A Weyl Criterion for Finite-State Dimension and Applications
Jack H. Lutz, Satyadev Nandakumar, Subin Pulari

TL;DR
This paper extends the classical Weyl criterion to characterize finite-state dimensions of sequences, providing a new analytical tool for studying data compression, prediction, and normality in sequences.
Contribution
It generalizes the Weyl criterion from normality (dimension 1) to all finite-state dimensions, linking exponential sums with finite-state dimension.
Findings
Extended Weyl criterion characterizes all finite-state dimensions.
Finite-state dimension relates to subsequence limits of exponential sums.
Demonstrated utility through illustrative examples.
Abstract
Finite-state dimension, introduced early in this century as a finite-state version of classical Hausdorff dimension, is a quantitative measure of the lower asymptotic density of information in an infinite sequence over a finite alphabet, as perceived by finite automata. Finite-state dimension is a robust concept that now has equivalent formulations in terms of finite-state gambling, lossless finite-state data compression, finite-state prediction, entropy rates, and automatic Kolmogorov complexity. The Schnorr-Stimm dichotomy theorem gave the first automata-theoretic characterization of normal sequences, which had been studied in analytic number theory since Borel defined them. This theorem implies that a sequence (or a real number having this sequence as its base-b expansion) is normal if and only if it has finite-state dimension 1. One of the most powerful classical tools for…
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