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The fluctuation-dissipation theorem is a central result in statistical mechanics and is usually formulated for systems described by diffusion processes. In this paper, we propose a generalization for a wider class of stochastic processes,…

Statistical Mechanics · Physics 2018-09-20 Alberto Montefusco , Mark A. Peletier , Hans Christian Öttinger

We presented a general approach for obtaining the generalized transport equations with fractional derivatives by using the Liouville equation with fractional derivatives for a system of classical particles and Zubarev's nonequilibrium…

Statistical Mechanics · Physics 2020-05-26 P. P. Kostrobij , B. M. Markovych , M. V. Tokarchuk

The diffusive transport in two-dimensional incompressible turbulent fields is investigated with the aid of high-quality direct numerical simulations. Three classes of turbulence spectra that are able to capture both short and long-range…

Fluid Dynamics · Physics 2023-03-24 D. I. Palade , L. M. Pomârjanschi , M. Ghită

We study the transport properties of passive inertial particles in a $2-d$ incompressible flows. Here the particle dynamics is represented by the $4-d$ dissipative embedding map of $2-d$ area-preserving standard map which models the…

Chaotic Dynamics · Physics 2009-07-23 N. Nirmal Thyagu , Neelima Gupte

This paper addresses the limitations of standard uncertainty models, e.g., robust (norm-bounded) and stochastic (one fixed distribution, e.g., Gaussian), and proposes to model uncertainty via Optimal Transport (OT) ambiguity sets. These…

Optimization and Control · Mathematics 2023-09-08 Liviu Aolaritei , Nicolas Lanzetti , Hongruyu Chen , Florian Dörfler

Many important transport phenomena are described by simple mathematical models rooted in the diffusion equation. Geometrical constraints present in such phenomena often have influence of a universal sort and manifest themselves in scaling…

Statistical Mechanics · Physics 2007-05-23 Michael Slutsky

Advection-diffusion equations describe a large family of natural transport processes, e.g., fluid flow, heat transfer, and wind transport. They are also used for optical flow and perfusion imaging computations. We develop a machine learning…

Computer Vision and Pattern Recognition · Computer Science 2022-03-30 Peirong Liu , Yueh Lee , Stephen Aylward , Marc Niethammer

It is shown how Adler's trace dynamics can be applied to stochastic mechanics and other complex classical dynamical systems. Emergent non-commutivity due to the fractal nature of sample trajectories is closely related to the fact that the…

Quantum Physics · Physics 2007-05-23 Mark Davidson

This paper focuses on the analytical probabilistic modeling of vehicular traffic. It formulates a stochastic node model. It then formulates a network model by coupling the node model with the link model of Lu and Osorio (2018), which is a…

Computer Science and Game Theory · Computer Science 2022-09-07 Jing Lu , Carolina Osorio

We present the exact analytical equation of diffusion-mobility for two-dimensional (2D) Schr\"odinger type transport systems, from molecules to materials. The density of electronic states in such Schr\"odinger systems pertains to the 2D…

Statistical Mechanics · Physics 2019-09-27 K. Navamani

In the present study we examine non-Gaussian spreading of solutes subject to advection, dispersion and kinetic sorption (adsorption/desorption). We start considering the behavior of a single particle and apply a random walk to describe…

Probability · Mathematics 2011-01-14 Gerard Uffink , Amro Elfeki , Michel Dekking , Johannes Bruining , Cor Kraaikamp

The diffusion of molecules in complex intracellular environments can be strongly influenced by spatial heterogeneity and stochasticity. A key challenge when modelling such processes using stochastic random walk frameworks is that negative…

Biological Physics · Physics 2019-01-31 Elliot J. Carr , Matthew J. Simpson

Diffusion models are a class of generative models that serve to establish a stochastic transport map between an empirically observed, yet unknown, target distribution and a known prior. Despite their remarkable success in real-world…

Machine Learning · Computer Science 2025-03-13 Puheng Li , Zhong Li , Huishuai Zhang , Jiang Bian

This short note is motivated by a recently discovered connection between a drift-diffusion process in $n$-dimensional Euclidean space with a divergence-free drift sampled from a stationary and isotropic Gaussian ensemble of critical scaling…

Probability · Mathematics 2026-03-20 Sefika Kuzgun , Felix Otto , Christian Wagner

The study of passive scalar transport in a turbulent velocity field leads naturally to the notion of generalized flows which are families of probability distributions on the space of solutions to the associated ODEs, which no longer satisfy…

Chaotic Dynamics · Physics 2009-10-31 Weinan E , Eric Vanden Eijnden

A paradigm for isothermal, mechanical rectification of stochastic fluctuations is introduced in this paper. The central idea is to transform energy injected by random perturbations into rigid-body rotational kinetic energy. The prototype…

Probability · Mathematics 2007-10-18 Nawaf Bou-Rabee , Houman Owhadi

The diffusive transport distance, a novel pseudo-metric between probability measures on the real line, is introduced. It generalizes Martingale optimal transport, and forms a hierarchy with the Hellinger and the Wasserstein metrics. We…

Analysis of PDEs · Mathematics 2025-01-27 Daniel Matthes , Eva-Maria Rott , André Schlichting

We study an ensemble of random walkers carrying internal noisy phase oscillators which are synchronized among the walkers by local interactions. Due to individual mobility, the interaction partners of every walker change randomly, hereby…

Statistical Mechanics · Physics 2016-05-04 Robert Großmann , Fernando Peruani , Markus Bär

The sensitivity of anomalous transport in crowded media to the form of the inter-particle interactions is investigated through computer simulations. We extend the highly simplified Lorentz model towards realistic natural systems by modeling…

Soft Condensed Matter · Physics 2020-06-05 Charlotte F. Petersen , Thomas Franosch

We introduce the concept of Randomly Modulated Gaussian Processes as a unifying framework for modeling, analyzing and classifying anomalous diffusion models in heterogeneous media. This formulation incorporates correlations in the…

Biological Physics · Physics 2026-03-16 Yann Lanoiselée , Denis S. Grebenkov , Gianni Pagnini
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