Selection principle for Weak KAM solutions on Rn via large deviation principle for diffusions
Yuan Gao, Yuxi Han
Abstract
Stationary Hamilton-Jacobi equations generally admit many weak KAM solutions. The question is how to select one weak KAM solution that reflects a meaningful physical principle. In this paper, we propose a selection principle for Hamilton-Jacobi equations arising from the large deviation principle of general drift-diffusion processes on Rn based on the exponential asymptotics of invariant measures. We first characterize the Aubry set as the finitely many equilibria of the drift, using an action estimate from the orthogonal decomposition of the drift. For any boundary data on the Aubry set compatible with the Peierls barrier, we construct the unique coercive weak KAM solution with these boundary data, which is also the maximal locally Lipschitz viscosity solution. The Freidlin-Wentzell graph formula then provides the boundary data on the Aubry set that select the unique weak KAM solution. The selected solution is exactly the rate function in the large deviation principle for invariant measures in the zero noise limit. We also show that this rate function is the vanishing viscosity limit, to which the viscous approximations converge locally uniformly. Finally, under additional regularity assumptions, we show that the long-time and zero-noise limits commute for suitably prepared initial densities.
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