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In micro-assembly applications, ensemble of chiplets immersed in a dielectric fluid are steered using dielectrophoretic forces induced by an array of electrode population. Generalizing the finite population deterministic models proposed in…

Dynamical Systems · Mathematics 2023-05-17 Iman Nodozi , Abhishek Halder , Ion Matei

In this paper, we start from a very natural system of cross-diffusion equations, which can be seen as a gradient flow for the Wasserstein distance of a certain functional. Unfortunately, the cross-diffusion system is not well-posed, as a…

Analysis of PDEs · Mathematics 2023-07-07 Romain Ducasse , Filippo Santambrogio , Havva Yoldaş

We consider a one-dimensional kinetic model of granular media in the case where the interaction potential is quadratic. Taking advan- tage of a simple first integral, we can use a reformulation (equivalent to the initial kinetic model for…

Analysis of PDEs · Mathematics 2015-06-19 Martial Agueh , Guillaume Carlier

We study the equation of one-dimensional quasistatic nonlinear viscoelasticity with Dirichlet boundary conditions, in the particular case that the underlying dissipation geometry (provided by the viscosity) is comparable to the Bhattacharya…

Analysis of PDEs · Mathematics 2026-05-12 Alexander Mielke , Billy Sumners

We perform a convergence analysis of a discrete-in-time minimization scheme approximating a finite dimensional singularly perturbed gradient flow. We allow for different scalings between the viscosity parameter $\varepsilon$ and the time…

Analysis of PDEs · Mathematics 2018-11-14 Giovanni Scilla , Francesco Solombrino

We study the existence and long-time asymptotics of weak solutions to a system of two nonlinear drift-diffusion equations that has a gradient flow structure in the Wasserstein distance. The two equations are coupled through a…

Analysis of PDEs · Mathematics 2021-12-14 Lisa Beck , Daniel Matthes , Martina Zizza

This article is concerned with the existence of nonnegative weak solutions to a particular fourth-order partial differential equation: it is a formal gradient flow with respect to a generalized Wasserstein transportation distance with…

Analysis of PDEs · Mathematics 2016-03-07 Jonathan Zinsl

We prove the convergence of a Wasserstein gradient flow of a free energy in inhomogeneous media. Both the energy and media can depend on the spatial variable in a fast oscillatory manner. In particular, we show that the gradient-flow…

Analysis of PDEs · Mathematics 2025-08-19 Yuan Gao , Nung Kwan Yip

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

Global existence and long-time behavior of solutions to a family of nonlinear fourth order evolution equations on $R^d$ are studied. These equations constitute gradient flows for the perturbed information functionals $F[u] = 1/(2\alpha)…

Analysis of PDEs · Mathematics 2009-01-06 Daniel Matthes , Robert J. McCann , Giuseppe Savar'e

These are lecture notes for various Summer and Winter schools that I have given. The notes describe the methodology called Variational Modelling, and focus on the application to the modelling of gradient-flow systems. I describe the…

Mathematical Physics · Physics 2014-02-11 Mark A. Peletier

We model the evolution of tokens within a deep stack of Transformer layers as a continuous-time flow on the unit sphere, governed by a mean-field interacting particle system, building on the framework introduced in (Geshkovski et al.,…

Machine Learning · Computer Science 2025-04-17 Giuseppe Bruno , Federico Pasqualotto , Andrea Agazzi

Extending previous work [arXiv:1408.0628] by the first author we present a variant of the Arratia flow, which consists of a collection of coalescing Brownian motions starting from every point of the unit interval. The important new feature…

Probability · Mathematics 2020-10-21 Vitalii Konarovskyi , Max von Renesse

A comprehensive methodology for establishing the existence of gradient flows for cross-diffusion systems with respect to suitable energies is proposed. The approach is based on the construction of piecewise-in-time constant approximations…

Analysis of PDEs · Mathematics 2026-04-03 Mathias Dus , Ansgar Jüngel

We propose a variational scheme for computing Wasserstein gradient flows. The scheme builds upon the Jordan--Kinderlehrer--Otto framework with the Benamou-Brenier's dynamic formulation of the quadratic Wasserstein metric and adds a…

Numerical Analysis · Mathematics 2020-07-15 Wuchen Li , Jianfeng Lu , Li Wang

We study a system of drift-diffusion PDEs for a potentially infinite number of incompressible phases, subject to a joint pointwise volume constraint. Our analysis is based on the interpretation as a collection of coupled Wasserstein…

Analysis of PDEs · Mathematics 2024-11-22 Clément Cancès , Daniel Matthes , Ismael Medina , Bernhard Schmitzer

An evolving surface finite element discretisation is analysed for the evolution of a closed two-dimensional surface governed by a system coupling a generalised forced mean curvature flow and a reaction--diffusion process on the surface,…

Numerical Analysis · Mathematics 2022-06-06 Charles M. Elliott , Harald Garcke , Balázs Kovács

In this work, we investigate a variational formulation for a time-fractional Fokker-Planck equation which arises in the study of complex physical systems involving anomalously slow diffusion. The model involves a fractional-order Caputo…

Numerical Analysis · Mathematics 2020-06-05 Manh Hong Duong , Bangti Jin

This paper presents a Wasserstein attraction approach for solving dynamic mass transport problems over networks. In the transport problem over networks, we start with a distribution over the set of nodes that needs to be "transported" to a…

Optimization and Control · Mathematics 2022-04-28 Ferran Arqué , César A. Uribe , Carlos Ocampo-Martinez

Many tasks in machine learning and signal processing can be solved by minimizing a convex function of a measure. This includes sparse spikes deconvolution or training a neural network with a single hidden layer. For these problems, we study…

Optimization and Control · Mathematics 2018-10-30 Lenaic Chizat , Francis Bach