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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

We present a method to efficiently compute Wasserstein gradient flows. Our approach is based on a generalization of the back-and-forth method (BFM) introduced by Jacobs and L\'eger to solve optimal transport problems. We evolve the gradient…

Numerical Analysis · Mathematics 2020-11-17 Matt Jacobs , Wonjun Lee , Flavien Léger

We study the connection between a system of many independent Brownian particles on one hand and the deterministic diffusion equation on the other. For a fixed time step $h>0$, a large-deviations rate functional $J_h$ characterizes the…

Probability · Mathematics 2015-05-18 Stefan Adams , Nicolas Dirr , Mark Peletier , Johannes Zimmer

A nonlinear parabolic equation of sixth order is analyzed. The equation arises as a reduction of a model from quantum statistical mechanics, and also as the gradient flow of a second-order information functional with respect to the…

Analysis of PDEs · Mathematics 2021-08-25 Daniel Matthes , Eva-Maria Rott

We perform numerical analysis of a nonlinear gradient flow, which can be regarded as a parabolic minimal surface problem or a regularised total variation flow, using the gradient discretisation method (GDM). GDM is a unified convergence…

Numerical Analysis · Mathematics 2026-04-21 Jerome Droniou , Kim-Ngan Le , Huateng Zhu

This paper contains two contributions in the study of optimal transport on metric graphs. Firstly, we prove a Benamou-Brenier formula for the Wasserstein distance, which establishes the equivalence of static and dynamical optimal transport.…

Analysis of PDEs · Mathematics 2022-05-02 Matthias Erbar , Dominik Forkert , Jan Maas , Delio Mugnolo

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

The theory of Wasserstein gradient flows in the space of probability measures has made an enormous progress over the last twenty years. It constitutes a unified and powerful framework in the study of dissipative partial differential…

Analysis of PDEs · Mathematics 2022-01-17 Daniel Adams , Manh Hong Duong , Goncalo dos Reis

Numerous infinite dimensional dynamical systems arising in different fields have been shown to exhibit a gradient flow structure in the Wasserstein space. We construct Two Point Flux Approximation Finite Volume schemes discretizing such…

Numerical Analysis · Mathematics 2020-06-29 Andrea Natale , Gabriele Todeschi

We present a new approach to parallelization of the first-order backward difference discretization (BDF1) of the time derivative in partial differential equations, such as the nonlinear heat and viscous Burgers equations. The time…

Numerical Analysis · Mathematics 2024-06-04 Nail K. Yamaleev , Subhash Paudel

In this paper we provide a variational characterisation for a class of non-linear evolution equations with constant non-negative Dirichlet boundary conditions on a bounded domain as gradient flows in the space of non-negative measures. The…

Analysis of PDEs · Mathematics 2025-02-28 Matthias Erbar , Giulia Meglioli

It is well-known that many diffusion equations can be recast as Wasserstein gradient flows. Moreover, in recent years, by modifying the Wasserstein distance appropriately, this technique has been transferred to further evolution equations…

Probability · Mathematics 2020-10-15 Kaveh Bashiri , Anton Bovier

We propose a novel class of temporal high-order parametric finite element methods for solving a wide range of geometric flows of curves and surfaces. By incorporating the backward differentiation formulae (BDF) for time discretization into…

Numerical Analysis · Mathematics 2024-08-21 Wei Jiang , Chunmei Su , Ganghui Zhang

The aim of this paper is to develop and analyze high-order time stepping schemes for solving semilinear subdiffusion equations. We apply the $k$-step BDF convolution quadrature to discretize the time-fractional derivative with order…

Numerical Analysis · Mathematics 2020-03-10 Kai Wang , Zhi Zhou

We present a computationally efficient framework, called $\texttt{FlowDRO}$, for solving flow-based distributionally robust optimization (DRO) problems with Wasserstein uncertainty sets while aiming to find continuous worst-case…

Machine Learning · Computer Science 2024-02-27 Chen Xu , Jonghyeok Lee , Xiuyuan Cheng , Yao Xie

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

We study the discretization of generalized Wasserstein distances with nonlinear mobilities on the real line via suitable discrete metrics on the cone of N ordered particles, a setting which naturally appears in the framework of…

Analysis of PDEs · Mathematics 2022-09-01 Simone Di Marino , Lorenzo Portinale , Emanuela Radici

Anomalous diffusion is often modelled in terms of the subdiffusion equation, which can involve a weakly singular source term. For this case, many predominant time stepping methods, including the correction of high-order BDF schemes [{\sc…

Numerical Analysis · Mathematics 2023-06-27 Jiankang Shi , Minghua Chen

We design and compute first-order implicit-in-time variational schemes with high-order spatial discretization for initial value gradient flows in generalized optimal transport metric spaces. We first review some examples of gradient flows…

Numerical Analysis · Mathematics 2023-08-16 Guosheng Fu , Stanley Osher , Wuchen Li

We develop a new computational framework to solve the partial differential equations (PDEs) governing the flow of the joint probability density functions (PDFs) in continuous-time stochastic nonlinear systems. The need for computing the…

Optimization and Control · Mathematics 2019-08-08 Kenneth F. Caluya , Abhishek Halder