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Numerical Notebook and Data for "Eigenbasis Conditioning and Fisher-Information Singularity Classes Near a Second-Order Exceptional Point"

Markus, Olga

Published Jul 17, 2026• 0 citations
Publisher

Abstract

This repository contains the complete Python notebook and numerically generated data supporting Sections 7.1–7.5 and Figs. 1–3 of the accompanying article, “Eigenbasis Conditioning and Fisher-Information Singularity Classes Near a Second-Order Exceptional Point.” The archive includes the exact canonical EP2 benchmark, a reproducible ensemble of 300 noncanonical continuous complex operator paths, the Bernoulli Fisher-information readout models, the relative Fisher–conditioning analysis, and the numerical precision, unitary-invariance, and nonunitary-similarity tests. The repository contains the complete ensemble-generation parameters, recorded pseudorandom seeds, processed numerical data, software-environment specifications, and files underlying the reported figures. All data in the archive are numerically generated. The notebook code is released under the MIT License. The generated numerical data, figures, and documentation are released under the Creative Commons Attribution 4.0 International License.

DOI
10.5281/zenodo.21431444

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This repository contains the numerical data and computational codes supporting the results presented in the manuscript: "Engineered non-Gaussian Coherence as a Thermodynamic Resource for Quantum Batteries". The archive (data_QB.zip) includes all datasets, Jupyter notebooks, and figure files required to reproduce the results reported in both the main text and the Supplemental Material. Each figure is organised in a separate directory containing the corresponding data (.txt), code (.ipynb), and generated plots (.png/.pdf). The provided materials are sufficient to reproduce all figures and results without restriction. Detailed instructions and directory structure are described in the accompanying README.txt file. This dataset is made openly available to ensure transparency and reproducibility of the reported results.
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