Quantum Program Analysis and Optimization

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.

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Publication Details

Journal
IEEE Nanotechnology Magazine
Published
2025-04-07
DOI
https://doi.org/10.1109/mnano.2025.3551388
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
0.00
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article

Quantum Program Analysis and Optimization

Chia-Heng Tu, Shih‐Hao Hung, Yu-Tsung Wu, Po-Hsuan Huang et al.
IEEE Nanotechnology Magazine
Quantum Computing Algorithms and Architecture
article

Quantum Program Analysis and Optimization

Chia-Heng Tu, Shih‐Hao Hung, Yu-Tsung Wu, Po-Hsuan Huang, Kai‐Chieh Chang, Yue Wu
article en

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.

IEEE Nanotechnology MagazineVol. 19(3)
National Taiwan University (TW), National Cheng Kung University (TW)
Openalex Percentile: Top 97%
Quantum Computing Algorithms and Architecture
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