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In this paper, we propose stochastic structure-preserving schemes to compute the effective diffusivity for particles moving in random flows. We first introduce the motion of particles using the Lagrangian formulation, which is modeled by…

Numerical Analysis · Mathematics 2020-08-24 Junlong Lyu , Zhongjian Wang , Jack Xin , Zhiwen Zhang

In this paper we study the problem of computing the effective diffusivity for a particle moving in chaotic and stochastic flows. In addition we numerically investigate the residual diffusion phenomenon in chaotic advection. The residual…

Numerical Analysis · Mathematics 2017-11-28 Zhongjian Wang , Jack Xin , Zhiwen Zhang

In this paper, we study the convergence analysis for a robust stochastic structure-preserving Lagrangian numerical scheme in computing effective diffusivity of time-dependent chaotic flows, which are modeled by stochastic differential…

Numerical Analysis · Mathematics 2021-06-03 Zhongjian Wang , Jack Xin , Zhiwen Zhang

In this paper, we study the problem of computing the effective diffusivity for particles moving in chaotic flows. Instead of solving a convection-diffusion type cell problem in the Eulerian formulation (arising from homogenization theory…

Numerical Analysis · Mathematics 2020-12-17 Zhongjian Wang , Jack Xin , Zhiwen Zhang

We demonstrate the non-ergodicity of a simple Markovian stochastic processes with space-dependent diffusion coefficient $D(x)$. For power-law forms $D(x) \simeq|x|^{\alpha}$, this process yield anomalous diffusion of the form $\ < x^2(t)\ >…

Statistical Mechanics · Physics 2015-06-15 Andrey G. Cherstvy , Aleksei V. Chechkin , Ralf Metzler

In this paper, we present a systematic framework to derive a Lagrangian scheme for porous medium type generalized diffusion equations by employing a discrete energetic variational approach. Such discrete energetic variational approaches are…

Numerical Analysis · Mathematics 2020-07-15 Chun Liu , Yiwei Wang

The anelastic and pseudo-incompressible equations are two well-known soundproof approximations of compressible flows useful for both theoretical and numerical analysis in meteorology, atmospheric science, and ocean studies. In this paper,…

Numerical Analysis · Mathematics 2019-02-05 Werner Bauer , François Gay-Balmaz

In this article we review classical and recent results in anomalous diffusion and provide mechanisms useful for the study of the fundamentals of certain processes, mainly in condensed matter physics, chemistry and biology. Emphasis will be…

Statistical Mechanics · Physics 2019-02-25 Fernando A. Oliveira , Rogelma M. S. Ferreira , Luciano C. Lapas , Mendeli H. Vainstein

Anomalous diffusion processes, in particular superdiffusive ones, are known to be efficient strategies for searching and navigation by animals and also in human mobility. One way to create such regimes are L\'evy flights, where the walkers…

Physics and Society · Physics 2017-02-22 Sarah de Nigris , Timoteo Carletti , Renaud Lambiotte

The stochastic motion in a nonhomogeneous medium with traps is studied and diffusion properties of that system are discussed. The particle is subjected to a stochastic stimulation obeying a general L\'evy stable statistics and experiences…

Statistical Mechanics · Physics 2015-06-11 Tomasz Srokowski

Evaluating the completion time of a random algorithm or a running stochastic process is a valuable tip not only from a purely theoretical, but also pragmatic point of view. In the formal sense, this kind of a task is specified in terms of…

Statistical Mechanics · Physics 2022-11-24 Przemyslaw Chelminiak

We show that the Turing patterns in reaction systems with subdiffusion can be replicated in an effective system with Markovian cross-diffusion. The effective system has the same Turing instability as the original system, and the same…

Pattern Formation and Solitons · Physics 2020-01-29 Joseph W. Baron , Tobias Galla

We propose a structure-preserving parametric finite element method (SP-PFEM) for discretizing the surface diffusion of a closed curve in two dimensions (2D) or surface in three dimensions (3D). Here the "structure-preserving" refers to…

Numerical Analysis · Mathematics 2021-12-02 Weizhu Bao , Quan Zhao

We study the strong approximation of stochastic differential equations with discontinuous drift coefficients and (possibly) degenerate diffusion coefficients. To account for the discontinuity of the drift coefficient we construct an…

Numerical Analysis · Mathematics 2019-04-25 Andreas Neuenkirch , Michaela Szölgyenyi , Lukasz Szpruch

We discuss the effective diffusion constant $D_{{\it eff}}$ for stochastic processes with spatially-dependent noise. Starting from a stochastic process given by a Langevin equation, different drift-diffusion equations can be derived…

Statistical Mechanics · Physics 2026-02-16 Stefano Giordano , Ralf Blossey

We present a stochastic model for amplifying, diffusive media like, for instance, random lasers. Starting from a simple random-walk model, we derive a stochastic partial differential equation for the energy field with contains a…

Statistical Mechanics · Physics 2013-06-11 Stefano Lepri

In recent years, diffusion models have become the leading approach for distribution learning. This paper focuses on structure-preserving diffusion models (SPDM), a specific subset of diffusion processes tailored for distributions with…

Machine Learning · Computer Science 2025-03-12 Haoye Lu , Spencer Szabados , Yaoliang Yu

The nature of diffusion is usually studied for particles or time-evolving systems. Similar in principle, such studies can be conducted by tracking how a given function of observable properties evolves over time-akin to the evolution of…

Statistical Mechanics · Physics 2026-03-10 M. Süzen

In this work we consider an extension of a recently proposed structure preserving numerical scheme for nonlinear Fokker-Planck-type equations to the case of nonconstant full diffusion matrices. While in existing works the schemes are…

Numerical Analysis · Mathematics 2021-04-20 N. Loy , M. Zanella

When particles/molecules diffuse in systems that contain obstacles, the steady-state regime (during which the mean-square displacement scales linearly with time, $\left< r^2 \right> \sim t$) is preceded by a transient regime. It is common…

Biological Physics · Physics 2021-08-12 Nicholas Ilow , Gary W. Slater
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