Optimal Transport for Applied Mathematicians: Calculus of Variations, PDEs, and ModelingBirkhäuser, 17 oct. 2015 - 353 pages This monograph presents a rigorous mathematical introduction to optimal transport as a variational problem, its use in modeling various phenomena, and its connections with partial differential equations. Its main goal is to provide the reader with the techniques necessary to understand the current research in optimal transport and the tools which are most useful for its applications. Full proofs are used to illustrate mathematical concepts and each chapter includes a section that discusses applications of optimal transport to various areas, such as economics, finance, potential games, image processing and fluid dynamics. Several topics are covered that have never been previously in books on this subject, such as the Knothe transport, the properties of functionals on measures, the Dacorogna-Moser flow, the formulation through minimal flows with prescribed divergence formulation, the case of the supremal cost, and the most classical numerical methods. Graduate students and researchers in both pure and applied mathematics interested in the problems and applications of optimal transport will find this to be an invaluable resource. |
Table des matières
1 Primal and dual problems | 1 |
2 Onedimensional issues | 58 |
3 L1 and L theory | 86 |
4 Minimal flows | 120 |
5 Wasserstein spaces | 177 |
6 Numerical methods | 219 |
7 Functionals over probabilities | 249 |
8 Gradient flows | 285 |
Exercises | 324 |
339 | |
351 | |
Autres éditions - Tout afficher
Optimal Transport for Applied Mathematicians: Calculus of Variations, PDEs ... Filippo Santambrogio Aucun aperçu disponible - 2016 |
Optimal Transport for Applied Mathematicians: Calculus of Variations, PDEs ... Filippo Santambrogio Aucun aperçu disponible - 2015 |
Optimal Transport for Applied Mathematicians: Calculus of Variations, PDEs ... Filippo Santambrogio Aucun aperçu disponible - 2015 |
Expressions et termes fréquents
absolutely continuous algorithm apply approximation assumptions atomic barycenter bounded c-concave Chapter compact compute concave concave function condition consider constraint continuity equation continuous function convex function cost c(x countable curves defined definition denote density differentiable displacement convexity domain duality equilibrium existence fact finite function f geodesic given gradient flow hence Hint to Ex implies inequality infimum Kantorovich potential Knothe Lebesgue measure Lemma linear Lipschitz continuous mass Math measures µ metric space minimization Monge monotone norm Note obtained optimal map optimal transport map optimal transport plan particles particular probability measures Proof properties Proposition prove result satisfies Section semi-continuity sequence solution spt(y strictly convex subdifferential Suppose Theorem transport problem triangle inequality unique v₁ vector field weak convergence