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

preprint2020arXivOpen access

Abstract

By investigating path-distribution dependent stochastic differential equations, the following type of nonlinear Fokker--Planck equations for probability measures (μt)t≥0(μ_t)_{t \geq 0} on the path space C:=C([−r0,0];Rd),\mathcal C:=C([-r_0,0];\mathbb R^d), is analyzed: ∂tμ(t)=Lt,μt∗μt,  t≥0,\partial_t μ(t)=L_{t,μ_t}^*μ_t,\ \ t\ge 0, where μ(t)μ(t) is the image of μtμ_t under the projection C∋ξ↦ξ(0)∈Rd\mathcal C\niξ\mapsto ξ(0)\in\mathbb R^d, and Lt,μ(ξ):=12∑i,j=1daij(t,ξ,μ)∂2∂ξ(0)i∂ξ(0)j+∑i=1dbi(t,ξ,μ)∂∂ξ(0)i,  t≥0,ξ∈C,μ∈PC.L_{t,μ}(ξ):= \frac 1 2\sum_{i,j=1}^d a_{ij}(t,ξ,μ)\frac{\partial^2} {\partial_{ξ(0)_i} \partial_{ξ(0)_j}} +\sum_{i=1}^d b_i(t,ξ,μ)\frac{\partial}{\partial_{ξ(0)_i}},\ \ t\ge 0, ξ\in \mathcal C, μ\in \mathcal P^{\mathcal C}. Under reasonable conditions on the coefficients aija_{ij} and bib_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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