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In this paper, we establish a novel approach to proving existence of non-negative weak solutions for degenerate parabolic equations of fourth order, like the Cahn-Hilliard and certain thin film equations. The considered evolution equations…

Analysis of PDEs · Mathematics 2014-09-16 Stefano Lisini , Daniel Matthes , Giuseppe Savaré

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

Let $V_* : \mathbb{R}^d \to \mathbb{R}$ be some (possibly non-convex) potential function, and consider the probability measure $\pi \propto e^{-V_*}$. When $\pi$ exhibits multiple modes, it is known that sampling techniques based on…

Optimization and Control · Mathematics 2023-02-24 Carles Domingo-Enrich , Aram-Alexandre Pooladian

Macroscopic equations arising out of stochastic particle systems in detailed balance (called dissipative systems or gradient flows) have a natural variational structure, which can be derived from the large-deviation rate functional for the…

Mathematical Physics · Physics 2023-10-05 Robert I. A. Patterson , D. R. Michiel Renger , Upanshu Sharma

We consider a one-dimensional aggregation-diffusion equation, which is the gradient flow in the Wasserstein space of a functional with competing attractive-repulsive interactions. We prove that the fully deterministic particle…

Analysis of PDEs · Mathematics 2021-01-01 Sara Daneri , Emanuela Radici , Eris Runa

We develop unified and easy to use framework to study robust fully discrete numerical methods for nonlinear degenerate diffusion equations $$ \partial_t u-\mathfrak{L}[\varphi(u)]=f(x,t) \qquad\text{in}\qquad \mathbb{R}^N\times(0,T), $$…

Numerical Analysis · Mathematics 2018-10-17 Félix del Teso , Jørgen Endal , Espen R. Jakobsen

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

We address the inverse problem of identifying nonlocal interaction potentials in nonlinear aggregation-diffusion equations from noisy discrete trajectory data. Our approach involves formulating and solving a regularized variational problem,…

Analysis of PDEs · Mathematics 2025-01-31 Jose A. Carrillo , Gissell Estrada-Rodriguez , Laszlo Mikolas , Sui Tang

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

We consider finite-volume approximations of Fokker-Planck equations on bounded convex domains in $\mathbb{R}^d$ and study the corresponding gradient flow structures. We reprove the convergence of the discrete to continuous Fokker-Planck…

Analysis of PDEs · Mathematics 2020-08-26 Dominik Forkert , Jan Maas , Lorenzo Portinale

In this paper, the inherent gradient flow structures of thermo-poro-visco-elastic processes in porous media are examined for the first time. In the first part, a modelling framework is introduced aiming for describing such processes as…

Numerical Analysis · Mathematics 2019-11-27 Jakub Wiktor Both , Kundan Kumar , Jan Martin Nordbotten , Florin Adrian Radu

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

The displacement $\lambda$-convexity of a nonstandard entropy with respect to a nonlocal transportation metric in finite state spaces is shown using a gradient flow approach. The constant $\lambda$ is computed explicitly in terms of a…

Analysis of PDEs · Mathematics 2016-11-16 José A. Carrillo , Ansgar Jüngel , Matheus C. Santos

We investigate a Poisson-Nernst-Planck type system in three spatial dimensions where the strength of the electric drift depends on a possibly small parameter and the particles are assumed to diffuse quadratically. On grounds of the global…

Analysis of PDEs · Mathematics 2015-10-23 Jonathan Zinsl

Wasserstein gradient flow provides a general framework for minimizing an energy functional $J$ over the space of probability measures on a Riemannian manifold $(M,g)$. Its canonical time-discretization, the Jordan-Kinderlehrer-Otto (JKO)…

Machine Learning · Statistics 2026-03-05 Peter Halmos , Boris Hanin

We study Markov processes associated with stochastic differential equations, whose non-linearities are gradients of convex functionals. We prove a general result of existence of such Markov processes and a priori estimates on the transition…

Probability · Mathematics 2007-05-23 Luigi Ambrosio , Giuseppe Savare , Lorenzo Zambotti

We formulate the fractional Ricci flow theory for (pseudo) Riemannian geometries enabled with nonholonomic distributions defining fractional integro-differential structures, for non-integer dimensions. There are constructed fractional…

Differential Geometry · Mathematics 2012-08-13 Sergiu I. Vacaru

As a counterpoint to recent numerical methods for crystal surface evolution, which agree well with microscopic dynamics but suffer from significant stiffness that prevents simulation on fine spatial grids, we develop a new numerical method…

Numerical Analysis · Mathematics 2020-06-24 Katy Craig , Jian-Guo Liu , Jianfeng Lu , Jeremy L. Marzuola , Li Wang

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 develop a gradient-flow theory for time-dependent functionals defined in abstract metric spaces. Global well-posedness and asymptotic behavior of solutions are provided. Conditions on functionals and metric spaces allow to consider the…

Analysis of PDEs · Mathematics 2015-09-15 Lucas C. F. Ferreira , Julio C. Valencia-Guevara
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