A \(\lambda\)-convexity based proof for the propagation of chaos for weakly interacting stochastic particles

DOI10.1016/j.jfa.2020.108734zbMath1459.60005OpenAlexW3048401089MaRDI QIDQ2197808

Matias G. Delgadino, Grigorios A. Pavliotis, José Antonio Carrillo

Publication date: 1 September 2020

Published in: Journal of Functional Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfa.2020.108734

zbMATH Keywords

gamma-convergencepropagation of chaosgradient flows

Mathematics Subject Classification ID

Interacting random processes; statistical mechanics type models; percolation theory (60K35) Stochastic methods (Fokker-Planck, Langevin, etc.) applied to problems in time-dependent statistical mechanics (82C31) PDEs with randomness, stochastic partial differential equations (35R60) Convergence of probability measures (60B10) Fokker-Planck equations (35Q84)

Related Items (7)

Coarse graining of a Fokker–Planck equation with excluded volume effects preserving the gradient flow structure ⋮ Phase transitions, logarithmic Sobolev inequalities, and uniform-in-time propagation of chaos for weakly interacting diffusions ⋮ On the diffusive-mean field limit for weakly interacting diffusions exhibiting phase transitions ⋮ Mean-field limits: from particle descriptions to macroscopic equations ⋮ Convergence rates for the Vlasov-Fokker-Planck equation and uniform in time propagation of chaos in non convex cases ⋮ Propagation of chaos: a review of models, methods and applications. I: Models and methods ⋮ Propagation of chaos: a review of models, methods and applications. II: Applications

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