The local Turnpike Property in Mean Field Control and Games with quadratic Hamiltonian
Marco Cirant, Nicolò De Bernardi
TL;DR
This work addresses the local stability and turnpike behavior of mean field games with a quadratic Hamiltonian in a non-monotone setting. It identifies a stationary state $(\bar{u},\bar{m})$ satisfying a symmetry and a second-order positivity condition (S) that together yield a local exponential turnpike property for dynamic equilibria. By combining a perturbative linearization, a Lyapunov-type energy functional, and a nonlinear fixed-point argument, the authors prove the existence of stable finite-horizon solutions and, for small discount $\delta$, infinite-horizon equilibria that stay exponentially close to $(\bar{u},\bar{m})$. The approach extends turnpike phenomena beyond global uniqueness/monotonicity, leveraging probabilistic flow techniques, spectral-like positivity, and detailed $L^2$ and $L^{\infty}$ estimates on a torus, with potential extension to more general Hamiltonians and dissipative settings.
Abstract
We study the local stability properties of solutions to ergodic and discounted mean field games systems in the long time horizon, around stationary equilibria, when the Hamiltonian is quadratic. We replace the usual monotonicity of the coupling term with a weaker, local assumption on the stationary equilibrium (that need not be unique), stemming from a second-order strict positivity condition. This new stability assumption, together with a symmetry property of the system, allows us to derive an exponential turnpike property for those solutions that are close to the stationary one. Finally, through a fixed-point argument, we establish the actual existence of stable solutions, both on the finite horizon $[0,T]$ and on the infinite horizon, provided that the initial (and terminal) data are close enough to the stationary equilibrium.
