Zeno Blockade Photonic Quantum Optimization: Simulation Code and Data

Code and data associated with the arXiv paper 'Zeno Blockade Enabling Photonic Quantum Optimization' by Mohammad-Ali Miri, Uchenna Chukwu, and Nicholas Chancellor. The repository contains Python code and pre-computed numerical data for generating plots on quantum optics simulations and Zeno blockade effects. The data was last updated on 2026-04 14 and is licensed under Apache 2.0.

Use Cases

• Reproducing plots for quantum optics simulations based on the provided Jupyter notebook and modules.
• Analyzing success probability versus cycle number for various coherent levels using the saved .npy data.
• Studying the approach to Markovianity in a Zeno blockade system based on the included loss level data.
• Extending state-vector or density matrix quantum optics simulations using the provided custom Python modules.

Strengths

• Includes pre-computed numerical data (.npy files) for simulations that take over 24 hours to run on a consumer laptop.
• Code is fully provided to regenerate all data and plots, licensed under the permissive Apache 2.0 license.
• Repository contains three custom Python modules for quantum optics simulation, density matrix extension, and computing constructions.

Limitations

• Row count and column-level documentation are unknown; data structure must be inferred after download.
• The dataset is small (3.5 MB) and primarily contains code and numerical arrays, not a large-scale data corpus.

Provenance

Source

figshare repository associated with an arXiv paper by authors from Quantum Computing Inc.

Collection Method

Numerical simulation outputs from quantum optics models, generated by the provided Python code.

Time Range

Associated with research published on arXiv in 2026.

Freshness

Last updated 2026-04-14 15:30:28.

Geography

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