MATH-748 / 2 crédits

Enseignant: Invited lecturers (see below)

Langue: Anglais

Remark: Spring semester: 15.4-30.06.2027


Frequency

Only this year

Summary

The main goal is to analyse aggregation-diffusion PDEs. These ubiquitous models are descriptions of many body interacting particle systems with applications in physics, biology and data science. Calculus of variations, optimal transport and PDE tools will be used for understanding their properties.

Content

Part I Introduction and preliminaries

 

1. Motivation and examples: bacterial chemotaxis, granular flows, damping dominated systems, opinion dynamics, data science.
2. Aggregation-Diffusion Equations: a brief introduction
3. A primer on optimal transport theory

 

Part II The Aggregation Equation

 

4. Nonlocal interactions via smooth potentials
5. Nonlocal interaction via mildly singular potentials and one dimensional aggregation equations 
6. The case of singular interaction potentials   
7. Minima of nonlocal interaction energies

 

Part III The case with diffusion

 

8. Linear diffusion: Periodic case and bifurcations.
9. A primer on nonlinear diffusions: Classical and Variational Approach
10. A priori estimates and functional inequalities
11. Asymptotic behavior: the case of homogeneous potentials

Keywords

Nonlinear Fokker-Planck equations, optimal transport, gradient flows, free energies, minimizers, HLS inequalities, asymptotic behavior, bifurcations.

Learning Prerequisites

Required courses

Basic PDE course

Recommended courses

Optimal transport course but not necessary

Learning Outcomes

By the end of the course, the student must be able to:

  • Analyze Qualitative properties of solutions of nonlocal aggregation-diffusion equations, Long time aysmptotics. Mininimizers of interaction energies.

Resources

Bibliography

Own material, course given at the University of Oxford and book in preparation.

Moodle Link

Dans les plans d'études

  • Forme de l'examen: Exposé (session libre)
  • Matière examinée: Topics on Aggregation-Diffusion PDEs
  • Cours: 22 Heure(s)
  • Projet: 12 Heure(s)
  • Type: optionnel

Semaine de référence

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