Rate of propagation of chaos for diffusive stochastic particle systems via Girsanov transformation

Abstract: This paper focus on investigating the explicit rate of convergence for the propagation of chaos, in a pathwise sense a family of interacting stochastic particle related to some Brownian driven McKean-Vlasov dynamics. Precisely the McKean form of nonlinearity is concentrated on a path dependent drift component and satisfies a particular sub-gaussian moment control. Such control enables to derive a uniform estimate of the cost in terms of exponential martingale between the particle and its McKean/mean-field limit system which in turn provide an optimal rate of propagation of chaos in terms of the total variation distance. As a by-product, we deepen some recent propagation of chaos results due to Lacker 2018 and provides a partial stochastic interpretation of the entropy control technique introduced in Jabin and Wang 2016.