Weak-Strong Uniqueness for Second-Order Mean-Field Games

TL;DR

This paper extends the weak-strong uniqueness principle to second-order mean-field game systems, ensuring weak solutions coincide with strong solutions under certain conditions, including models with variable diffusion and quadratic growth regimes.

Contribution

It introduces a novel approach for establishing weak-strong uniqueness in second-order MFGs with variable diffusion and quadratic growth, using monotonicity and mollification strategies.

Findings

Proves weak-strong uniqueness for a broad class of second-order MFGs.

Develops a new a priori second-order estimate for quadratic growth regimes.

Shows that weak solutions from numerical methods coincide with strong solutions when they exist.

Abstract

We extend the weak-strong uniqueness principle for mean-field game (MFG) systems to a broad class of second-order stationary and time-dependent problems. Under standard monotonicity, growth, and coercivity assumptions on the Hamiltonian, and relying strictly on the integrability exponents guaranteed by the existing theory for monotone MFG systems, we show that any weak solution must coincide with a given strong solution. Our analysis covers models with spatially dependent scalar diffusion coefficients, using monotonicity arguments and a coefficient-adapted mollification strategy to manage the variable diffusion terms. We extend this strategy to establish weak-strong uniqueness in the corresponding second-order, initial-terminal, time-dependent setting. Finally, to address the critical quadratic growth regime, we derive a new a priori second-order estimate for a stationary MFG system with logarithmic coupling. This estimate provides quantitative bounds on the solution in terms of the data, and yields weak-strong uniqueness in the range where the improved integrability yields $L^2$ control of the density. Since numerical and approximation methods for MFGs naturally yield weak solutions in the monotonicity sense, whereas strong solutions are known to exist in many settings, our results identify any weak limit produced by such methods with the strong solution whenever one exists.