Equilibrium states and invariant measures for random dynamical systems
Ivan Werner

TL;DR
This paper investigates conditions under which random dynamical systems with countably many maps admit invariant measures and equilibrium states, providing necessary and sufficient criteria for their existence.
Contribution
It introduces new non-degeneracy and consistency conditions for such systems and establishes a bijective correspondence between invariant measures and equilibrium states.
Findings
Every uniformly continuous Markov system with a dominating chain is consistent.
Necessary and sufficient conditions for invariant measure existence are provided.
A bijection between invariant measures and equilibrium states is established.
Abstract
Random dynamical systems with countably many maps which admit countable Markov partitions on complete metric spaces such that the resulting Markov systems are uniformly continuous and contractive are considered. A non-degeneracy and a consistency conditions for such systems, which admit some proper Markov partitions of connected spaces, are introduced, and further sufficient conditions for them are provided. It is shown that every uniformly continuous Markov system associated with a continuous random dynamical system is consistent if it has a dominating Markov chain. A necessary and sufficient condition for the existence of an invariant Borel probability measure for such a non-degenerate system with a dominating Markov chain and a finite (16) is given. The condition is also sufficient if the non-degeneracy is weakened with the consistency condition. A further sufficient condition for…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
