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March 5, 20260 citationsOpen Access

A Stable Captured-Share Plateau in Random Operator Mapping

TMTR Mills

Key Points

  • The research aims to explore how covariance affects mapping within random operator ensembles.
  • Investigated random operator ensembles using GOE, GUE, and Bernoulli matrices.
  • Conducted high-resolution mapping with N = 128.
  • Utilized a Google Colab notebook and Python scripts for reproducibility.
  • Analyzed gate thresholds and captured-share statistics.
  • Demonstrated a stable captured-share plateau across the studied ensembles.
  • Provided comprehensive comparisons between different random operator mappings.
  • Included high-resolution figures and supplementary configuration notes.

Abstract

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 (mapping₀69ₑxperiments. ipynb) A flattened Python script for offline execution (mapping₀69ₑxperiments. 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.

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Cite This Study

TR Mills (2026) studied this question.

synapsesocial.com/papers/69a91dc3d6127c7a504c0e23https://doi.org/10.5281/zenodo.18843935
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