Compound Poisson statistics for dynamical systems via spectral perturbation (2308.10798v2)
Abstract: We consider random transformations $T_\omegan:=T_{\sigma{n-1}\omega}\circ\cdots\circ T_{\sigma\omega}\circ T_\omega,$ where each map $T_{\omega}$ acts on a complete metrizable space $M$. The randomness comes from an invertible ergodic driving map $\sigma:\Omega\to\Omega$ acting on a probability space $(\Omega,\mathcal{F},m).$ For a family of random target sets $H_{\omega, n}\subset M$ 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 $\mathcal{L}{n}{\omega,0}:=\mathcal{L}{\sigma{n-1}\omega,0}\circ\cdots\circ\mathcal{L}{\sigma\omega,0}\circ\mathcal{L}{\omega,0}$, where $\mathcal{L}{\omega,0}$ is the transfer operator for the map $T\omega$. We construct a perturbed cocycle with generator $\mathcal{L}{\omega,n,s}(\cdot):=\mathcal{L}{\omega,0}(\cdot e{is\mathbb{1}{H{\omega,n}}})$ and an associated random variable $S_{\omega,n,k}(x):=\sum_{j=0}{k-1}\mathbb{1}{H{\sigmaj\omega,n}}(T_\omegajx)$, 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 $S_{\omega,n,n}$ 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.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Collections
Sign up for free to add this paper to one or more collections.