Lipschitz Stability Estimate and Uniqueness in the Retrospective Analysis for The Mean Field Games System via Two Carleman Estimates

Abstract

A retrospective analysis process for the mean field games system (MFGS) is considered. For the first time, Carleman estimates are applied to the analysis of the MFGS. Two new Carleman estimates are derived. They allow to obtain the Lipschitz stability estimate with respect to the possible error in the input initial and terminal data for a retrospective problem for MFGS. This stability estimate, in turn implies uniqueness theorem for the problem under the consideration. The idea of using Carleman estimates to obtain stability and uniqueness results came from the field of Ill-Posed and Inverse Problems.