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2026
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| Online Access: | https://doi.org/10.5281/zenodo.18897853 |
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| _version_ | 1866901779659096064 |
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| author | Kai Huang |
| author_facet | Kai Huang |
| contents | <h2>Overview</h2> <p>This initial release provides the first comprehensive experimental and simulated validation of the <strong>Retrodiction Landauer Principle</strong> ($F \geq e^{-\Sigma/2}$) in the context of quantum error correction.</p> <h2>Key Contents</h2> <ul> <li><strong>Hardware Benchmarking:</strong> 100% satisfaction of the predicted bound across 1,020 data points from IBM (Brisbane, Sherbrooke, Torino) and Google (Sycamore, Willow) quantum processors.</li> <li><strong>Decoder Hierarchy Analysis:</strong> Verification of the 36/36 performance match across MWPM, Unweighted MWPM, and Greedy decoders using Google's <code>stim</code> simulator.</li> <li><strong>Thermodynamic Filtering:</strong> Confirmation of post-selection scaling ($\ln R = \alpha \cdot d + \beta$) across independent experimental datasets.</li> <li><strong>Optimal Recovery Proof:</strong> Theoretical and numerical evidence showing the Petz recovery map achieves the highest fidelity among all retrodiction-consistent maps.</li> </ul> <h2>Limitations & Scope</h2> <p>Note that $F$ and $\Sigma$ were computed from reported channel parameters rather than simultaneous direct measurements. This version focuses on the stationary-Petz-recovery regime for Markovian and non-Markovian noise.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18897853 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | akaiHuang/petz-recovery-unification: v0.0.9: Petz Recovery Unification - The Quantum Thermodynamic Bound Kai Huang <h2>Overview</h2> <p>This initial release provides the first comprehensive experimental and simulated validation of the <strong>Retrodiction Landauer Principle</strong> ($F \geq e^{-\Sigma/2}$) in the context of quantum error correction.</p> <h2>Key Contents</h2> <ul> <li><strong>Hardware Benchmarking:</strong> 100% satisfaction of the predicted bound across 1,020 data points from IBM (Brisbane, Sherbrooke, Torino) and Google (Sycamore, Willow) quantum processors.</li> <li><strong>Decoder Hierarchy Analysis:</strong> Verification of the 36/36 performance match across MWPM, Unweighted MWPM, and Greedy decoders using Google's <code>stim</code> simulator.</li> <li><strong>Thermodynamic Filtering:</strong> Confirmation of post-selection scaling ($\ln R = \alpha \cdot d + \beta$) across independent experimental datasets.</li> <li><strong>Optimal Recovery Proof:</strong> Theoretical and numerical evidence showing the Petz recovery map achieves the highest fidelity among all retrodiction-consistent maps.</li> </ul> <h2>Limitations & Scope</h2> <p>Note that $F$ and $\Sigma$ were computed from reported channel parameters rather than simultaneous direct measurements. This version focuses on the stationary-Petz-recovery regime for Markovian and non-Markovian noise.</p> |
| title | akaiHuang/petz-recovery-unification: v0.0.9: Petz Recovery Unification - The Quantum Thermodynamic Bound |
| url | https://doi.org/10.5281/zenodo.18897853 |