Compound Poisson statistics for dynamical systems via spectral perturbation

Fuente: arXiv
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Auteurs principaux: Atnip, Jason, Froyland, Gary, González-Tokman, Cecilia, Vaienti, Sandro
Format: Preprint
Publié: 2023
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author Atnip, Jason
Froyland, Gary
González-Tokman, Cecilia
Vaienti, Sandro
author_facet Atnip, Jason
Froyland, Gary
González-Tokman, Cecilia
Vaienti, Sandro
contents We consider random transformations $T_ω^n:=T_{σ^{n-1}ω}\circ\cdots\circ T_{σω}\circ T_ω,$ where each map $T_ω$ acts on a complete metrizable space $M$. The randomness comes from an invertible ergodic driving map $σ:Ω\toΩ$ acting on a probability space $(Ω,\mathcal{F},m).$ For a family of random target sets $H_{ω, n}\subset M$ that shrink as $n\to\infty$, 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 $\mathcal{L}^{n}_{ω,0}:=\mathcal{L}_{σ^{n-1}ω,0}\circ\cdots\circ\mathcal{L}_{σω,0}\circ\mathcal{L}_{ω,0}$, where $\mathcal{L}_{ω,0}$ is the transfer operator for the map $T_ω$. We construct a perturbed cocycle with generator $\mathcal{L}_{ω,n,s}(\cdot):=\mathcal{L}_{ω,0}(\cdot e^{is\mathbb{1}_{H_{ω,n}}})$ and an associated random variable $S_{ω,n,k}(x):=\sum_{j=0}^{k-1}\mathbb{1}_{H_{σ^jω,n}}(T_ω^jx)$, which counts the number of visits to random targets in an orbit of length $k$. Under suitable assumptions, we show that in the $n\to\infty$ limit, the random variables $S_{ω,n,n}$ 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.
format Preprint
id arxiv_https___arxiv_org_abs_2308_10798
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Compound Poisson statistics for dynamical systems via spectral perturbation
Atnip, Jason
Froyland, Gary
González-Tokman, Cecilia
Vaienti, Sandro
Dynamical Systems
We consider random transformations $T_ω^n:=T_{σ^{n-1}ω}\circ\cdots\circ T_{σω}\circ T_ω,$ where each map $T_ω$ acts on a complete metrizable space $M$. The randomness comes from an invertible ergodic driving map $σ:Ω\toΩ$ acting on a probability space $(Ω,\mathcal{F},m).$ For a family of random target sets $H_{ω, n}\subset M$ that shrink as $n\to\infty$, 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 $\mathcal{L}^{n}_{ω,0}:=\mathcal{L}_{σ^{n-1}ω,0}\circ\cdots\circ\mathcal{L}_{σω,0}\circ\mathcal{L}_{ω,0}$, where $\mathcal{L}_{ω,0}$ is the transfer operator for the map $T_ω$. We construct a perturbed cocycle with generator $\mathcal{L}_{ω,n,s}(\cdot):=\mathcal{L}_{ω,0}(\cdot e^{is\mathbb{1}_{H_{ω,n}}})$ and an associated random variable $S_{ω,n,k}(x):=\sum_{j=0}^{k-1}\mathbb{1}_{H_{σ^jω,n}}(T_ω^jx)$, which counts the number of visits to random targets in an orbit of length $k$. Under suitable assumptions, we show that in the $n\to\infty$ limit, the random variables $S_{ω,n,n}$ 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.
title Compound Poisson statistics for dynamical systems via spectral perturbation
topic Dynamical Systems
url https://arxiv.org/abs/2308.10798