On dynamical bit sequences

TL;DR

This paper investigates the probability of certain sum events in a dynamical sequence of i.i.d. Bernoulli variables, deriving sharp estimates linked to capacity and fractal dimensions, with implications for sample-path properties.

Contribution

It provides new sharp probability estimates for sum events in dynamical Bernoulli sequences, connecting these to capacity and fractal dimension concepts, and addresses a question from prior work.

Findings

Probability described by Kolmogorov capacitance for fixed 

Probability linked to Howroyd's 1/2-dimensional box-dimension profiles

Sample-path properties connected to capacity and fractal dimensions

Abstract

Let X^{(k)}(t) = (X_1(t), ..., X_k(t)) denote a k-vector of i.i.d. random variables, each taking the values 1 or 0 with respective probabilities p and 1-p. As a process indexed by non-negative t, $X^{(k)}(t)$ is constructed--following Benjamini, Haggstrom, Peres, and Steif (2003)--so that it is strong Markov with invariant measure ((1-p)\delta_0+p\delta_1)^k. We derive sharp estimates for the probability that ``X_1(t)+...+X_k(t)=k-\ell for some t in F,'' where F \subset [0,1] is nonrandom and compact. We do this in two very different settings: (i) Where \ell is a constant; and (ii) Where \ell=k/2, k is even, and p=q=1/2. We prove that the probability is described by the Kolmogorov capacitance of F for case (i) and Howroyd's 1/2-dimensional box-dimension profiles for case (ii). We also present sample-path consequences, and a connection to capacities that answers a question of Benjamini et. al. (2003)