A Stable Captured-Share Plateau in Random Operator Mapping
This deposit contains the full preprint and reproducibility materials for the paper “A Stable Captured-Share Plateau in Random Operator Mapping.” The work investigates covariance-induced mapping in random operator ensembles and demonstrates a stable captured-share plateau across GOE, GUE, and Bernoulli matrices, including a high-resolution N = 128 deep run. The repository includes: The complete manuscript (PDF) The Google Colab notebook used for all experiments (mapping_069_experiments.ipynb) A flattened Python script for offline execution (mapping_069_experiments.py) High-resolution figures used in the paper Supplemental configuration notes and reproducibility details All experiments are fully reproducible by running the notebook from top to bottom. The results include gate thresholds, captured-share statistics, ensemble comparisons, and the Random-Q surrogate baseline. The OSF companion archive contains the same materials with version tracking. This Zenodo release serves as the permanent DOI-linked record for citation, review, and future journal submission.
Authors
- TR Mills
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-03-03
- DOI
- https://doi.org/10.5281/zenodo.18843934
- Primary Topic
- Advanced Neuroimaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00