Compound Poisson statistics for dynamical systems via spectral perturbation
Abstract
We consider random transformations where each map acts on a complete metrizable space . The randomness comes from an invertible ergodic driving map acting on a probability space For a family of random target sets that shrink as , we consider quenched compound Poisson statistics of returns of random orbits to these random targets. We develop a spectral approach to such statistics: associated with the random map cocycle is a transfer operator cocycle , where is the transfer operator for the map . We construct a perturbed cocycle with generator and an associated random variable , which counts the number of visits to random targets in an orbit of length . Under suitable assumptions, we show that in the limit, the random variables converge in distribution to a compound Poisson distributed random variable. We provide several explicit examples for piecewise monotone interval maps in both the deterministic and random settings.
Cite
@article{arxiv.2308.10798,
title = {Compound Poisson statistics for dynamical systems via spectral perturbation},
author = {Jason Atnip and Gary Froyland and Cecilia González-Tokman and Sandro Vaienti},
journal= {arXiv preprint arXiv:2308.10798},
year = {2024}
}