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In solving diffusion problems, it is common to consider the finite difference equation to be an approximation to the differential equation. Nevertheless, history shows that the finite difference equation is primitive and that the…

History and Overview · Mathematics 2010-02-09 T. N. Narasimhan

This essay advocates the view that any problem that has a meaningful empirical content, can be formulated in constructive, more definitely, finite terms. We consider combinatorial models of dynamical systems and approaches to statistical…

Quantum Physics · Physics 2015-07-21 Vladimir V. Kornyak

In this work, we consider a diffusive two-species d-dimensional model and study it in great details. Two types of particles, with hard-core, diffuse symmetrically and cross each other. For arbitrary dimensions, we obtain the exact density,…

Statistical Mechanics · Physics 2009-11-07 M. Mobilia , P. -A. Bares

In this note, we investigate a doubly nonlinear diffusion equation in the slow diffusion regime. We prove stability of the pressure of solutions that are close to traveling wave solutions in a homogeneous Lipschitz sense. We derive…

Analysis of PDEs · Mathematics 2026-02-25 Christian Seis , Dominik Winkler

Liquid mixtures of many interacting components often exhibit numerous coexisting types of droplets. An exciting example is the cytosol of biological cells, where diverse droplets, called condensates, are essential for cellular function.…

Soft Condensed Matter · Physics 2025-05-28 Yicheng Qiang , Chengjie Luo , David Zwicker

In this paper, we introduce two deterministic models aimed at capturing the dynamics of congested Internet connections. The first model is a continuous-time model that combines a system of differential equations with a sudden change in one…

Networking and Internet Architecture · Computer Science 2007-05-23 Ian Frommer , Eric Harder , Brian Hunt , Ryan Lance , Edward Ott , James Yorke

For the time-dependent Ginzburg-Landau equation on the real line, we construct solutions which converge, as $x \to \pm\infty$, to periodic stationary states with different wave-numbers $\eta_\pm$. These solutions are stable with respect to…

patt-sol · Physics 2009-10-31 Thierry Gallay , Alexander Mielke

Despite the growing interest in diffusion models, gaining a deep understanding of the model class remains an elusive endeavour, particularly for the uninitiated in non-equilibrium statistical physics. Thanks to the rapid rate of progress in…

Machine Learning · Computer Science 2025-05-23 Fabio De Sousa Ribeiro , Ben Glocker

This paper is devoted to study the wave propagation and its stability for a class of two-component discrete diffusive systems. We first establish the existence of positive monotone monostable traveling wave fronts. Then, applying the…

Dynamical Systems · Mathematics 2020-12-02 Zhixian Yu , Yuji Wan , Cheng-Hsiung Hsu

Diffusion models have become increasingly popular for generative modeling due to their ability to generate high-quality samples. This has unlocked exciting new possibilities for solving inverse problems, especially in image restoration and…

Diffusion models for continuous data gained widespread adoption owing to their high quality generation and control mechanisms. However, controllable diffusion on discrete data faces challenges given that continuous guidance methods do not…

An exactly solvable model for the rewiring dynamics of weighted, directed networks is introduced. Simulations indicate that the model exhibits two types of condensation: (i) a phase in which, for each node, a finite fraction of its total…

Statistical Mechanics · Physics 2009-11-11 A. G. Angel , T. Hanney , M. R. Evans

In this paper, we propose and analyze an abstract stabilized mixed finite element framework that can be applied to nonlinear incompressible elasticity problems. In the abstract stabilized framework, we prove that any mixed finite element…

Numerical Analysis · Mathematics 2020-07-30 Qingguo Hong , Chunmei Liu , Jinchao Xu

Diffusion models, a family of generative models based on deep learning, have become increasingly prominent in cutting-edge machine learning research. With a distinguished performance in generating samples that resemble the observed data,…

Machine Learning · Computer Science 2023-05-02 Lequan Lin , Zhengkun Li , Ruikun Li , Xuliang Li , Junbin Gao

Mathematical models of biological populations commonly use discrete structure classes to capture trait variation among individuals (e.g. age, size, phenotype, intracellular state). Upscaling these discrete models into continuum descriptions…

Populations and Evolution · Quantitative Biology 2026-03-18 Eleonora Agostinelli , Keith L. Chambers , Helen M. Byrne , Mohit P. Dalwadi

Over the last decade, an enormous interest and activity in complex networks have been witnessed within the physics community. On the other hand, diffusion and its theory, have equipped the toolbox of the physicist for decades. In this…

Statistical Mechanics · Physics 2010-05-04 Ingve Simonsen

A general system of several ordinary differential equations coupled with a reaction-diffusion equation in a bounded domain with zero-flux boundary condition is studied in the context of pattern formation. These initial-boundary value…

Analysis of PDEs · Mathematics 2021-10-29 Szymon Cygan , Anna Marciniak-Czochra , Grzegorz Karch , Kanako Suzuki

Two frameworks that have been used to characterize reflected diffusions include stochastic differential equations with reflection and the so-called submartingale problem. We introduce a general formulation of the submartingale problem for…

Probability · Mathematics 2014-12-03 Weining Kang , Kavita Ramanan

Selected theoretical developments in modeling of deposition of submicrometer size (submicron) particles on solid surfaces, with and without surface diffusion, of interest in colloid, polymer, and certain biological systems, are surveyed. We…

Materials Science · Physics 2008-10-16 Vladimir Privman

In this work, we aimed to replicate and extend the results presented in the DiffFluid paper[1]. The DiffFluid model showed that diffusion models combined with Transformers are capable of predicting fluid dynamics. It uses a denoising…

Fluid Dynamics · Physics 2025-07-14 Yannick Gachnang , Vismay Churiwala