Long Time Behavior of Finite and Infinite Dimensional Reflected Brownian Motions
Abstract
This article presents a review of some old and new results on the long time behavior of reflected diffusions. First, we present a summary of prior results on construction, ergodicity and geometric ergodicity of reflected diffusions in the positive orthant $\mathbb{R}^d_+$, $d \in \mathbb{N}$. The geometric ergodicity results, although very general, usually give implicit convergence rates due to abstract couplings and Lyapunov functions used in obtaining them. This leads us to some recent results on an important subclass of reflected Brownian motions (RBM) (constant drift and diffusion coefficients and oblique reflection at boundaries), known as the HarrisonReiman class, where explicit rates of convergence are obtained as functions of the system parameters and underlying dimension. In addition, sufficient conditions on system parameters of the RBM are provided under which local convergence to stationarity holds at a `dimensionfree' rate, that is, for any fixed $k \in \mathbb{N}$, the rate of convergence of the $k$marginal to equilibrium does not depend on the dimension of the whole system. Finally, we study the long time behavior of infinite dimensional rankbased diffusions, including the wellstudied infinite Atlas model. The gaps between the ordered particles evolve as infinite dimensional RBM and this gap process has uncountably many explicit product form stationary distributions. Sufficient conditions for initial configurations to lie in the weak domain of attraction of the various stationary distributions are provided. Finally, it is shown that, under conditions, all of these explicit stationary distributions are extremal (equivalently, ergodic) and, in some sense, the only product form invariant probability distributions. Proof techniques involve a pathwise analysis of RBM using explicit synchronous and mirror couplings and constructing Lyapunov functions.
 Publication:

arXiv eprints
 Pub Date:
 August 2022
 DOI:
 10.48550/arXiv.2208.02855
 arXiv:
 arXiv:2208.02855
 Bibcode:
 2022arXiv220802855B
 Keywords:

 Mathematics  Probability