Lagrangian stochastic models with specular boundary condition

TL;DR

This paper proves the well-posedness of a Lagrangian stochastic model with specular boundary conditions in smooth bounded domains, extending previous work from simpler geometries and combining stochastic calculus with PDE analysis.

Contribution

It extends the well-posedness results of Lagrangian stochastic models with specular boundary conditions to general smooth bounded domains, using a combination of stochastic calculus and PDE techniques.

Findings

Established well-posedness in smooth bounded domains

Constructed Langevin processes satisfying boundary conditions

Derived time-marginal densities for nonlinear processes

Abstract

In this paper, we prove the well-posedness of a conditional McKean Lagrangian stochastic model endowing the specular boundary condition and the mean no--permeability condition in smooth bounded confinement domain D. This result extend our previous work, where we dealt with the case where the confinement domain is the upper--half plane and where the specular boundary condition is introduced in generic Langevin process owing to some well known results on the law of the passage times at zero of the Brownian primitive. The extension to more general confinement domain exhibit more difficulties that can be handled by combining stochastic calculus and the analysis of kinetic equations. As a prerequisite for the nonlinear case, we construct a Langevin process confined in D and satisfying the specular boundary condition. We then use PDE techniques to construct the time-marginal densities of the nonlinear process from which we are able to exhibit the conditional McKean Lagrangian stochastic model.