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Dynamical random walk of classical particle in thermodynamically equilibrium fluctuating medium, - Gaussian random potential field, - is considered in the framework of explicit stochastic representation of deterministic interactions. We…

Statistical Mechanics · Physics 2013-02-05 Yu. E. Kuzovlev

We consider the inverse problem of determining different type of information about a diffusion process, described by ordinary or fractional diffusion equations stated on a bounded domain, like the density of the medium or the velocity field…

Analysis of PDEs · Mathematics 2019-07-05 Yavar Kian , Zhiyuan Li , Yikan Liu , Masahiro Yamamoto

We present an exact functional formalism to deal with linear Langevin equations with arbitrary memory kernels and driven by any noise structure characterized through its characteristic functional. No others hypothesis are assumed over the…

Other Condensed Matter · Physics 2009-11-10 A. A. Budini , M. O. Caceres

We study various temporal correlation functions of a tagged particle in one-dimensional systems of interacting point particles evolving with Hamiltonian dynamics. Initial conditions of the particles are chosen from the canonical thermal…

Statistical Mechanics · Physics 2015-06-25 Anjan Roy , Abhishek Dhar , Onuttom Narayan , Sanjib Sabhapandit

Starting from the kinetic equations for the fluctuations and correlations of a dilute gas of inelastic hard spheres or disks, a Boltzmann-Langevin equation for the one-particle distribution function of the homogeneous cooling state is…

Statistical Mechanics · Physics 2015-05-13 J. Javier Brey , P. Maynar , M. I. Garcia de Soria

Self-diffusion, $D$, in a system of particles that interact with a pseudo hard sphere potential is analyzed. Coupling with a solvent is represented by a Langevin thermostat, characterized by the damping time $t_d$. The hypotheses that…

Statistical Mechanics · Physics 2023-02-08 L. Marchioni , M. A. Di Muro , M. Hoyuelos

Given a discrete stochastic process, for example a chemical reaction system or a birth and death process, we often want to find a continuous stochastic approximation so that the techniques of stochastic differential equations may be brought…

Statistical Mechanics · Physics 2010-09-29 Edward W. J. Wallace

In this work we study the diffusion annealed Langevin dynamics, a score-based diffusion process recently introduced in the theory of generative models and which is an alternative to the classical overdamped Langevin diffusion. Our goal is…

Probability · Mathematics 2025-11-14 Patrick Cattiaux , Paula Cordero-Encinar , Arnaud Guillin

In this work, we present an effective discrete Edwards-Wilkinson equation aimed to describe the single-file diffusion process. The key physical properties of the system are captured defining an effective elasticity, which is proportional to…

Statistical Mechanics · Physics 2010-06-04 P. M. Centres , S. Bustingorry

The flow of granular material through a rough narrow pipe is described by the Langevin equation formalism. The stochastic force is caused by irregular interaction between the wall and the granular particles. In correspondence with…

Materials Science · Physics 2007-05-23 Tino Riethmueller , Lutz Schimansky-Geier , Dirk Rosenkranz , Thorsten Poeschel

We consider a system of two reaction-diffusion-advection equations describing the one dimensional directed motion of particles with superimposed diffusion and mutual alignment. For this system we show the existence of traveling wave…

Analysis of PDEs · Mathematics 2021-01-19 Heinrich Freistühler , Jan Fuhrmann

Recent advances in single particle tracking and supercomputing techniques demonstrate the emergence of normal or anomalous, viscoelastic diffusion in conjunction with non-Gaussian distributions in soft, biological, and active matter…

Statistical Mechanics · Physics 2018-01-23 Jakub Ślęzak , Ralf Metzler , Marcin Magdziarz

Discontinuous transitions into absorbing states require an effective mechanism that prevents the stabilization of low density states. They can be found in different systems, such as lattice models or stochastic differential equations (e.g.…

Statistical Mechanics · Physics 2015-08-12 Salete Pianegonda , Carlos E. Fiore

In this paper we study the fluctuations from the limiting behavior of small noise random perturbations of diffusions with multiple scales. The result is then applied to the exit problem for multiscale diffusions, deriving the limiting law…

Probability · Mathematics 2015-02-20 Sergio A. Almada Monter , Konatantinos Spiliopoulos

The fluctuation-dissipation theory is grounded on the Langevin condition expressing the local independence between the thermal force and the particle velocity history. Upon hydrodynamic grounds, it is reasonable to relax this condition in…

Statistical Mechanics · Physics 2024-12-30 Massimiliano Giona , Giuseppe Procopio , Chiara Pezzotti

With recently developed tools, we prove a homogenisation theorem for a random ODE with short and long-range dependent fractional noise. The effective dynamics are not necessarily diffusions, they are given by stochastic differential…

Probability · Mathematics 2020-06-23 Johann Gehringer , Xue-Mei Li

Diffusion in colloidal suspensions can be very slow due to the cage effect, which confines each particle within a short radius on one hand, and involves large-scale cooperative motions on the other. In search of insight into this…

Soft Condensed Matter · Physics 2017-03-08 Takeshi Ooshida , Susumu Goto , Takeshi Matsumoto , Michio Otsuki

Diffusion (score-based) generative models have been widely used for modeling various types of complex data, including images, audios, and point clouds. Recently, the deep connection between forward-backward stochastic differential equations…

Machine Learning · Computer Science 2022-06-22 Weitao Du , Tao Yang , He Zhang , Yuanqi Du

We study the stochastic motion of particles driven by long-range correlated fractional Gaussian noise in a superharmonic external potential of the form $U(x)\propto x^{2n}$ ($n\in\mathbb{N}$). When the noise is considered to be external,…

Statistical Mechanics · Physics 2021-06-17 Tobias Guggenberger , Aleksei Chechkin , Ralf Metzler

We present a concise, self-contained derivation of diffusion-based generative models. Starting from basic properties of Gaussian distributions (densities, quadratic expectations, re-parameterisation, products, and KL divergences), we…

Machine Learning · Computer Science 2025-11-18 Sepehr Maleki , Negar Pourmoazemi