In this talk, we present new findings on the regularity of first-order mean field games systems with a local coupling. We focus on systems where the initial density is a compactly supported function on the real line. Our results show that the solution is smooth in regions where the density is strictly positive and that the density itself is globally continuous. Additionally, the speed of propagation is determined by the behavior of the cost function for small densities. When the coupling is entropic, we demonstrate that the support of the density propagates with infinite speed. On the other hand, when f(m) = mθ with θ > 0, we prove that the speed of propagation is finite. In this case, we establish that under a natural non-degeneracy assumption, the free boundary is strictly convex and enjoys C1,1 regularity. We also establish sharp estimates on the speed of support propagation and the rate of long time decay for the density. Our methods are based on the analysis of a new elliptic equation satisfied by the flow of optimal trajectories. The results also apply to mean field planning problems, characterizing the structure of minimizers of a class of optimal transport problems with congestion.
Tag - Optimal transport
In mean-field game theory, Nash equilibria are described through solutions of PDE systems coupling Hamilton-Jacobi and Fokker-Planck equations. When the models involve local functions of the density in the cost functionals, this leads to study PDEs in non-regular setting. In this context a good notion of weak solutions to MFG systems is crucial to characterize singular limits, asymptotic regimes etc. A typical example occurs for vanishing viscosity limits as well as for optimal transport problems with congestion effects.
In recent years, the field of optimal transport has attracted the attention of many high-profile mathematicians with a wide range of applications. In this talk we will discuss some of its recent applications in financial mathematics, particularly on the problems of model calibration, robust finance and portfolio optimisation. Classical topological duality results are extended to probabilistic settings, connecting stochastic control problems with non-linear partial differential equations and providing interesting practical interpretations in finance. We will also look at how numerical methods, including machine learning algorithms, can be implemented to solve these problems.

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