Infinite-volume mixing for dynamical systems preserving an infinite measure
Marco Lenci

TL;DR
This paper introduces a new framework for defining mixing in infinite-measure-preserving dynamical systems using global observables and infinite-volume averages, addressing a key open problem in infinite ergodic theory.
Contribution
It proposes the concept of global observables and infinite-volume averages to define and analyze mixing in infinite measure systems, expanding the understanding beyond local observables.
Findings
Definitions of global-global and global-local mixing introduced
Applied to random walks and Farey map systems
Provides new tools for studying chaos in infinite measure systems
Abstract
In the scope of the statistical description of dynamical systems, one of the defining features of chaos is the tendency of a system to lose memory of its initial conditions (more precisely, of the distribution of its initial conditions). For a dynamical system preserving a probability measure, this property is named `mixing' and is equivalent to the decay of correlations for observables in phase space. For the class of dynamical systems preserving infinite measures, this probabilistic connection is lost and no completely satisfactory definition has yet been found which expresses the idea of losing track of the initial state of a system due to its chaotic dynamics. This is actually on open problem in the field of infinite ergodic theory. Virtually all the definitions that have been attempted so far use "local observables", that is, functions that essentially only "see" finite portions of…
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.
