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A reaction-diffusion equation with power nonlinearity formulated either on the half-line or on the finite interval with nonzero boundary conditions is shown to be locally well-posed in the sense of Hadamard for data in Sobolev spaces. The…

Analysis of PDEs · Mathematics 2018-10-15 A. Alexandrou Himonas , Dionyssios Mantzavinos , Fangchi Yan

This is an expository paper on the theory of gradient flows, and in particular of those PDEs which can be interpreted as gradient flows for the Wasserstein metric on the space of probability measures (a distance induced by optimal…

Analysis of PDEs · Mathematics 2016-09-14 Filippo Santambrogio

The well-posedness and regularity properties of diffusion-aggregation equations, emerging from interacting particle systems, are established on the whole space for bounded interaction force kernels by utilizing a compactness convergence…

Analysis of PDEs · Mathematics 2024-06-19 Li Chen , Paul Nikolaev , David J. Prömel

Aggregation-diffusion equations are foundational tools for modelling biological aggregations. Their principal use is to link the collective movement mechanisms of organisms to their emergent space use patterns in a concrete mathematical…

Populations and Evolution · Quantitative Biology 2025-04-16 Jonathan R. Potts

This paper is devoted to global well-posedness, self-similarity and symmetries of solutions for a superdiffusive heat equation with superlinear and gradient nonlinear terms with initial data in new homogeneous Besov-Morrey type spaces.…

Analysis of PDEs · Mathematics 2016-05-06 Marcelo Fernandes de Almeida , Arlúcio da Cruz Viana

Typically, aggregation-diffusion is modeled by parabolic equations that combine linear or nonlinear diffusion with a Fokker-Planck convection term. Under very general suitable assumptions, we prove that radial solutions of the evolution…

Analysis of PDEs · Mathematics 2021-12-15 Jose A. Carrillo , David Gómez-Castro , Juan Luis Vázquez

In this manuscript we review new ideas and first results on application of the Graphical Models approach, originated from Statistical Physics, Information Theory, Computer Science and Machine Learning, to optimization problems of network…

Systems and Control · Computer Science 2017-02-08 Michael Chertkov , Sidhant Misra , Marc Vuffray , Dvijotham Krishnamurty , Pascal Van Hentenryck

We analyze some parabolic PDEs with different drift terms which are gradient flows in the Wasserstein space and consider the corresponding discrete-in-time JKO scheme. We prove with optimal transport techniques how to control the L p and L…

Analysis of PDEs · Mathematics 2019-11-26 Simone Di Marino , Filippo Santambrogio

We describe the mathematical theory of diffusion and heat transport with a view to including some of the main directions of recent research. The linear heat equation is the basic mathematical model that has been thoroughly studied in the…

Analysis of PDEs · Mathematics 2017-06-27 Juan Luis Vázquez

We develop a microscopic theory for the dynamics of quantum fluids of light, deriving an effective kinetic equation in momentum space that takes the form of the convection-diffusion equation. In the particular case of two-dimensional…

We give sharp conditions for the large time asymptotic simplification of aggregation-diffusion equations with linear diffusion. As soon as the interaction potential is bounded and its first and second derivatives decay fast enough at…

Analysis of PDEs · Mathematics 2021-05-28 José A. Carrillo , David Gómez-Castro , Yao Yao , Chongchun Zeng

We investigate a class of aggregation-diffusion equations with strongly singular kernels and weak (fractional) dissipation in the presence of an incompressible flow. Without the flow the equations are supercritical in the sense that the…

Analysis of PDEs · Mathematics 2020-06-09 Katharina Hopf , José L. Rodrigo

We establish the well-posedness of an initial-boundary value problem for a general class of time-fractional, advection-diffusion-reaction equations, allowing space- and time-dependent coefficients as well as initial data that may have low…

Analysis of PDEs · Mathematics 2020-03-24 William McLean , Kassem Mustapha , Raed Ali , Omar Knio

We consider a Keller-Segel model with non-linear porous medium type diffusion and nonlocal attractive power law interaction, focusing on potentials that are less singular than Newtonian interaction. Here, the nonlinear diffusion is chosen…

Analysis of PDEs · Mathematics 2023-06-30 Shen Bian , Jiale Bu

Subsurface flows are commonly modeled by advection-diffusion equations. Insufficient measurements or uncertain material procurement may be accounted for by random coefficients. To represent, for example, transitions in heterogeneous media,…

Numerical Analysis · Mathematics 2021-01-25 Andrea Barth , Andreas Stein

The diffusion equation is the primary tool to study the movement dynamics of a free Brownian particle, but when spatial heterogeneities in the form of permeable interfaces are present, no fundamental equation has been derived. Here we…

Statistical Mechanics · Physics 2022-09-14 Toby Kay , Luca Giuggioli

We study the diffusion equation with an appropriate change of variables. This equation is in general a partial differential equation (PDE). With the self-similar and related Ansat\"atze we transform the PDE of diffusion to an ordinary…

Classical Physics · Physics 2023-04-14 Imre Ferenc Barna , László Mátyás

This paper reviews (and expands) some recent results on the modeling of aggregation-diffusion phenomena at various scales, focusing on the emergence of collective dynamics as a result of the competition between attractive and repulsive…

Analysis of PDEs · Mathematics 2024-01-04 Inwon Kim , Antoine Mellet , Jeremy Sheung-Him Wu

Wasserstein gradient flows provide a powerful means of understanding and solving many diffusion equations. Specifically, Fokker-Planck equations, which model the diffusion of probability measures, can be understood as gradient descent over…

Machine Learning · Computer Science 2021-10-26 Petr Mokrov , Alexander Korotin , Lingxiao Li , Aude Genevay , Justin Solomon , Evgeny Burnaev

We propose a new Neural Galerkin Normalizing Flow framework to approximate the transition probability density function of a diffusion process by solving the corresponding Fokker-Planck equation with an atomic initial distribution,…

Machine Learning · Computer Science 2026-03-20 Riccardo Saporiti , Fabio Nobile
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