Quantum Program Analysis and Optimization
Huang, Po-Hsuan Wu, Yu-Hui Wu, Yu-Tsung Chang, Kai-Chieh Tu, Chia-Heng Hung, Shih-Hao
Huang, Po-Hsuan
Wu, Yu-Hui
Wu, Yu-Tsung
Chang, Kai-Chieh
Tu, Chia-Heng
Hung, Shih-Hao
Supervisor
Department
Computer Science
Embargo End Date
Type
Journal article
Date
2025
License
Language
English
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Abstract
Quantum computing has the potential to tackle complex problems that are intractable for classical computers, thanks to its unique properties, such as superposition and entanglement. Nevertheless, developing efficient quantum programs remains challenging because of the diversity and rapid evolution of hardware, and limited access to quantum devices. To tackle these issues, we propose an open-source, profile-guided development flow that allows programmers to refine and optimize quantum code using quantum circuit simulators to evaluate program performance without the need for physical quantum hardware. In the proposed flow, the performance data collected in previous simulation runs helps guide compiler optimizations to generate efficient quantum circuits. An integrated visualization tool further aids programmers by associating performance data with the quantum program code, making it easier to pinpoint code regions for potential improvement. This development flow offers a practical path toward the development of novel and efficient quantum algorithms for various quantum computing platforms.
Citation
P.-H. Huang, Y.-H. Wu, Y.-T. Wu, K.-C. Chang, C.-H. Tu, and S.-H. Hung, “Quantum Program Analysis and Optimization,” IEEE Nanotechnol Mag, pp. 1–12, 2025, doi: 10.1109/MNANO.2025.3551388.
Source
IEEE Nanotechnology Magazine
Conference
Keywords
Quantum computing, Logic gates, Quantum circuit, Qubit, Hardware, Quantum algorithm, Computers, Optimization, Codes, Circuits
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Source
Publisher
IEEE