  This article investigates the convergence of the Generalized Frank-Wolfe
(GFW) algorithm for the resolution of potential and convex second-order mean
field games. More specifically, the impact of the discretization of the
mean-field-game system on the effectiveness of the GFW algorithm is analyzed.
The article focuses on the theta-scheme introduced by the authors in a previous
study. A sublinear and a linear rate of convergence are obtained, for two
different choices of stepsizes. These rates have the mesh-independence
property: the underlying convergence constants are independent of the
discretization parameters.
