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Multiperiodic Processes: Ergodic Sources with a Sublinear Entropy

Information Theory 2026-01-21 v5 Machine Learning math.IT Statistics Theory Statistics Theory

Abstract

We construct multiperiodic processes -- a simple example of stationary ergodic (but not mixing) processes over natural numbers that enjoy the vanishing entropy rate under a mild condition. Multiperiodic processes are supported on randomly shifted deterministic sequences called multiperiodic sequences, which can be efficiently generated using an algorithm called the Infinite Clock. Under a suitable parameterization, multiperiodic sequences exhibit relative frequencies of particular numbers given by Zipf's law. Exactly in the same setting, the respective multiperiodic processes satisfy an asymptotic power-law growth of block entropy, called Hilberg's law. Hilberg's law is deemed to hold for statistical language models, in particular.

Keywords

Cite

@article{arxiv.2302.09049,
  title  = {Multiperiodic Processes: Ergodic Sources with a Sublinear Entropy},
  author = {Łukasz Dębowski},
  journal= {arXiv preprint arXiv:2302.09049},
  year   = {2026}
}

Comments

30 pages; 1 figure

R2 v1 2026-06-28T08:43:00.648Z