A comparison on constrain encoding methods for quantum approximate optimization algorithm
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866929529961840640 |
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| author | Liu, Yiwen Jiao, Qingyue Zhou, Yidong Liang, Zhiding Shi, Yiyu Wan, Ke Guo, Shangjie |
| author_facet | Liu, Yiwen Jiao, Qingyue Zhou, Yidong Liang, Zhiding Shi, Yiyu Wan, Ke Guo, Shangjie |
| contents | The Quantum Approximate Optimization Algorithm (QAOA) represents a significant opportunity for practical quantum computing applications, particularly in the era before error correction is fully realized. This algorithm is especially relevant for addressing constraint satisfaction problems (CSPs), which are critical in various fields such as supply chain management, energy distribution, and financial modeling. In our study, we conduct a numerical comparison of three different strategies for incorporating linear constraints into QAOA: transforming them into an unconstrained format, introducing penalty dephasing, and utilizing the quantum Zeno effect. We assess the efficiency and effectiveness of these methods using the knapsack problem as a case study. Our findings provide insights into the potential applicability of different encoding methods for various use cases. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_04030 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A comparison on constrain encoding methods for quantum approximate optimization algorithm Liu, Yiwen Jiao, Qingyue Zhou, Yidong Liang, Zhiding Shi, Yiyu Wan, Ke Guo, Shangjie Quantum Physics Optimization and Control The Quantum Approximate Optimization Algorithm (QAOA) represents a significant opportunity for practical quantum computing applications, particularly in the era before error correction is fully realized. This algorithm is especially relevant for addressing constraint satisfaction problems (CSPs), which are critical in various fields such as supply chain management, energy distribution, and financial modeling. In our study, we conduct a numerical comparison of three different strategies for incorporating linear constraints into QAOA: transforming them into an unconstrained format, introducing penalty dephasing, and utilizing the quantum Zeno effect. We assess the efficiency and effectiveness of these methods using the knapsack problem as a case study. Our findings provide insights into the potential applicability of different encoding methods for various use cases. |
| title | A comparison on constrain encoding methods for quantum approximate optimization algorithm |
| topic | Quantum Physics Optimization and Control |
| url | https://arxiv.org/abs/2410.04030 |