English

An iterated random function with Lipschitz number one

Probability 2025-06-30 v1 Dynamical Systems

Abstract

Consider the set of functions fθ(x)=θxf_{\theta}(x)=|\theta -x| on R\mathbb{R}. Define a Markov process that starts with a point x0Rx_0 \in \mathbb{R} and continues with xk+1=fθk+1(xk)x_{k+1}=f_{\theta_{k+1}}(x_{k}) with each θk+1\theta _{k+1} picked from a fixed bounded distribution μ\mu on R+\mathbb{R}^+. We prove the conjecture of G. Letac that if μ\mu is not supported on a lattice, then this process has a unique stationary distribution πμ\pi_{\mu} and any distribution converges under iteration to πμ\pi_{\mu} (in the weak-^* topology). We also give a bound on the rate of convergence in the special case that μ\mu is supported on a two-point set. We hope that the techniques will be useful for the study of other Markov processes where the transition functions have Lipschitz number one.

Keywords

Cite

@article{arxiv.2506.22420,
  title  = {An iterated random function with Lipschitz number one},
  author = {Aaron Abrams and Henry Landau and Zeph Landau and James Pommersheim and Eric Zaslow},
  journal= {arXiv preprint arXiv:2506.22420},
  year   = {2025}
}

Comments

This is the eighth of eleven old articles being uploaded to arxiv after publication

R2 v1 2026-07-01T03:36:55.304Z