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The purpose of this work is to establish a quantitative and constructive stability result for a class of subcritical Gagliardo-Nirenberg-Sobolev inequalities which interpolates between the logarithmic Sobolev inequality and the standard…

Analysis of PDEs · Mathematics 2025-02-07 Matteo Bonforte , Jean Dolbeault , Bruno Nazaret , Nikita Simonov

We prove the global-in-time existence of nonnegative weak solutions to a class of fourth order partial differential equations on a convex bounded domain in arbitrary spatial dimensions. Our proof relies on the formal gradient flow structure…

Analysis of PDEs · Mathematics 2015-07-21 Daniel Loibl , Daniel Matthes , Jonathan Zinsl

We prove global-in-time existence and uniqueness of measure solutions of a nonlocal interaction system of two species in one spatial dimension. For initial data including atomic parts we provide a notion of gradient-flow solutions in terms…

Analysis of PDEs · Mathematics 2019-06-26 J. A. Carrillo , M. Di Francesco , A. Esposito , S. Fagioli , M. Schmidtchen

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

We study the implicit bias of gradient flow (i.e., gradient descent with infinitesimal step size) on linear neural network training. We propose a tensor formulation of neural networks that includes fully-connected, diagonal, and…

Machine Learning · Computer Science 2021-09-13 Chulhee Yun , Shankar Krishnan , Hossein Mobahi

We consider a non-standard finite-volume discretization of a strongly non-linear fourth order diffusion equation on the $d$-dimensional cube, for arbitrary $d \geq 1$. The scheme preserves two important structural properties of the…

Analysis of PDEs · Mathematics 2016-06-29 Jan Maas , Daniel Matthes

We consider a class of time dependent second order partial differential equations governed by a decaying entropy. The solution usually corresponds to a density distribution, hence positivity (non-negativity) is expected. This class of…

Numerical Analysis · Mathematics 2018-11-28 Zheng Sun , José A. Carrillo , Chi-Wang Shu

We study the Wasserstein gradient flow of semi-discrete energies in the space of probability measures, that is functionals depending on two measures-one being an absolutely continuous density and the other an atomic measure. These energies…

Analysis of PDEs · Mathematics 2026-03-05 Joao Miguel Machado

The defining equation $(\ast):\ \dot \omega\_t=-F'(\omega\_t),$ of a gradient flow is kinetic in essence. This article explores some dynamical (rather than kinetic) features of gradient flows (i) by embedding equation $(\ast)$ into the…

Probability · Mathematics 2018-06-11 Ivan Gentil , Christian Léonard , Luigia Ripani

We study both the local and global existence of a gradient flow of the Sinai-Ruelle-Bowen entropy functional on a Hilbert manifold of expanding maps of a circle equipped with a Sobolev norm in the tangent space of the manifold. We show…

Mathematical Physics · Physics 2023-06-22 Miaohua Jiang

We study a class of fourth-order quasilinear degenerate parabolic equations under both time-and space-dependent and time-and space-independent forces, modeling non-Newtonian thin-film flow over a solid surface in the "complete wetting"…

Analysis of PDEs · Mathematics 2026-01-06 Jinhong Zhao , Bin Guo

We derive some fluid-dynamic models for electron transport near a Dirac point in graphene. We start from a kinetic model constituted by a set of spinorial Wigner equations, we make suitable scalings (hydrodynamic or diffusive) of the model…

Mathematical Physics · Physics 2019-05-27 Nicola Zamponi

In this paper we study a gradient flow approach to the problem of quantization of measures in one dimension. By embedding our problem in $L^2$, we find a continuous version of it that corresponds to the limit as the number of particles…

Analysis of PDEs · Mathematics 2016-01-26 Emanuele Caglioti , François Golse , Mikaela Iacobelli

In this paper, we give the covariant formulation of second gradient electrodynamics, which is a generalized electrodynamics of second order including derivatives of higher order. The relativistic form of the field equations, the…

Classical Physics · Physics 2020-11-23 Markus Lazar , Jakob Leck

In this work, we present a new approach to analyze the gradient flow for a positive semi-definite matrix denoising problem in an extensive-rank and high-dimensional regime. We use recent linear pencil techniques of random matrix theory to…

Machine Learning · Statistics 2023-03-17 Antoine Bodin , Nicolas Macris

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

In this paper, we introduce a geometric flow for Lagrangian submanifolds in a K\"ahler manifold that stays in its initial Hamiltonian isotopy class and is a gradient flow for volume. The stationary solutions are the Hamiltonian stationary…

Differential Geometry · Mathematics 2024-09-25 Jingyi Chen , Micah Warren

We investigate a family of gradient flows of positive and probability measures, focusing on the Hellinger-Kantorovich (HK) geometry, which unifies transport mechanism of Otto-Wasserstein, and the birth-death mechanism of Hellinger (or…

Analysis of PDEs · Mathematics 2025-01-29 Alexander Mielke , Jia-Jie Zhu

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

Obtaining system parameters and reconstructing the full flow state from limited velocity observations using conventional fluid dynamics solvers can be prohibitively expensive. Here we employ machine learning algorithms to overcome the…

Fluid Dynamics · Physics 2024-10-17 Vladimir Parfenyev , Mark Blumenau , Ilia Nikitin
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