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We consider a class of particle systems which appear in various applications such as approximation theory, plasticity, potential theory and space-filling designs. The positions of the particles on the real line are described as a global…

Analysis of PDEs · Mathematics 2022-10-05 Patrick van Meurs , Ken'ichiro Tanaka

We solve explicitly a certain minimization problem for probability measures involving an interaction energy that is repulsive at short distances and attractive at large distances. We complement earlier works by showing that part of the…

Analysis of PDEs · Mathematics 2023-11-27 Rupert L. Frank , Ryan W. Matzke

Incompressible flows can be effective mixers by appropriately advecting a passive tracer to produce small filamentation length scales. In addition, diffusion is generally perceived as beneficial to mixing due to its ability to homogenise a…

Fluid Dynamics · Physics 2018-04-20 Christopher J. Miles , Charles R. Doering

We study the existence and the rate of equilibration of weak solutions to a two-component system of non-linear diffusion-aggregation equations, with small cross diffusion effects. The aggregation term is assumed to be purely attractive, and…

Analysis of PDEs · Mathematics 2024-06-17 Daniel Matthes , Christian Parsch

Over the past fifteen years, the theory of Wasserstein gradient flows of convex (or, more generally, semiconvex) energies has led to advances in several areas of partial differential equations and analysis. In this work, we extend the…

Analysis of PDEs · Mathematics 2017-05-04 Katy Craig

We consider a congested aggregation model that describes the evolution of a density through the competing effects of nonlocal Newtonian attraction and a hard height constraint. This provides a counterpoint to existing literature on…

Analysis of PDEs · Mathematics 2017-09-13 Katy Craig , Inwon Kim , Yao Yao

We study the emergence of gradient flows in Wasserstein distance as high friction limits of an abstract Euler flow generated by an energy functional. We develop a relative energy calculation that connects the Euler flow to the gradient flow…

Analysis of PDEs · Mathematics 2021-03-22 Corrado Lattanzio , Athanasios E. Tzavaras

Typically, aggregation-diffusion is modeled by parabolic equations that combine linear or nonlinear diffusion with a Fokker-Planck convection term. Under very general suitable assumptions, we prove that radial solutions of the evolution…

Analysis of PDEs · Mathematics 2021-12-15 Jose A. Carrillo , David Gómez-Castro , Juan Luis Vázquez

We study a singular-limit problem arising in the modelling of chemical reactions. At finite {\epsilon} > 0, the system is described by a Fokker-Planck convection-diffusion equation with a double-well convection potential. This potential is…

Analysis of PDEs · Mathematics 2014-09-16 Steffen Arnrich , Alexander Mielke , Mark A. Peletier , Giuseppe Savaré , Marco Veneroni

We study a two parameter family of energy minimization problems for interaction energies $\mathcal{E}_{\alpha,\beta}$ with attractive-repulsive potential $W_{\alpha,\beta}$. We develop a concavity principle, which allows us to provide a…

Optimization and Control · Mathematics 2024-04-04 Cameron Davies

We prove the tightness of radially-symmetric solutions to 2D aggregation-diffusion equations, where the pairwise attraction force is possibly degenerate at large distance. We first reduce the problem into the finiteness of a time integral…

Analysis of PDEs · Mathematics 2020-06-04 Ruiwen Shu

This paper studies the large time behavior of aggregation-diffusion equations. For one spatial dimension with certain assumptions on the interaction potential, the diffusion index $m$, and the initial data, we prove the convergence to the…

Analysis of PDEs · Mathematics 2021-08-23 Ruiwen Shu

The aggregation equation arises naturally in kinetic theory in the study of granular media, and its interpretation as a 2-Wasserstein gradient flow for the nonlocal interaction energy is well-known. Starting from the spatially homogeneous…

Analysis of PDEs · Mathematics 2024-12-24 A. Esposito , R. S. Gvalani , A. Schlichting , M. Schmidtchen

We show that degenerate nonlinear diffusion equations can be asymptotically obtained as a limit from a class of nonlocal partial differential equations. The nonlocal equations are obtained as gradient flows of interaction-like energies…

Analysis of PDEs · Mathematics 2023-10-12 José Antonio Carrillo , Antonio Esposito , Jeremy Sheung-Him Wu

We prove the existence of non-trivial global minimizers of a class of free energies related to aggregation equations with degenerate diffusion on $\Real^d$. Such equations arise in mathematical biology as models for organism group dynamics…

Analysis of PDEs · Mathematics 2010-09-28 Jacob Bedrossian

We study the quantitative convergence of drift-diffusion PDEs that arise as Wasserstein gradient flows of linearly convex functions over the space of probability measures on ${\mathbb R}^d$. In this setting, the objective is in general not…

Optimization and Control · Mathematics 2025-07-17 Lénaïc Chizat , Maria Colombo , Xavier Fernández-Real

We study the high-frequency limit of non-autonomous gradient flows in metric spaces of energy functionals comprising an explicitly time-dependent perturbation term which might oscillate in a rapid way, but fulfills a certain Lipschitz…

Analysis of PDEs · Mathematics 2016-10-25 Simon Plazotta , Jonathan Zinsl

Given a large ensemble of interacting particles, driven by nonlocal interactions and localized repulsion, the mean-field limit leads to a class of nonlocal, nonlinear partial differential equations known as aggregation-diffusion equations.…

Analysis of PDEs · Mathematics 2018-10-10 Jose A. Carrillo , Katy Craig , Yao Yao

We perform a fast-reaction limit for a linear reaction-diffusion system consisting of two diffusion equations coupled by a linear reaction. We understand the linear reaction-diffusion system as a gradient flow of the free energy in the…

Analysis of PDEs · Mathematics 2020-12-07 Artur Stephan

We introduce a novel particle-based algorithm for end-to-end training of latent diffusion models. We reformulate the training task as minimizing a free energy functional and obtain a gradient flow that does so. By approximating the latter…

Machine Learning · Statistics 2026-03-31 Tim Y. J. Wang , Juan Kuntz , O. Deniz Akyildiz
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