Abstract
Optimal matching problems are very classical in computer science, physics and mathematics. In this talk, we will discuss the related rates of convergence of empirical measures associated with n independent random points, whose common distribution is the normal Gaussian distribution in Euclidean space with dimension d ≥ 3. Our method is based on the PDE and mass transportation approach developed by L. Ambrosio, F. Stra and D. Trevisan.