$Classi|Q\rangle$ Towards a Translation Framework To Bridge The Classical-Quantum Programming Gap
Esposito, Matteo, Sabzevari, Maryam Tavassoli, Ye, Boshuai, Falessi, Davide, Khan, Arif Ali, Taibi, Davide
–arXiv.org Artificial Intelligence
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 $Classi|Q\rangle$, 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 $Classi|Q\rangle$ development to meet the diverse needs of researchers and practitioners. $Classi|Q\rangle$ 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 $Classi|Q\rangle$, including support for additional quantum languages, improved optimization strategies, and integration with emerging quantum computing platforms.
arXiv.org Artificial Intelligence
Jul-1-2024
- Country:
- Europe
- North America > United States (0.14)
- Genre:
- Research Report (0.50)
- Technology:
- Information Technology
- Artificial Intelligence
- Machine Learning (1.00)
- Representation & Reasoning (0.94)
- Hardware (1.00)
- Software > Programming Languages (1.00)
- Artificial Intelligence
- Information Technology