Superpositions for General Conditional Mckean-Vlasov Stochastic Differential Equations
Qi Feng, Jin Ma

TL;DR
This paper establishes superposition principles linking Conditional McKean-Vlasov SDEs, nonlinear Zakai equations, and infinite-dimensional Fokker-Planck equations, providing new insights into their well-posedness in a general setting.
Contribution
It introduces superposition principles connecting these complex equations, enabling the transfer of well-posedness results among them in a novel, highly general framework.
Findings
Proved superposition principle between nonlinear Zakai equation and CMVSDE.
Established superposition principle between infinite-dimensional Fokker-Planck and Zakai equations.
Demonstrated well-posedness results in a broad, previously unexplored setting.
Abstract
In this paper, we study the connection between a general class of Conditional Mckean-Vlasov Stochastic Differential Equations (CMVSDEs) and its corresponding (infinite dimensional) Conditional Fokker-Planck Equation. The CMVSDE under consideration is similar to the one studied in [4], which is a non-trivial generalization of the McKean-Vlasov SDE with common noise and is closely related to a new type of non-linear Zakai equation that has not been studied in the literature. The main purpose of this paper is to establish the superposition principles among the three subjects so that their well-posedness can imply each other. More precisely, we shall first prove the superposition principle between the non-linear Zakai equation, a non-linear measure-valued stochastic PDE, and a CMVSDE; and then prove the superposition principle between an infinite dimensional conditional Fokker-Planck…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSpectral Theory in Mathematical Physics · Stochastic processes and financial applications · Gas Dynamics and Kinetic Theory
