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Related papers: Persistence effects in deterministic diffusion

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We analyze the influence of boundary conditions on numerical simulations of the diffusive properties of a two dimensional granular gas. We show in particular that periodic boundary conditions introduce unphysical correlations in time which…

Statistical Mechanics · Physics 2009-10-31 C. Henrique , G. Batrouni , D. Bideau

We analyze diffusion of particles on a two dimensional square lattice. Each lattice site contains an arbitrary number of particles. Interactions affect particles only in the same site, and are macroscopically represented by the excess…

Statistical Mechanics · Physics 2022-08-17 Matías A. Di Muro , Miguel Hoyuelos

In this minireview we present the main results regarding the transport properties of stochastic movement with relocations to known positions. To do so, we formulate the problem in a general manner to see several cases extensively studied…

Statistical Mechanics · Physics 2019-10-23 Axel Masó-Puigdellosas , Daniel Campos , Vicenç Méndez

Diffusion in a one dimensional random force field leads to interesting localisation effects, which we study using the equivalence with a directed walk model with traps. We show that although the average dispersion of positions $\bar{< x^2 >…

Disordered Systems and Neural Networks · Physics 2009-10-31 Albert Compte , Jean-Philippe Bouchaud

We consider a collection of weakly interacting diffusion processes moving in a two-scale locally periodic environment. We study the large deviations principle of the empirical distribution of the particles' positions in the combined limit…

Probability · Mathematics 2022-11-03 Zachary Bezemek , Konstantinos Spiliopoulos

We consider a continuous-space and continuous-time diffusion process under resetting with memory. A particle resets to a position chosen from its trajectory in the past according to a memory kernel. Depending on the form of the memory…

Statistical Mechanics · Physics 2017-11-29 Denis Boyer , Martin R. Evans , Satya N. Majumdar

The persistence exponent, which characterises the long-time decay of the survival probability of stochastic processes in the presence of an absorbing target, plays a key role in quantifying the dynamics of fluctuating systems. Determining…

Statistical Mechanics · Physics 2025-06-23 Julien Brémont , Léo Régnier , Olivier Bénichou , Raphaël Voituriez

We show that particle transport in a uniform, quantum multi-baker map, is generically ballistic in the long time limit, for any fixed value of Planck's constant. However, for fixed times, the semi-classical limit leads to diffusion. Random…

Quantum Physics · Physics 2009-11-07 Daniel K. Wojcik , J. R. Dorfman

We consider the drift and diffusion properties of periodically driven renewal processes. These processes are defined by a periodically time dependent waiting time distribution, which governs the interval between subsequent events. We show…

Statistical Mechanics · Physics 2009-11-11 Tobias Prager , Lutz Schimansky-Geier

We determine the rate of escape from a potential well, and the diffusion coefficient in a periodic potential, of a random walker that moves under the influence of the potential in between successive collisions with the heat bath. In the…

Statistical Mechanics · Physics 2016-09-05 Massimo Pica Ciamarra , Antonio Piscitelli

The unbounded diffusion observed for the standard mapping in a regime of high nonlinearity is suppressed by dissipation due to the violation of Liouville's theorem. The diffusion coefficient becomes important for the description of scaling…

Chaotic Dynamics · Physics 2024-11-20 Edson D. Leonel , Celia M. Kuwana , Diego F. M. Oliveira

We consider a discrete time simple symmetric random walk on Z^d, d>=1, where the path of the walk is perturbed by inserting deterministic jumps. We show that for any time n and any deterministic jumps that we insert, the expected number of…

Probability · Mathematics 2012-12-12 Lung-Chi Chen , Rongfeng Sun

Random walks are studied on disordered cellular networks in 2-and 3-dimensional spaces with arbitrary curvature. The coefficients of the evolution equation are calculated in term of the structural properties of the cellular system. The…

Disordered Systems and Neural Networks · Physics 2009-10-28 Tomaso Aste

Collective diffusion coefficient in a two-dimensional lattice gas on a nonhomogeneous substrate is investigated using variational approach. Particles reside at adsorption sites with different well depths potentials and jump randomly between…

Statistical Mechanics · Physics 2009-11-13 F Krzyzewski , Magdalena A. Zaluska-Kotur

The study of diffusion with preferential returns to places visited in the past has attracted an increased attention in recent years. In these highly non-Markov processes, a standard diffusive particle intermittently resets at a given rate…

Statistical Mechanics · Physics 2024-05-08 Denis Boyer , Satya N. Majumdar

Diffusion is a fundamental physical phenomenon with critical applications in fields such as metallurgy, cell biology, and population dynamics. While standard diffusion is well-understood, anomalous diffusion often requires complex non-local…

Statistical Mechanics · Physics 2026-01-16 Gabriel Barreiro , Vladimir Pérez-Veloz

A rapidly increasing number of systems is identified in which the stochastic motion of tracer particles follows the Brownian law $\langle\mathbf{r}^2(t) \rangle\simeq Dt$ yet the distribution of particle displacements is strongly…

Statistical Mechanics · Physics 2019-01-30 V. Sposini , A. V. Chechkin , R. Metzler

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

Data-dependent metrics are powerful tools for learning the underlying structure of high-dimensional data. This article develops and analyzes a data-dependent metric known as diffusion state distance (DSD), which compares points using a…

Machine Learning · Statistics 2020-03-10 Lenore Cowen , Kapil Devkota , Xiaozhe Hu , James M. Murphy , Kaiyi Wu

Probabilistic graphical models are a powerful concept for modeling high-dimensional distributions. Besides modeling distributions, probabilistic graphical models also provide an elegant framework for performing statistical inference;…

Artificial Intelligence · Computer Science 2022-09-13 Christian Knoll
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