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Mathematical models of motility are often based on random-walk descriptions of discrete individuals that can move according to certain rules. It is usually the case that large masses concentrated in small regions of space have a great…

Physics and Society · Physics 2022-11-23 Carles Falcó

Fractional Brownian motion (fBm) is a centered self-similar Gaussian process with stationary increments, which depends on a parameter $H \in (0, 1)$ called the Hurst index. The use of time-changed processes in modeling often requires the…

Probability · Mathematics 2014-08-21 Jebessa B. Mijena

Continuous-time random walks offer powerful coarse-grained descriptions of transport processes. We here microscopically derive such a model for a Brownian particle diffusing in a deep periodic potential. We determine both the waiting-time…

Statistical Mechanics · Physics 2019-08-21 Andreas Dechant , Farina Kindermann , Artur Widera , Eric Lutz

In this work animations of the random walk movement using a freeware Algodoo were done in order to support teaching the concepts of Brownian Motion. The random walk movement were simulate considering elastic collision between the particles…

A class of Gaussian processes generalizing the usual fractional Brownian motion for Hurst indices in (1/2,1) and multifractal Brownian motion introduced in Ralchenko and Shevchenko (Theory Probab Math Stat 80, 2010) and Boufoussi et al.…

Probability · Mathematics 2013-07-08 Jelena Ryvkina

We study the extremal properties of a stochastic process $x_t$ defined by a Langevin equation $\dot{x}_t=\sqrt{2 D_0 V(B_t)}\,\xi_t$, where $\xi_t$ is a Gaussian white noise with zero mean, $D_0$ is a constant scale factor, and $V(B_t)$ is…

Statistical Mechanics · Physics 2021-10-14 D. S. Grebenkov , V. Sposini , R. Metzler , G. Oshanin , F. Seno

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

Anomalous-diffusion, the departure of the spreading dynamics of diffusing particles from the traditional law of Brownian-motion, is a signature feature of a large number of complex soft-matter and biological systems. Anomalous-diffusion…

Stochastic Gradient Descent (SGD) is commonly modeled as a Langevin process, assuming that minibatch noise acts as Brownian motion. However, this approximation relies on a continuous-time limit and a sqrt(eta) noise scaling that does not…

Surface diffusion of small adsorbates is analyzed in terms of the so-called intermediate scattering function and dynamic structure factor, observables in experiments using the well-known quasielastic Helium atom scattering and Helium spin…

Statistical Mechanics · Physics 2018-09-26 S. Miret-Artés

The diversity of diffusive systems exhibiting long-range correlations characterized by a stochastically varying Hurst exponent calls for a generic multifractional model. We present a simple, analytically tractable model which fills the gap…

We show that the generalized diffusion coefficient of a subdiffusive intermittent map is a fractal function of control parameters. A modified continuous time random walk theory yields its coarse functional form and correctly describes a…

Chaotic Dynamics · Physics 2015-06-26 N. Korabel , A. V. Chechkin , R. Klages , I. M. Sokolov , V. Yu. Gonchar

A physical-mathematical approach to anomalous diffusion may be based on generalized diffusion equations (containing derivatives of fractional order in space or/and time) and related random walk models. The fundamental solution (for the…

Statistical Mechanics · Physics 2007-09-25 Rudolf Gorenflo , Francesco Mainardi , Daniele Moretti , Gianni Pagnini , Paolo Paradisi

Stochastic diffusion is the noisy and uncertain process through which dynamics like epidemics, or agents like animal species, disperse over a larger area. Understanding these processes is becoming increasingly important as we attempt to…

We show through intensive simulations that the paradigmatic features of anomalous diffusion are indeed the features of a (continuous-time) random walk driven by two different Markovian hopping-trap mechanisms. If $p \in (0,1/2)$ and $1-p$…

Statistical Mechanics · Physics 2022-05-25 Silvia Vitali , Paolo Paradisi , Gianni Pagnini

Anomalous diffusion processes pose a unique challenge in classification and characterization. Previously (Mangalam et al., 2023, Physical Review Research 5, 023144), we established a framework for understanding anomalous diffusion using…

Adaptation and Self-Organizing Systems · Physics 2024-01-23 Henrik Seckler , Ralf Metzler , Damian G. Kelty-Stephen , Madhur Mangalam

This thesis is dedicated to the study of stochastic processes; non-deterministic physical phenomena that can be well described by classical physics. The stochastic processes we are interested in are akin to Brownian Motion and can be…

Cosmology and Nongalactic Astrophysics · Physics 2023-06-06 Ashley Wilkins

Levy flights and fractional Brownian motion (fBm) have become exemplars of the heavy tailed jumps and long-ranged memory seen in space physics and elsewhere. Natural time series frequently combine both effects, and Linear Fractional Stable…

Mathematical Physics · Physics 2008-03-20 Nicholas W. Watkins , Daniel Credgington , Raul Sanchez , Sandra C. Chapman

It is shown that in systems with time-dependent and/or spatially nonuniform temperature $T(t,x)$, (i) most of the transport processes is weakly non-ergodic, and (ii) the diffusion (Brownian motion, BM) is anomalous. A few examples of simple…

Statistical Mechanics · Physics 2012-06-21 Andrzej Fuliński

This paper introduces a four-dimensional (4D) geometry-based stochastic model (GBSM) for polarized multiple-input multiple-output (MIMO) systems with moving scatterers. We propose a novel motion path model with high degrees of freedom based…

Systems and Control · Electrical Eng. & Systems 2023-06-08 Hamed Radpour , Laxmikant Minz , Seong-Ook Park , Duck-Yong Kim , Young-Chan Moon