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This paper presents existence and uniqueness results for a class of parabolic systems with non linear diffusion and nonlocal interaction. These systems can be viewed as regular perturbations of Wasserstein gradient flows. Here we extend…

Analysis of PDEs · Mathematics 2015-06-02 Maxime Laborde

The Poisson-Nernst-Planck system of equations used to model ionic transport is interpreted as a gradient flow for the Wasserstein distance and a free energy in the space of probability measures with finite second moment. A variational…

Analysis of PDEs · Mathematics 2015-09-08 David Kinderlehrer , Léonard Monsaingeon , Xiang Xu

A novel third order nonlinear evolution equation governing the dynamics of high frequency electrostatic drift waves has been derived in the framework of a plasma fluid model in an inhomogeneous magnetized plasma. The linear dispersion…

Plasma Physics · Physics 2023-06-09 Siba Prasad Acharya , M. S. Janaki

This paper is devoted to existence and uniqueness results for classes of nonlinear diffusion equations (or systems) which may be viewed as regular perturbations of Wasserstein gradient flows. First, in the case. where the drift is a…

Analysis of PDEs · Mathematics 2015-05-07 Guillaume Carlier , Maxime Laborde

In this paper we establish a rigorous gradient flow structure for one-dimensional Kimura equations with respect to some Wasserstein-Shahshahani optimal transport geometry. This is achieved by first conditioning the underlying stochastic…

Analysis of PDEs · Mathematics 2022-10-03 Jean-Baptiste Casteras , Léonard Monsaingeon

We prove optimal error bounds for a second order in time finite element approximation of curve shortening flow in possibly higher codimension. In addition, we introduce a second order in time method for curve diffusion. Both schemes are…

Numerical Analysis · Mathematics 2026-01-29 Klaus Deckelnick , Robert Nürnberg

A fully discrete Lagrangian scheme for numerical solution of the nonlinear fourth order DLSS equation in one space dimension is analyzed. The discretization is based on the equation's gradient flow structure in the $L^2$-Wasserstein metric.…

Numerical Analysis · Mathematics 2014-10-08 Daniel Matthes , Horst Osberger

This paper contributes to the exploration of a recently introduced computational paradigm known as second-order flows, which are characterized by novel dissipative hyperbolic partial differential equations extending accelerated gradient…

Numerical Analysis · Mathematics 2025-05-13 Haifan Chen , Guozhi Dong , José A. Iglesias , Wei Liu , Ziqing Xie

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

New criteria for energy stability of multi-step, multi-stage, and mixed schemes are introduced in the context of evolution equations that arise as gradient flow with respect to a metric. These criteria are used to exhibit second and third…

Numerical Analysis · Mathematics 2023-10-09 Saem Han , Selim Esedoglu , Krishna Garikipati

In this paper, we propose a novel numerical scheme to optimize the gradient flows for learning energy-based models (EBMs). From a perspective of physical simulation, we redefine the problem of approximating the gradient flow utilizing…

Computer Vision and Pattern Recognition · Computer Science 2023-05-01 Yang Wu , Pengxu Wei , Liang Lin

We study the numerical behaviour of a particle method for gradient flows involving linear and nonlinear diffusion. This method relies on the discretisation of the energy via non-overlapping balls centred at the particles. The resulting…

Analysis of PDEs · Mathematics 2016-12-07 J. A. Carrillo , Y. Huang , F. S. Patacchini , G. Wolansky

We propose a variational form of the BDF2 method as an alternative to the commonly used minimizing movement scheme for the time-discrete approximation of gradient flows in abstract metric spaces. Assuming uniform semi-convexity --- but no…

Analysis of PDEs · Mathematics 2017-12-25 Daniel Matthes , Simon Plazotta

Starting from a nonlinear 2D/1D fluid-structure interaction problem between a thin layer of a viscous fluid and a thin elastic structure, on the vanishing limit of the relative fluid thickness, we rigorously derive a sixth-order thin-film…

Analysis of PDEs · Mathematics 2022-07-27 Mario Bukal , Boris Muha

In this work, we show that a family of non-linear mean-field equations on discrete spaces can be viewed as a gradient flow of a natural free energy functional with respect to a certain metric structure we make explicit. We also prove that…

Probability · Mathematics 2016-10-26 Matthias Erbar , Max Fathi , Vaios Laschos , André Schlichting

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

A new formulation of boundary value problems in gradient elasticity is presented in this work. The main outcome is the construction of partial differential systems of second order, which are typically equivalent with the well known fourth…

Analysis of PDEs · Mathematics 2019-09-25 Antonios Charalambopoulos , Evanthia Douka , Stelios Mavratzas

Let K be an irreducible and reversible Markov kernel on a finite set X. We construct a metric W on the set of probability measures on X and show that with respect to this metric, the law of the continuous time Markov chain evolves as the…

Probability · Mathematics 2011-06-17 Jan Maas

The gradient-flow dynamics of an arbitrary geometric quantity is derived using a generalization of Darcy's Law. We consider flows in both Lagrangian and Eulerian formulations. The Lagrangian formulation includes a dissipative modification…

Adaptation and Self-Organizing Systems · Physics 2008-04-28 Darryl D. Holm , Vakhtang Putkaradze , Cesare Tronci

Sampling a probability distribution with an unknown normalization constant is a fundamental problem in computational science and engineering. This task may be cast as an optimization problem over all probability measures, and an initial…

Machine Learning · Statistics 2024-09-12 Yifan Chen , Daniel Zhengyu Huang , Jiaoyang Huang , Sebastian Reich , Andrew M. Stuart