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Stochastic differential equations (SDEs) describe dynamical systems where deterministic flows, governed by a drift function, are superimposed with random fluctuations, dictated by a diffusion function. The accurate estimation (or discovery)…

Machine Learning · Computer Science 2025-10-22 Patrick Seifner , Kostadin Cvejoski , David Berghaus , Cesar Ojeda , Ramses J. Sanchez

In this review, we scrutinize historical and modern results on the linear response of dynamical systems to external perturbations with a particular emphasis on the celebrated relationship between fluctuations and dissipation expressed by…

The question of the "physical meaning" and "origin" of the Bose-Einstein (BE) factor in the fluctuation-dissipation theorem (FDT) is often raised and this term is sometimes interpreted as originating from a real harmonic oscillator…

Statistical Mechanics · Physics 2009-06-03 Vincenzo Branchina , Marco Di Liberto , Ivano Lodato

We present a finite element approach for diffusion problems with thermal fluctuations based on a fluctuating hydrodynamics model. The governing transport equations are stochastic partial differential equations with a fluctuating forcing…

Numerical Analysis · Mathematics 2024-03-21 P. Martínez-Lera , M. De Corato

Theory and simulation of Brownian colloids suspended in an implicit solvent, with the hydrodynamics of the fluid accounted for by effective interactions between the colloids, are shown to yield a marked and hitherto unobserved discrepancy…

Soft Condensed Matter · Physics 2020-03-18 Duraivelan Palanisamy , Wouter K. den Otter

Stochastic averaging for a class of backward stochastic differential equations driven by both standard and fractional Brownian motions (SFrBSDEs in short), is investigated. An averaged SFrBSDEs for the original SFrBSDEs is proposed, and…

Probability · Mathematics 2021-06-04 Ibrahima Faye , Sadibou Aidara , Yaya Sagna

In a stochastic process, where noise is always present, the fluctuation-dissipation theorem (FDT) becomes one of the most important tools in statistical mechanics and, consequently, it appears everywhere. Its major utility is to provide a…

Statistical Mechanics · Physics 2021-03-08 Márcio S. Gomes-Filho , Fernando A. Oliveira

The classical theory of Brownian motion rests on fundamental laws of statistical mechanics, such as the equipartition theorem and the fluctuation-dissipation theorem, which are not applicable in non-isothermal situations. We derive the…

Statistical Mechanics · Physics 2014-06-10 Gianmaria Falasco , Manuel Victor Gnann , Klaus Kroy

We study a gas of hard rods on a ring, driven by an external thermostat, with either elastic or inelastic collisions, which exhibits sub-diffusive behavior $<x^2 > \sim t^{1/2}$. We show the validity of the usual Fluctuation-Dissipation…

Statistical Mechanics · Physics 2008-10-10 D. Villamaina , A. Puglisi , A. Vulpiani

Stochastic models with fractional Brownian motion as source of randomness have become popular since the early 2000s. Fractional Brownian motion (fBm) is a Gaussian process, whose covariance depends on the so-called Hurst parameter $H\in…

Probability · Mathematics 2026-01-22 Anna P. Kwossek , Andreas Neuenkirch , David J. Prömel

We introduce thermal fluctuations in the lattice Boltzmann method for non-ideal fluids. A fluctuation-dissipation theorem is derived within the Langevin framework and applied to a specific lattice Boltzmann model that approximates the…

Soft Condensed Matter · Physics 2010-12-01 M. Gross , R. Adhikari , M. E. Cates , F. Varnik

We analytically study a one dimensional compaction model in the glassy regime. Both correlation and response functions are calculated exactly in the evolving dense and low tapping strength limit, where the density relaxes in a $1/\ln t$…

Statistical Mechanics · Physics 2009-11-10 Martin Depken , Robin Stinchcombe

This paper investigates the probability distribution of solutions to McKean--Vlasov stochastic differential equations driven by fractional Brownian motion with Hurst parameter H>1/2. Our main contribution is the derivation of the associated…

Probability · Mathematics 2026-01-12 Saloua Labed , Nacira Agram , Bernt Oksendal

In this work, we introduce a time memory formalism in poroelasticity model that couples the pressure and displacement. We assume this multiphysics process occurs in multicontinuum media. The mathematical model contains a coupled system of…

Numerical Analysis · Mathematics 2022-01-20 Aleksei Tyrylgin , Maria Vasilyeva , Anatoly Alikhanov , Dongwoo Sheen

In complex physical systems, conventional differential equations often fall short in capturing non-local and memory effects, as they are limited to local dynamics and integer-order interactions. This study introduces a stepwise data-driven…

Computational Physics · Physics 2025-05-30 Xiangnan Yu , Hao Xu , Zhiping Mao , HongGuang Sun , Yong Zhang , Dongxiao Zhang , Yuntian Chen

The Fractional Langevin Equation (FLE) describes a non-Markovian Generalized Brownian Motion with long time persistence (superdiffusion), or anti-persistence (subdiffusion) of both velocity-velocity correlations, and position increments. It…

Statistical Mechanics · Physics 2011-07-11 P. Siegle , I. Goychuk , P. Hanggi

We show that for stochastic dynamical systems out of equilibrium the violation of the fluctuation-dissipation equality is bounded by a function of the entropy production. The result applies to a much wider situation than `near equilibrium',…

Statistical Mechanics · Physics 2009-01-23 Leticia F. Cugliandolo , David S. Dean , Jorge Kurchan

We investigated the validity of fluctuation-dissipation relations in the nonequilibrium stationary state of fluidized granular media under gravity by two independent approaches, based on theory and numerical simulations. A phenomenological…

Statistical Mechanics · Physics 2012-07-03 Jun'ichi Wakou , Masaharu Isobe

In this paper, we study a class of dissipative stochastic differential equations driven by nonlinear multiplicative fractional Brownian noise with Hurst index $H \in \left(\frac{1}{3},\frac{1}{2})\cup(\frac{1}{2}, 1\right) $. We establish…

Probability · Mathematics 2025-10-02 Qiyong Cao , Hongjun Gao , Wei Wei

Diffusion models have recently emerged as powerful stochastic frameworks for high-dimensional inference and generation. However, existing applications to partial differential equations (PDEs) predominantly rely on physics-informed training…

Numerical Analysis · Mathematics 2026-04-03 Yi Bing , Liu Jia , Fu Jinyang , Peng Xiang