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On Normality and Equidistribution for Separator Enumerators

Subin Pulari

TL;DR

The paper investigates whether $f$-normality, defined via a representation-driven finite-state dimension with separator enumerators, can be characterized by equidistribution properties of the best-approximation-from-below sequence. It first proves a strong negative result: there exist computable $f_0,f_1$ and $x$ with identical $a_n^{f}(x)$ yet drastically different $f$-dimensions, ruling out a universal equidistribution criterion across all enumerators. It then identifies a natural structured regime—finite-state coherent enumerators obtained by invertible synchronous Mealy relabelings—where a complete equidistribution characterization holds: $f$-normality is equivalent to $k$-adic equidistribution of $(k^{n}a_n^{f}(x))$, aligning with base-$k$ normality. The work connects the representation-based framework to classical randomness notions and clarifies when equidistribution criteria can be used, while outlining directions for extending these results beyond the coherent regime.

Abstract

A separator is a countable dense subset of $[0,1)$, and a separator enumerator is a naming scheme that assigns a real number in $[0,1)$ to each finite word so that the set of all named values is a separator. Mayordomo introduced separator enumerators to define $f$-normality and a relativized finite-state dimension $\dim^{f}_{\mathrm{FS}}(x)$, where finite-state dimension measures the asymptotic lower rate of finite-state information needed to approximate $x$ through its $f$-names. This framework extends classical base-$k$ normality, and Mayordomo showed that it supports a point-to-set principle for finite-state dimension. This representation-based viewpoint has since been developed further in follow-up work, including by Calvert et al., yielding strengthened randomness notions such as supernormal and highly normal numbers. Mayordomo posed the following open question: can $f$-normality be characterized via equidistribution properties of the sequence $\left(|Σ|^{n} a^{f}_{n}(x)\right)_{n=0}^{\infty}$, where $a^{f}_{n}(x)$ is the sequence of best approximations to $x$ from below induced by $f$? We give a strong negative answer: we construct computable separator enumerators $f_0,f_1$ and a point $x$ such that $a^{f_0}_{n}(x)=a^{f_1}_{n}(x)$ for all $n$, yet $\dim^{f_0}_{\mathrm{FS}}(x)=0$ while $\dim^{f_1}_{\mathrm{FS}}(x)=1$. Consequently, no criterion depending only on the sequence $\left(|Σ|^{n} a^{f}_{n}(x)\right)_{n=0}^{\infty}$ - in particular, no equidistribution property of this sequence - can characterize $f$-normality uniformly over all separator enumerators. On the other hand, for a natural finite-state coherent class of separator enumerators we recover a complete equidistribution characterization of $f$-normality.

On Normality and Equidistribution for Separator Enumerators

TL;DR

The paper investigates whether -normality, defined via a representation-driven finite-state dimension with separator enumerators, can be characterized by equidistribution properties of the best-approximation-from-below sequence. It first proves a strong negative result: there exist computable and with identical yet drastically different -dimensions, ruling out a universal equidistribution criterion across all enumerators. It then identifies a natural structured regime—finite-state coherent enumerators obtained by invertible synchronous Mealy relabelings—where a complete equidistribution characterization holds: -normality is equivalent to -adic equidistribution of , aligning with base- normality. The work connects the representation-based framework to classical randomness notions and clarifies when equidistribution criteria can be used, while outlining directions for extending these results beyond the coherent regime.

Abstract

A separator is a countable dense subset of , and a separator enumerator is a naming scheme that assigns a real number in to each finite word so that the set of all named values is a separator. Mayordomo introduced separator enumerators to define -normality and a relativized finite-state dimension , where finite-state dimension measures the asymptotic lower rate of finite-state information needed to approximate through its -names. This framework extends classical base- normality, and Mayordomo showed that it supports a point-to-set principle for finite-state dimension. This representation-based viewpoint has since been developed further in follow-up work, including by Calvert et al., yielding strengthened randomness notions such as supernormal and highly normal numbers. Mayordomo posed the following open question: can -normality be characterized via equidistribution properties of the sequence , where is the sequence of best approximations to from below induced by ? We give a strong negative answer: we construct computable separator enumerators and a point such that for all , yet while . Consequently, no criterion depending only on the sequence - in particular, no equidistribution property of this sequence - can characterize -normality uniformly over all separator enumerators. On the other hand, for a natural finite-state coherent class of separator enumerators we recover a complete equidistribution characterization of -normality.
Paper Structure (8 sections, 14 theorems, 33 equations)

This paper contains 8 sections, 14 theorems, 33 equations.

Key Result

Lemma 1

There exists an infinite sequence $Z\in\Sigma^{\infty}$ such that for every $\Sigma$-FST $T$, where $z_n:=Z\!\upharpoonright\! n$.

Theorems & Definitions (36)

  • Definition 1: Finite-state transducer (FST)
  • Definition 2: $T$-information content Mayordomo2025
  • Definition 3: Separator, separator enumerator Mayordomo2025
  • Definition 4: Relativized approximation complexity Mayordomo2025
  • Definition 5: Relativized finite-state dimension and $f$-normality Mayordomo2025
  • Definition 6: Best approximation from below Mayordomo2025
  • Lemma 1
  • proof
  • Lemma 2
  • proof
  • ...and 26 more