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| Format: | Recurso digital |
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Zenodo
2026
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| Online Access: | https://doi.org/10.5281/zenodo.18306335 |
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Table of Contents:
- <p>This archive contains the full reproducibility package for the manuscript:</p> <p> </p> <p>Information-Theoretic Surrogate Testing of Normalized Prime Gaps: Mutual and Conditional Mutual Information Under IAAFT Nulls (Angelina Hintsanen, NEXUS AI Lab).</p> <p> </p> <p>The package includes Python scripts, configuration metadata, CSV outputs, and publication-quality figures for three experiment phases:</p> <p> </p> <ul> <li>Phase B1: Mutual information (MI) lag sweep on normalized prime gaps with IAAFT surrogate hypothesis testing</li> <li>Phase B2: MI surrogate testing on four control sequences (null validation suite)</li> <li>Phase B3: Conditional mutual information (CMI) lag sweep with growing-conditioning structure test</li> </ul> <p> </p> <p> </p> <p>All outputs are provided as produced by the pipeline: per-lag result tables, run metadata JSON, and PNG/PDF plots. The archive is designed for independent replication and extension.</p> <p> </p> <p>Contents</p> <p> </p> <ul> <li>PrimeGap_PhaseB1_MI_* (results + metadata + figures)</li> <li>PrimeGap_PhaseB2_controls_* (controls + summary tables + figures)</li> <li>PrimeGap_PhaseB3_CMI_* (results + metadata + figures)</li> </ul> <p>prime gaps, primes, information theory, mutual information, conditional mutual information, surrogate data, IAAFT, nonlinear dependence, computational number theory, experimental mathematics, kNN estimator, KSG estimator, Frenzel-Pompe</p>