Primal dual methods for Wasserstein gradient flows

Applied Math And Analysis Seminar

Li Wang (University of Minnesota)

Monday, August 20, 2018 -
9:30am to 10:30am
Physics 047

In this talk, I will introduce a variational method for nonlinear equations with a gradient flow structure, which arise widely in applications such as porous median flows, material science, animal swarms, and chemotaxis. Our method builds on the JKO framework and a reformulation of the Wasserstein distance into a convex optimization with a linear PDE constraint. As a result, we end up with one nested structure of optimization problem with two time scales, and we adopt a recent primal dual three operator splitting scheme. Thanks to the variational structure, our method has a built-in positivity preserving, entropy decreasing properties, and overcomes stability issue due to the strong nonlinearity and degeneracy. Upon discretization of the PDE constraint, we also show the Γ−convergence of the fully discrete optimization towards the semi-discrete JKO scheme. This is a joint work with Jose Carrillo, Katy Craig, and Chaozhen Wei.

Last updated: 2018/12/12 - 2:21pm