Quantum computing, albeit readily available as hardware or emulated on the cloud, is still far from being available in general regarding complex programming paradigms and learning curves. This vision paper introduces Classi|Q〉, a translation framework idea to bridge Classical and Quantum Computing by translating high-level programming languages, e.g., Python or C++, into a low-level language, e.g., Quantum Assembly. Our idea paper serves as a blueprint for ongoing efforts in quantum software engineering, offering a roadmap for further Classi|Q〉 development to meet the diverse needs of researchers and practitioners. Classi|Q〉 is designed to empower researchers and practitioners with no prior quantum experience to harness the potential of hybrid quantum computation. We also discuss future enhancements to Classi|Q〉, including support for additional quantum languages, improved optimization strategies, and integration with emerging quantum computing platforms.
Esposito, M., Tavassoli Sabzevari, M., Ye, B., Falessi, D., Ali Khan, A., Taibi, D. (2024). 𝐶𝑙𝑎𝑠𝑠𝑖|𝑄⟩: Towards a Translation Framework to Bridge the Classical-Quantum Programming Gap. In QSE-NE 2024 - Proceedings of the 1st ACM International Workshop on Quantum Software Engineering: The Next Evolution, Co-located with: ESEC/FSE 2024 (pp.11-14). 1601 Broadway, 10th Floor, NEW YORK, NY, UNITED STATES : Association for Computing Machinery, Inc [10.1145/3663531.3664752].
𝐶𝑙𝑎𝑠𝑠𝑖|𝑄⟩: Towards a Translation Framework to Bridge the Classical-Quantum Programming Gap
Matteo Esposito;Davide Falessi;
2024-01-01
Abstract
Quantum computing, albeit readily available as hardware or emulated on the cloud, is still far from being available in general regarding complex programming paradigms and learning curves. This vision paper introduces Classi|Q〉, a translation framework idea to bridge Classical and Quantum Computing by translating high-level programming languages, e.g., Python or C++, into a low-level language, e.g., Quantum Assembly. Our idea paper serves as a blueprint for ongoing efforts in quantum software engineering, offering a roadmap for further Classi|Q〉 development to meet the diverse needs of researchers and practitioners. Classi|Q〉 is designed to empower researchers and practitioners with no prior quantum experience to harness the potential of hybrid quantum computation. We also discuss future enhancements to Classi|Q〉, including support for additional quantum languages, improved optimization strategies, and integration with emerging quantum computing platforms.File | Dimensione | Formato | |
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