2000 character limit reached
Convergence Rates in Uniform Ergodicity by Hitting Times and $L^2$-exponential Convergence Rates
Published 14 Feb 2021 in math.PR | (2102.07069v2)
Abstract: Generally the convergence rate in exponential ergodicity $\lambda$ is an upper bound for the convergence rate $\kappa$ in uniform ergodicity for a Markov process, that is $\lambda\geqslant\kappa$. In this paper, we prove that $\kappa\geqslant \inf {lambda,1/M_H}$, where $M_H$ is a uniform bound on the moment of the hitting time to a "compact" set $H$. In the case where $M_H$ can be made arbitrarily small for $H$ large enough, we obtain that $\lambda=\kappa$. The general results are applied to Markov chains, diffusion processes and solutions to SDEs driven by symmetric stable processes.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.