Simulation-Free Fidelity Estimation via Quantum Output Order Statistics
Fuente:
arXiv
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866914093703626752 |
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| author | Micklitz, Tobias |
| author_facet | Micklitz, Tobias |
| contents | We introduce a simulation-free method to estimate the fidelity of large quantum circuits based on the order statistics of measured output probabilities from highly entangled, chaotic states. The approach requires only the highest-probability output bitstrings -- the most frequently observed measurement outcomes -- and builds on exact analytical results for the order statistics of Haar-random quantum states derived here. Analyzing their modification under depolarizing noise, we propose a scalable fidelity estimator, validated on Google's 12-qubit Sycamore experiment and further supported by numerical simulations. We demonstrate its practicality for intermediate-scale quantum circuits, where cross-entropy benchmarking is costly and direct fidelity estimation is difficult. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_13026 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Simulation-Free Fidelity Estimation via Quantum Output Order Statistics Micklitz, Tobias Quantum Physics Disordered Systems and Neural Networks We introduce a simulation-free method to estimate the fidelity of large quantum circuits based on the order statistics of measured output probabilities from highly entangled, chaotic states. The approach requires only the highest-probability output bitstrings -- the most frequently observed measurement outcomes -- and builds on exact analytical results for the order statistics of Haar-random quantum states derived here. Analyzing their modification under depolarizing noise, we propose a scalable fidelity estimator, validated on Google's 12-qubit Sycamore experiment and further supported by numerical simulations. We demonstrate its practicality for intermediate-scale quantum circuits, where cross-entropy benchmarking is costly and direct fidelity estimation is difficult. |
| title | Simulation-Free Fidelity Estimation via Quantum Output Order Statistics |
| topic | Quantum Physics Disordered Systems and Neural Networks |
| url | https://arxiv.org/abs/2510.13026 |