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We show how Langevin diffusions can be interpreted in the context of stochastic Hamiltonian systems with structure-preserving noise and dissipation on reductive Lie groups. Reductive Lie groups provide the setting in which the Lie group…

Probability · Mathematics 2025-09-15 Erwin Luesink , Oliver D. Street

We are concerned with multidimensional nonlinear stochastic transport equation driven by Brownian motions. For irregular fluxes, by using stochastic BGK approximations and commutator estimates, we gain the existence and uniqueness of…

Probability · Mathematics 2018-01-16 Jinlong Wei , Rongrong Tian , Guangying Lv

We define an operator which extends classical differentiation from smooth deterministic functions to certain stochastic processes. Based on this operator, we define a procedure which associates a stochastic analog to standard differential…

Probability · Mathematics 2016-08-16 Jacky Cresson , Sébastien Darses

Including the effect of thermal fluctuations in traditional computational fluid dynamics requires developing numerical techniques for solving the stochastic partial differential equations of fluctuating hydrodynamics. These Langevin…

Computational Physics · Physics 2015-06-12 S. Delong , B. E. Griffith , E. Vanden-Eijnden , A. Donev

Energy transport equations are derived directly from full molecular dynamics models as coarse-grained description. With the local energy chosen as the coarse-grained variables, we apply the Mori-Zwanzig formalism to derive a reduced model,…

Statistical Mechanics · Physics 2017-09-19 Weiqi Chu , Xiantao Li

We analyze quantal Brownian motion in $d$ dimensions using the unified model for diffusion localization and dissipation, and Feynman-Vernon formalism. At high temperatures the propagator possess a Markovian property and we can write down an…

Condensed Matter · Physics 2009-10-31 Doron Cohen

Stochastic approximation is a powerful class of algorithms with celebrated success. However, a large body of previous analysis focuses on stochastic approximations driven by contractive operators, which is not applicable in some important…

Machine Learning · Computer Science 2025-11-21 Ethan Blaser , Shangtong Zhang

The Generalized Elastic Model is a linear stochastic model which accounts for the behaviour of many physical systems in nature, ranging from polymeric chains to single-file systems. If an external perturbation is exerted \emph{only} on a…

Statistical Mechanics · Physics 2013-05-14 Alessandro Taloni , Aleksei Chechkin , Joseph Klafter

We present an insightful ``derivation'' of the Langevin equation and the fluctuation dissipation theorem in the specific context of a heavier particle moving through an ideal gas of much lighter particles. The Newton's Law of motion…

Statistical Mechanics · Physics 2007-05-23 Rangan Lahiri , Arvind , Anirban Sain

The Langevin equation (LE) for the one-dimensional relativistic Brownian motion is derived from a microscopic collision model. The model assumes that a heavy point-like Brownian particle interacts with the lighter heat bath particles via…

Statistical Mechanics · Physics 2008-11-26 Jörn Dunkel , Peter Hänggi

A considerable number of systems have recently been reported in which Brownian yet non-Gaussian dynamics was observed. These are processes characterised by a linear growth in time of the mean squared displacement, yet the probability…

Statistical Mechanics · Physics 2018-11-26 V. Sposini , A. V. Chechkin , F. Seno , G. Pagnini , R. Metzler

We introduce a general formulation of the fluctuation-dissipation relations (FDR) holding also in far-from-equilibrium stochastic dynamics. A great advantage of this version of the FDR is that it does not require the explicit knowledge of…

Statistical Mechanics · Physics 2021-09-15 Marco Baldovin , Lorenzo Caprini , Angelo Vulpiani

We develop two-dimensional Brownian dynamics simulations to examine the motion of disks under thermal fluctuations and Hookean forces. Our simulations are designed to be experimental-like, since the experimental conditions define the…

Soft Condensed Matter · Physics 2017-05-26 Manuel Pancorbo , Miguel A. Rubio , P. Domínguez-García

Despite the success of fractional Brownian motion (fBm) in modeling systems that exhibit anomalous diffusion due to temporal correlations, recent experimental and theoretical studies highlight the necessity for a more comprehensive approach…

Statistical Mechanics · Physics 2024-07-02 Adrian Pacheco-Pozo , Diego Krapf

We use an effective Markovian description to study the long-time behaviour of a nonlinear second order Langevin equation with Gaussian noise. When dissipation is neglected, the energy of the system grows as with time a power-law with an…

Chaotic Dynamics · Physics 2014-12-19 Kirone Mallick

We investigate the impact of intermittent energy injections on a Brownian particle, modeled as stochastic renewals of its kinetic energy to a fixed value. Between renewals, the particle follows standard underdamped Langevin dynamics. For…

Statistical Mechanics · Physics 2025-06-11 Ion Santra , Kristian Stølevik Olsen

We consider the hydrodynamic limit in the macroscopic regime of the coupled system of stochastic differential equations, $ d\lambda_t^i=\frac{1}{\sqrt{N}} dW_t^i - V'(\lambda_t^i) dt+ \frac{\beta}{2N} \sum_{j\not=i}…

Probability · Mathematics 2019-03-05 Jeremie Unterberger

We consider a system of multiscale stochastic differential equations whose slow component is drivenby a fractional Brownian motion with Hurst parameter H greater than 1/2. Under ergodic assumptions ensuring the applicability of the…

Probability · Mathematics 2025-12-10 Xue-Mei Li , Colin Piernot , Szymon Sobczak , Kexing Ying

We derive various exact results for Markovian systems that spontaneously relax to a non-equilibrium steady-state by using joint probability distributions symmetries of different entropy production decompositions. The analytical approach is…

Statistical Mechanics · Physics 2012-02-10 Reinaldo García-García , Vivien Lecomte , A. B. Kolton , D. Domínguez

We study noise-averaged observables for a system of exchange-coupled quantum spins (qubits), each subject to a stochastic drive, by establishing mappings onto stochastic models in the strong-noise limit. Averaging over noise yields…

Statistical Mechanics · Physics 2020-03-16 Daniel A. Rowlands , Austen Lamacraft
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