Moving prime environments and arithmetic cluster limits
Primarily AI-generated textHuman understanding: no partsmath.PR — Probabilitymath.NT — Number Theory
Contributed by Brice Pouly ↗
Version 1 / Oct 18, 2026 / CC BY 4.0
Abstract
We study shrinking-target occurrences of completely multiplicative functions with arbitrarily moving phases on a fixed finite set of exceptional primes and independent Haar values at the remaining primes. After exact removal of the environment-only points, effective integer-subgroup profiles classify all subsequential marked cluster limits, while target-scale pair overlaps characterize Poisson convergence. The quantitative input is a direct Haar comparison with the moving germ kernel, uniform in the exceptional phases and with stretched-exponential error. For deterministic profiles and interval targets, the complete spatial covariance measure reconstructs the unmarked law through primitive multiplicative rays and finite interval geometry. A positive forest formula makes this reconstruction valid even with unbounded cluster sizes. For a fixed known bounded Borel target, retaining positions and angular marks yields the corresponding identification from the complete marked covariance, using signed overlap channels. Restricting the observation to an interior spatial window imposes both angular and logarithmic-spatial constraints. The maximal number of descendants of one germ becomes a rectangle-occupancy number for a subgroup of R2, finite exactly when that subgroup is discrete. Explicit rank-one laws illustrate what counts forget, while environmental mixtures show why deterministic identification does not extend by averaging covariances.
Provenance statement
The following declaration describes the research and the published source edition:
The research was organized and directed by the author with substantial assistance from GPT-6 Astra (OpenAI), the only language-model system used for this article. Assistance included exploring proof routes, drafting and reorganizing mathematical arguments, writing finite diagnostic programs, checking references, producing the manuscript and conducting adversarial reviews through separate instances. The author determines the claims and scope and accepts responsibility for the arguments, references and remaining errors. AI-assisted checks are not independent human peer review. The mathematical claims rest on the printed arguments and specified external results, not on model output or the success of finite tests.
For this Hexagon deposit, OpenAI Codex assisted source packaging, compilation checks and the preparation of submission metadata. This preparation does not constitute independent mathematical peer review.
The published edition used for this deposit, including its supplementary source material, is available at https://doi.org/10.5281/zenodo.22878806.
At the time of preparation for Hexagon, the submitter declares the text primarily AI-generated and declares that no part of the contribution has been checked and understood by a human.
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Version history
- v1Submitted by Brice PoulyInitial depositCurrentOct 18, 2026