English

On distributional limit laws for recurrence

Dynamical Systems 2025-05-22 v2 Probability

Abstract

For a probability measure preserving dynamical system (X,f,μ)(\mathcal{X},f,\mu), the Poincar\'e Recurrence Theorem asserts that μ\mu-almost every orbit is recurrent with respect to its initial condition. This motivates study of the statistics of the process Xn(x)=dist(fn(x),x))X_n(x)=\text{dist}(f^n(x),x)), and real-valued functions thereof. For a wide class of non-uniformly expanding dynamical systems, we show that the time-nn counting process Rn(x)R_n(x) associated to the number recurrences below a certain radii sequence rn(τ)r_n(\tau) follows an \emph{averaged} Poisson distribution G(τ)G(\tau). Furthermore, we obtain quantitative results on almost sure rates for the recurrence statistics of the process XnX_n.

Keywords

Cite

@article{arxiv.2401.13300,
  title  = {On distributional limit laws for recurrence},
  author = {Mark Holland and Mike Todd},
  journal= {arXiv preprint arXiv:2401.13300},
  year   = {2025}
}

Comments

Various updates in exposition, typos corrected. To appear in Nonlinearity

R2 v1 2026-06-28T14:25:35.525Z