Benchmarking Quantum Coprocessors in an Application-Centric, Hardware-Agnostic, and Scalable Way
Existing protocols for benchmarking current quantum coprocessors fail to meet the usual standards for assessing the performance of high-performance-computing platforms. After a synthetic review of these protocols—whether at the gate, circuit, or application level—we introduce a...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Transactions on Quantum Engineering |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9459509/ |
| _version_ | 1798032759299506176 |
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| author | Simon Martiel Thomas Ayral Cyril Allouche |
| author_facet | Simon Martiel Thomas Ayral Cyril Allouche |
| author_sort | Simon Martiel |
| collection | DOAJ |
| description | Existing protocols for benchmarking current quantum coprocessors fail to meet the usual standards for assessing the performance of high-performance-computing platforms. After a synthetic review of these protocols—whether at the gate, circuit, or application level—we introduce a new benchmark, dubbed Atos Q-score, which is application-centric, hardware-agnostic, and scalable to quantum advantage processor sizes and beyond. The Q-score measures the maximum number of qubits that can be used <italic>effectively</italic> to solve the MaxCut combinatorial optimization problem with the quantum approximate optimization algorithm. We give a robust definition of the notion of effective performance by introducing an improved approximation ratio based on the scaling of random and optimal algorithms. We illustrate the behavior of Q-score using perfect and noisy simulations of quantum processors. Finally, we provide an open-source implementation of Q-score that makes it easy to compute the Q-score of any quantum hardware. |
| first_indexed | 2024-04-11T20:19:13Z |
| format | Article |
| id | doaj.art-4c051334d7b446dfb61e6e8979819554 |
| institution | Directory Open Access Journal |
| issn | 2689-1808 |
| language | English |
| last_indexed | 2024-04-11T20:19:13Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Transactions on Quantum Engineering |
| spelling | doaj.art-4c051334d7b446dfb61e6e89798195542022-12-22T04:04:53ZengIEEEIEEE Transactions on Quantum Engineering2689-18082021-01-01211110.1109/TQE.2021.30902079459509Benchmarking Quantum Coprocessors in an Application-Centric, Hardware-Agnostic, and Scalable WaySimon Martiel0Thomas Ayral1https://orcid.org/0000-0003-0960-4065Cyril Allouche2Atos Quantum Laboratory, Les Clayes-sous-Bois, FranceAtos Quantum Laboratory, Les Clayes-sous-Bois, FranceAtos Quantum Laboratory, Les Clayes-sous-Bois, FranceExisting protocols for benchmarking current quantum coprocessors fail to meet the usual standards for assessing the performance of high-performance-computing platforms. After a synthetic review of these protocols—whether at the gate, circuit, or application level—we introduce a new benchmark, dubbed Atos Q-score, which is application-centric, hardware-agnostic, and scalable to quantum advantage processor sizes and beyond. The Q-score measures the maximum number of qubits that can be used <italic>effectively</italic> to solve the MaxCut combinatorial optimization problem with the quantum approximate optimization algorithm. We give a robust definition of the notion of effective performance by introducing an improved approximation ratio based on the scaling of random and optimal algorithms. We illustrate the behavior of Q-score using perfect and noisy simulations of quantum processors. Finally, we provide an open-source implementation of Q-score that makes it easy to compute the Q-score of any quantum hardware.https://ieeexplore.ieee.org/document/9459509/Combinatorial optimizationquantum algorithmsquantum benchmarking |
| spellingShingle | Simon Martiel Thomas Ayral Cyril Allouche Benchmarking Quantum Coprocessors in an Application-Centric, Hardware-Agnostic, and Scalable Way IEEE Transactions on Quantum Engineering Combinatorial optimization quantum algorithms quantum benchmarking |
| title | Benchmarking Quantum Coprocessors in an Application-Centric, Hardware-Agnostic, and Scalable Way |
| title_full | Benchmarking Quantum Coprocessors in an Application-Centric, Hardware-Agnostic, and Scalable Way |
| title_fullStr | Benchmarking Quantum Coprocessors in an Application-Centric, Hardware-Agnostic, and Scalable Way |
| title_full_unstemmed | Benchmarking Quantum Coprocessors in an Application-Centric, Hardware-Agnostic, and Scalable Way |
| title_short | Benchmarking Quantum Coprocessors in an Application-Centric, Hardware-Agnostic, and Scalable Way |
| title_sort | benchmarking quantum coprocessors in an application centric hardware agnostic and scalable way |
| topic | Combinatorial optimization quantum algorithms quantum benchmarking |
| url | https://ieeexplore.ieee.org/document/9459509/ |
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