Agafonov's Theorem for finite and infinite alphabets and probability distributions different from equidistribution
Thomas Seiller, Jakob Grue Simonsen

TL;DR
This paper characterizes when finite-state selection preserves distributional properties of sequences over finite and infinite alphabets, showing it holds precisely for Bernoulli distributions, thus generalizing Agafonov's Theorem.
Contribution
It provides a complete characterization of probability maps for which finite-state selection preserves $ ext{μ}$-distributedness, extending Agafonov's Theorem to Bernoulli distributions on infinite alphabets.
Findings
Finite-state selectors preserve $ ext{μ}$-distributedness iff $ ext{μ}$ is Bernoulli.
Agafonov's Theorem generalizes to Bernoulli distributions on infinite alphabets.
Shift-invariant measures preserving genericity are exactly positive Bernoulli measures.
Abstract
An infinite sequence over an alphabet is -distributed w.r.t. a probability map if, for every finite string , the limiting frequency of in exists and equals . %We raise the question of how to characterize the probability maps for which -distributedness is preserved across finite-state selection, or equivalently, by selection by programs using constant space. We prove the following result for any finite or countably infinite alphabet : every finite-state selector over selects a -distributed sequence from every -distributed sequence \emph{if and only if} is induced by a Bernoulli distribution on , that is a probability distribution on the alphabet extended to words by taking the product. The primary -- and remarkable -- consequence of our main result is a complete characterization of…
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Taxonomy
TopicsComputability, Logic, AI Algorithms · semigroups and automata theory · Algorithms and Data Compression
