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Nonlinear Fokker-Planck equations for Probability Measures on Path Space and Path-Distribution Dependent SDEs

Published 2 Sep 2017 in math.PR | (1709.00556v2)

Abstract: By investigating path-distribution dependent stochastic differential equations, the following type of nonlinear Fokker--Planck equations for probability measures $(\mu_t){t \geq 0}$ on the path space $\mathcal C:=C([-r_0,0];\mathbb Rd),$ is analyzed: $$\partial_t \mu(t)=L{t,\mu_t}*\mu_t,\ \ t\ge 0,$$ where $\mu(t)$ is the image of $\mu_t$ under the projection $\mathcal C\ni\xi\mapsto \xi(0)\in\mathbb Rd$, and $$L_{t,\mu}(\xi):= \frac 1 2\sum_{i,j=1}d a_{ij}(t,\xi,\mu)\frac{\partial2} {\partial_{\xi(0)i} \partial{\xi(0)j}} +\sum{i=1}d b_i(t,\xi,\mu)\frac{\partial}{\partial_{\xi(0)i}},\ \ t\ge 0, \xi\in \mathcal C, \mu\in \mathcal P{\mathcal C}.$$ Under reasonable conditions on the coefficients $a{ij}$ and $b_i$, the existence, uniqueness, Lipschitz continuity in Wasserstein distance, total variational norm and entropy, as well as derivative estimates are derived for the martingale solutions.

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