# Nonlinear Brownian motion and nonlinear Feynman-Kac formula of path-functions

 Non-equilibrium Dynamics and Random Matrices Topic: Nonlinear Brownian motion and nonlinear Feynman-Kac formula of path-functions Speaker: Shige Peng Affiliation: Shandon University Date: Wednesday, April 23 Time/Room: 2:00pm - 3:00pm/S-101 Video Link: http://video.ias.edu/nedrm/2014/0423-ShigePeng

We consider a typical situation in which probability model itself has non-negligible cumulated uncertainty. A new concept of nonlinear expectation and the corresponding non-linear distributions has been systematically investigated: cumulated nonlinear i.i.d random variables of order $1/n$ tend to a maximal distribution according a new law of large number, whereas, with a new central limit theorem, the accumulation of order $1/\sqrt{n}$ tends to a nonlinear normal distribution. The continuous time uncertainty accumulation derives a nonlinear Brownian motion as well as the corresponding OU-process driven by this nonlinear Brownian motion which converges to a nonlinear invariant measure of Gaussian type. The related stochastic calculus provides us a powerful tools to introduce time-space derivatives for functional of paths. The corresponding Feynman-Kac formula for gives one to one correspondence between fully nonlinear parabolic partial differential equations and backward stochastic differential equations driven by the nonlinear Brownian motion.