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Overdamped Langevin dynamics are reversible stochastic differential equations which are commonly used to sample probability measures in high-dimensional spaces, such as the ones appearing in computational statistical physics and Bayesian…

Numerical Analysis · Mathematics 2025-02-10 Tony Lelièvre , Grigorios A. Pavliotis , Geneviève Robin , Régis Santet , Gabriel Stoltz

We study the effect of advection and small diffusion on passive tracers. The advecting velocity field is assumed to have mean zero and to possess time-periodic stream lines. Using a canonical transform to action-angle variables followed by…

Fluid Dynamics · Physics 2009-11-13 Tobias Schaefer , Andrew C. Poje , Jesenko Vukadinovic

We make a comparative analysis of some recent one-dimensional Langevin models of the acceleration of a Lagrangian fluid particle in developed turbulent flow. The class of models characterized by random intensities of noises (RIN models)…

Statistical Mechanics · Physics 2007-05-23 A. K. Aringazin , M. I. Mazhitov

We investigate the ensemble and time averaged mean squared displacements for particle diffusion in a simple model for disordered media by assuming that the local diffusivity is both fluctuating in time and has a deterministic average growth…

Statistical Mechanics · Physics 2016-10-05 A. G. Cherstvy , R. Metzler

The diffusion behavior of particles moving in complex heterogeneous environment is a very topical issue. We characterize particle's trajectory via an underdamped Langevin system driven by a Gaussian white noise with a time dependent…

Statistical Mechanics · Physics 2022-01-05 Yao Chen , Xudong Wang

We study the Langevin dynamics of diffusive particles with regular pairwise interactions under mean-field scaling. By approximating empirical distributions with conditional distributions, we establish coercive and contractive properties for…

Probability · Mathematics 2026-05-28 Songbo Wang

In this paper, we consider the adaptive Eulerian--Lagrangian method (ELM) for linear convection-diffusion problems. Unlike the classical a posteriori error estimations, we estimate the temporal error along the characteristics and derive a…

Numerical Analysis · Mathematics 2012-09-07 Xiaozhe Hu , Young-Ju Lee , Jinchao Xu , Chensong Zhang

We study the contribution of advection by thermal velocity fluctuations to the effective diffusion coefficient in a mixture of two identical fluids. The steady-state diffusive flux in a finite system subject to a concentration gradient is…

Mesoscale and Nanoscale Physics · Physics 2015-05-27 A. Donev , A. de la Fuente , J. B. Bell , A. L. Garcia

We provide an asymptotic analysis of linear transport problems in the diffusion limit under minimal regularity assumptions on the domain, the coefficients, and the data. The weak form of the limit equation is derived and the convergence of…

Analysis of PDEs · Mathematics 2014-07-31 Herbert Egger , Matthias Schlottbom

The advection-diffusion equation can be approximated by a one-dimensional diffusion equation in Lagrangian coordinates along the directions of compression of fluid elements (the stable manifold). This result holds in any number of…

Chaotic Dynamics · Physics 2009-11-07 Jean-Luc Thiffeault

High-frequency wave propagation is often modelled by nonlinear Friedrichs systems where both the differential equation and the initial data contain the inverse of a small parameter $\varepsilon$, which causes oscillations with wavelengths…

Analysis of PDEs · Mathematics 2024-02-21 Julian Baumstark , Tobias Jahnke

The classical (overdamped) Langevin dynamics provide a natural algorithm for sampling from its invariant measure, which uniquely minimizes an energy functional over the space of probability measures, and which concentrates around the…

Probability · Mathematics 2023-09-26 Giovanni Conforti , Daniel Lacker , Soumik Pal

The diffusive dynamics of a particle in a medium with space-dependent friction coefficient is studied within the framework of the inertial Langevin equation. In this description, the ambiguous interpretation of the stochastic integral,…

Statistical Mechanics · Physics 2015-06-16 Oded Farago , Niels Grønbech-Jensen

We consider mixing problems in the form of transient convection--diffusion equations with a velocity vector field with multiscale character and rough data. We assume that the velocity field has two scales, a coarse scale with slow spatial…

Numerical Analysis · Mathematics 2014-05-05 Erik Burman

We study a diffusion approximation for a model of stochastic motion of a particle in one spatial dimension. The velocity of the particle is constant but the direction of the motion undergoes random changes with a Poisson clock. Moreover,…

Functional Analysis · Mathematics 2022-04-21 Adam Bobrowski , Tomasz Komorowski

We introduce a scheme for deriving an optimally-parametrised Langevin dynamics of few collective variables from data generated in molecular dynamics simulations. The drift and the position-dependent diffusion profiles governing the Langevin…

Statistical Mechanics · Physics 2008-08-22 Cristian Micheletti , Giovanni Bussi , Alessandro Laio

Langevin Dynamics has been extensively employed in global non-convex optimization due to the concentration of its stationary distribution around the global minimum of the potential function at low temperatures. In this paper, we propose to…

Optimization and Control · Mathematics 2023-05-22 Ryo Fujino

Biological and synthetic microswimmers display a wide range of swimming trajectories depending on driving forces and torques. In this paper we consider a simple overdamped model of self-propelled particles with a constant self-propulsion…

Statistical Mechanics · Physics 2021-05-26 Kristian Stølevik Olsen

We study the contribution of advection by thermal velocity fluctuations to the effective diffusion coefficient in a mixture of two indistinguishable fluids. The enhancement of the diffusive transport depends on the system size L and grows…

Mesoscale and Nanoscale Physics · Physics 2015-05-27 A. Donev , A. de la Fuente , J. B. Bell , A. L. Garcia

The stochastic gradient Langevin Dynamics is one of the most fundamental algorithms to solve sampling problems and non-convex optimization appearing in several machine learning applications. Especially, its variance reduced versions have…

Machine Learning · Computer Science 2022-11-22 Yuri Kinoshita , Taiji Suzuki
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