09-26 A. S. Bodrova , A. V. Chechkin , A. G. Cherstvy , H. Safdari , I. M. Sokolov , R. Metzler

Anomalous diffusion is predicted for Brownian particles in inhomogeneous viscosity landscapes by means of scaling arguments, which are substantiated through numerical simulations. Analytical solutions of the related Fokker-Planck equation…

We solve a model of sluggish stochastic motion in which a Brownian particle diffuses with a diffusion coefficient that decays algebraically with the distance to the origin, as $|x|^{-\alpha}$. Additionally, the particle resets with a…

Statistical Mechanics · Physics 2026-03-03 Denis Boyer , Satya N. Majumdar

In this paper we present a general mathematical construction that allows us to define a parametric class of $H$-sssi stochastic processes (self-similar with stationary increments), which have marginal probability density function that…

Probability · Mathematics 2007-11-06 Antonio Mura , Francesco Mainardi

While it is very common to model diffusion as a random walk by assuming memorylessness of the trajectory and diffusive step lengths, these assumptions can lead to significant errors. This paper describes the extent to which a physical…

Statistical Mechanics · Physics 2025-08-07 Ludovico Cademartiri

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

Physical Brownian motion describes the dynamics of a Brownian particle experiencing frictional force. It was investigated in the classical work [L. S. Ornstein and G. E. Uhlenbeck, Phys. Rev. 36 (1930)] as a physically meaningful approach…

Probability · Mathematics 2026-03-10 Siran Li , Hao Ni , Qianyu Zhu

This paper is devoted to a system of stochastic partial differential equations (SPDEs) that have a slow component driven by fractional Brownian motion (fBm) with the Hurst parameter $H >1/2$ and a fast component driven by fast-varying…

Probability · Mathematics 2021-11-12 Bin Pei , Yuzuru Inahama , Yong Xu

The standard diffusive spreading, characterized by a Gaussian distribution with mean square displacement that grows linearly with time, can break down, for instance, under the presence of correlations and heterogeneity. In this work, we…

Statistical Mechanics · Physics 2021-10-27 M. A. F. dos Santos , E. H. Colombo , C. Anteneodo

This article introduces a novel construction of the two-dimensional fractional Brownian motion (2D fBm) with dependent components. Unlike similar models discussed in the literature, our approach uniquely accommodates the full range of model…

In this paper we study the discrete approximation to Brownian motion with varying dimension (BMVD in abbreviation) introduced in [4] by continuous time random walks on square lattices. The state space of BMVD contains a $2$-dimensional…

Probability · Mathematics 2021-10-26 Shuwen Lou

The Arcsine laws of Brownian motion are a collection of results describing three different statistical quantities of one-dimensional Brownian motion: the time at which the process reaches its maximum position, the total time the process…

Statistical Mechanics · Physics 2023-08-03 Toby Kay , Luca Giuggioli

We consider one-dimensional branching Brownian motion in spatially random branching environment (BBMRE) and show that for almost every realisation of the environment, the distributions of the maximal particle of the BBMRE re-centred around…

Probability · Mathematics 2024-06-25 Jiří Černý , Alexander Drewitz , Pascal Oswald

Inspired by Dai et al. [2023], we develop a novel multi-scaling asymptotic regime for semimartingale reflecting Brownian motion (SRBM). In this regime, we establish the steady-state convergence of SRBM to a product-form limit with…

Probability · Mathematics 2025-06-16 Jin Guang , Xinyun Chen , J. G. Dai , Peter W. Glynn

In this thesis, we extend the recently introduced theory of stochastic modified equations (SMEs) for stochastic gradient optimization algorithms. In Ch. 3 we study time-inhomogeneous SDEs driven by Brownian motion. For certain SDEs we prove…

Probability · Mathematics 2025-11-26 Stefan Perko

This short note is motivated by a recently discovered connection between a drift-diffusion process in $n$-dimensional Euclidean space with a divergence-free drift sampled from a stationary and isotropic Gaussian ensemble of critical scaling…

Probability · Mathematics 2026-03-20 Sefika Kuzgun , Felix Otto , Christian Wagner

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 Mean Square Displacement is a central tool in the analysis of Single Particle Tracking experiments, shedding light on various biophysical phenomena. Frequently, parameters are extracted by performing time-averages on single particle…

Biological Physics · Physics 2013-05-24 Eldad Kepten Irena Bronshtein , Yuval Garini