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This paper is concerned with the stochastic thermodynamics of non-equilibrium Gaussian processes that can exhibit anomalous diffusion. In the systems considered, the noise correlation function is not necessarily related to friction. Thus,…

Statistical Mechanics · Physics 2022-12-20 S. Mohsen J. Khadem , Rainer Klages , Sabine H. L. Klapp

In this paper, a new fractional step method is proposed for simulating stiff and nonstiff chemically reacting flows. In stiff cases, a well-known spurious numerical phenomenon, i.e. the incorrect propagation speed of discontinuities, may be…

Computational Physics · Physics 2019-05-01 Jian-Hang Wang , Shucheng Pan , Xiangyu Y. Hu , Nikolaus A. Adams

Computational Fluid Dynamics (CFD) simulations are used for many air flow simulations including road vehicle aerodynamics. Numerical diffusion occurs when local flow direction is not aligned with the mesh lines and when there is a non-zero…

Fluid Dynamics · Physics 2025-12-29 Alok Warey , Taeyoung Han , Shailendra Kaushik

Fluctuating hydrodynamics provides a model for fluids at mesoscopic scales where thermal fluctuations can have a significant impact on the behavior of the system. Here we investigate a model for fluctuating hydrodynamics of a single…

Fluid Dynamics · Physics 2015-06-22 Anuj Chaudhri , John B. Bell , Alejandro L. Garcia , Aleksandar Donev

Nonequilibrium fluctuation-dissipation theorems (FDTs) are one of the most important advances in stochastic thermodynamics over the past two decades. Here we provide rigorous mathematical proofs of two types of nonequilibrium FDTs for…

Statistical Mechanics · Physics 2019-09-04 Xian Chen , Chen Jia

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

Reaction-diffusion (Turing) systems are fundamental to the formation of spatial patterns in nature and engineering. These systems are governed by a set of non-linear partial differential equations containing parameters that determine the…

Machine Learning · Computer Science 2022-11-28 Jordon Kho , Winston Koh , Jian Cheng Wong , Pao-Hsiung Chiu , Chin Chun Ooi

We study reaction-diffusion systems where diffusion is by jumps whose sizes are distributed exponentially. We first study the Fisher-like problem of propagation of a front into an unstable state, as typified by the A+B $\to$ 2A reaction. We…

Statistical Mechanics · Physics 2009-11-11 Elisheva Cohen , David A. Kessler

World models learn to predict future states of an environment, enabling planning and mental simulation. Current approaches default to Transformer-based predictors operating in learned latent spaces. This comes at a cost: O(N^2) computation…

Machine Learning · Computer Science 2026-03-24 Fabien Polly

Motivated by the modeling of the spatial structure of the velocity field of three-dimensional turbulent flows, and the phenomenology of cascade phenomena, a linear dynamics has been recently proposed able to generate high velocity gradients…

Reaction diffusion systems describe the behaviour of dynamic, interacting, particulate systems. Quantum stochastic processes generalise Brownian motion and Poisson processes, having operator valued It\^{o} calculus machinery. Here it is…

Mathematical Physics · Physics 2023-05-31 Chris D Greenman

Many biological activities are induced by cellular chemical reactions of diffusing reactants. The dynamics of such systems can be captured by stochastic reaction networks. A recent numerical study has shown that diffusion can significantly…

Biological Physics · Physics 2019-01-18 Tan Van Vu , Yoshihiko Hasegawa

We formulate low Mach number fluctuating hydrodynamic equations appropriate for modeling diffusive mixing in isothermal mixtures of fluids with different density and transport coefficients. These equations eliminate the fluctuations in…

Numerical Analysis · Mathematics 2016-01-20 A. Donev , A. J. Nonaka , Y. Sun , T. G. Fai , A. L. Garcia , J. B. Bell

We present approaches for the study of fluid-structure interactions subject to thermal fluctuations. A mixed mechanical description is utilized combining Eulerian and Lagrangian reference frames. We establish general conditions for…

Soft Condensed Matter · Physics 2023-02-28 Paul J. Atzberger

This is a pedagogical account on reaction-diffusion systems and their relationship with integrable quantum spin chains. Reaction-diffusion systems are paradigmatic examples of non-equilibrium systems. Their long-time behaviour is strongly…

Statistical Mechanics · Physics 2007-05-23 Malte Henkel

A fundamental principle of chaotic quantum dynamics is that local subsystems eventually approach a thermal equilibrium state. Large subsystems thermalize slower: their approach to equilibrium is limited by the hydrodynamic build-up of…

In the task of predicting spatio-temporal fields in environmental science using statistical methods, introducing statistical models inspired by the physics of the underlying phenomena that are numerically efficient is of growing interest.…

Methodology · Statistics 2024-07-23 Lucia Clarotto , Denis Allard , Thomas Romary , Nicolas Desassis

We present a numerical method to deal efficiently with large numbers of particles in incompressible fluids. The interactions between particles and fluid are taken into account by a physically motivated ansatz based on locally defined drag…

Condensed Matter · Physics 2016-08-31 W. Kalthoff , S. Schwarzer , G. H. Ristow , H. J. Herrmann

Fractional diffusion has become a fundamental tool for the modeling of multiscale and heterogeneous phenomena. However, due to its nonlocal nature, its accurate numerical approximation is delicate. We survey our research program on the…

Numerical Analysis · Mathematics 2015-08-19 Ricardo H. Nochetto , Enrique Otarola , Abner J. Salgado

A practical introduction to stochastic modelling of reaction-diffusion processes is presented. No prior knowledge of stochastic simulations is assumed. The methods are explained using illustrative examples. The article starts with the…

Subcellular Processes · Quantitative Biology 2007-11-19 Radek Erban , Jonathan Chapman , Philip Maini
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