Image Computation for Quantum Transition Systems
Fuente:
arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866909527380590592 |
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| author | Hong, Xin Gao, Dingchao Li, Sanjiang Ying, Shenggang Ying, Mingsheng |
| author_facet | Hong, Xin Gao, Dingchao Li, Sanjiang Ying, Shenggang Ying, Mingsheng |
| contents | With the rapid progress in quantum hardware and software, the need for verification of quantum systems becomes increasingly crucial. While model checking is a dominant and very successful technique for verifying classical systems, its application to quantum systems is still an underdeveloped research area. This paper advances the development of model checking quantum systems by providing efficient image computation algorithms for quantum transition systems, which play a fundamental role in model checking. In our approach, we represent quantum circuits as tensor networks and design algorithms by leveraging the properties of tensor networks and tensor decision diagrams. Our experiments demonstrate that our contraction partition-based algorithm can greatly improve the efficiency of image computation for quantum transition systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_04146 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Image Computation for Quantum Transition Systems Hong, Xin Gao, Dingchao Li, Sanjiang Ying, Shenggang Ying, Mingsheng Data Structures and Algorithms Emerging Technologies Quantum Physics With the rapid progress in quantum hardware and software, the need for verification of quantum systems becomes increasingly crucial. While model checking is a dominant and very successful technique for verifying classical systems, its application to quantum systems is still an underdeveloped research area. This paper advances the development of model checking quantum systems by providing efficient image computation algorithms for quantum transition systems, which play a fundamental role in model checking. In our approach, we represent quantum circuits as tensor networks and design algorithms by leveraging the properties of tensor networks and tensor decision diagrams. Our experiments demonstrate that our contraction partition-based algorithm can greatly improve the efficiency of image computation for quantum transition systems. |
| title | Image Computation for Quantum Transition Systems |
| topic | Data Structures and Algorithms Emerging Technologies Quantum Physics |
| url | https://arxiv.org/abs/2503.04146 |