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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

We study the Brownian motion of a classical particle in one-dimensional inhomogeneous environments where the transition probabilities follow quasiperiodic or aperiodic distributions. Exploiting an exact correspondence with the…

Statistical Mechanics · Physics 2009-10-31 F. Igloi , L. Turban , H. Rieger

In this work we study the transition from normal to anomalous diffusion of Brownian particles on disordered potentials. The potential model consists of a series of "potential hills" (defined on unit cell of constant length) whose heights…

Disordered Systems and Neural Networks · Physics 2016-03-23 R. Salgado-Garcia

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

Anomalous diffusion has been widely observed by single particle tracking microscopy in complex systems such as biological cells. The resulting time series are usually evaluated in terms of time averages. Often anomalous diffusion is…

Statistical Mechanics · Physics 2017-09-13 Stas Burov , Jae-Hyung Jeon , Ralf Metzler , Eli Barkai

A possible mechanism leading to anomalous diffusion is the presence of long-range correlations in time between the displacements of the particles. Fractional Brownian motion, a non-Markovian self-similar Gaussian process with stationary…

Statistical Mechanics · Physics 2019-04-03 Alexander H O Wada , Alex Warhover , Thomas Vojta

We consider a model system in which anomalous diffusion is generated by superposition of underlying linear modes with a broad range of relaxation times. In the language of Gaussian polymers, our model corresponds to Rouse (Fourier) modes…

Statistical Mechanics · Physics 2010-03-11 Assaf Amitai , Yacov Kantor , Mehran Kardar

We survey recent results of normal and anomalous diffusion of two types of random motions with long memory in ${\Bbb R}^d$ or ${\Bbb Z}^d$. The first class consists of random walks on ${\Bbb Z}^d$ in divergence-free random drift field,…

Probability · Mathematics 2019-01-01 Bálint Tóth

The diffusion process near low order synchro-betatron resonances driven by beam-beam interactions at a crossing angle is investigated. Macroscopic observables such as beam emittance, lifetime and beam profiles are calculated. These are…

Accelerator Physics · Physics 2015-06-05 Tanaji Sen

We derive an anomalous, sub-diffusive scaling limit for a one-dimensional version of the Mott random walk. The limiting process can be viewed heuristically as a one-dimensional diffusion with an absolutely continuous speed measure and a…

Probability · Mathematics 2024-04-19 David A. Croydon , Ryoki Fukushima , Stefan Junk

Strong anomalous diffusion phenomena are often observed in complex physical and biological systems, which are characterized by the nonlinear spectrum of exponents $q\nu(q)$ by measuring the absolute $q$-th moment $\langle |x|^q\rangle$.…

Statistical Mechanics · Physics 2020-03-20 Xudong Wang , Yao Chen , Weihua Deng

We propose two nonlinear random walk models which are suitable for the analysis of both chemotaxis and anomalous transport. We derive the balance equations for the population density for the case when the transition rate for a random walk…

Statistical Mechanics · Physics 2010-10-22 Sergei Fedotov

Fractional Brownian motion, a stochastic process with long-time correlations between its increments, is a prototypical model for anomalous diffusion. We analyze fractional Brownian motion in the presence of a reflecting wall by means of…

Statistical Mechanics · Physics 2018-02-21 Alexander H. O. Wada , Thomas Vojta

Anomalous diffusion or, more generally, anomalous transport, with nonlinear dependence of the mean-squared displacement on the measurement time, is ubiquitous in nature. It has been observed in processes ranging from microscopic movement of…

Motivated by studies on the recurrent properties of animal and human mobility, we introduce a path-dependent random walk model with long range memory for which not only the mean square displacement (MSD) can be obtained exactly in the…

Statistical Mechanics · Physics 2015-06-19 D. Boyer , J. C. R. Romo-Cruz

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

We study the stochastic dynamics of a particle with two distinct motility states. Each one is characterized by two parameters: one represents the average speed and the other represents the persistence quantifying the tendency to maintain…

Statistical Mechanics · Physics 2021-07-16 M. Reza Shaebani , Heiko Rieger

Many transport processes in nature exhibit anomalous diffusive properties with non-trivial scaling of the mean square displacement, e.g., diffusion of cells or of biomolecules inside the cell nucleus, where typically a crossover between…

Statistical Mechanics · Physics 2015-09-16 Andrea Cairoli , Adrian Baule

Dynamical systems having many coexisting attractors present interesting properties from both fundamental theoretical and modelling points of view. When such dynamics is under bounded random perturbations, the basins of attraction are no…

The passive and active motion of micron-sized tracer particles in crowded liquids and inside living biological cells is ubiquitously characterised by "viscoelastic" anomalous diffusion, in which the increments of the motion feature…

Statistical Mechanics · Physics 2020-05-05 Wei Wang , Flavio Seno , Igor M. Sokolov , Aleksei V. Chechkin , Ralf Metzler