Entrance measures for semigroups of time-inhomogeneous SDEs: possibly degenerate and expanding
Chunrong Feng, Baoyou Qu, Huaizhong Zhao

TL;DR
This paper develops a unified approach to analyze the long-term behavior of time-inhomogeneous Markov processes, including degenerate and expanding SDEs, establishing convergence to entrance measures and existence of invariant measures.
Contribution
It extends Harris's small set method to time-inhomogeneous SDEs with possibly degenerate and non-weakly-dissipative drifts, providing new convergence and ergodicity results.
Findings
Established convergence to entrance measures under weighted total variation.
Proved existence and uniqueness of quasi-periodic and invariant measures.
Applied the method to SDEs with degenerate and expanding dynamics.
Abstract
In this article, we solve the problem of the long time behaviour of transition probabilities of time-inhomogeneous Markov processes and give a unified approach to stochastic differential equations (SDEs) with periodic, quasi-periodic, almost-periodic forcing and much beyond. We extend Harris's ``small set'' method to the time-inhomogeneous situation with the help of Hairer-Mattingly's refinement of Harris's recurrence to a one-step contraction of probability measures under the total variation distance weighted by some appropriate Lyapunov function and a constant . We show that the convergence to an entrance measure under implies the convergence both in the total variation distance and the Wasserstein distance . For SDEs with locally Lipschitz and polynomial growth coefficients, in order to establish the local Doeblin condition, we…
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Taxonomy
TopicsStochastic processes and financial applications · Stochastic processes and statistical mechanics · Markov Chains and Monte Carlo Methods
