Abstract
Finding a minimum is an essential part of mathematical models, and it plays an important role in some optimization problems. Durr and Hoyer proposed a quantum searching algorithm (DHA), with a certain probability of success, to achieve quadratic speed than classical ones. In this paper, we propose an optimized quantum minimum searching algorithm with sure-success probability, which utilizes Grover-Long searching to implement the optimal exact searching, and the dynamic strategy to reduce the iterations of our algorithm. Besides, we optimize the oracle circuit to reduce the number of gates by the simplified rules. The performance evaluation including the theoretical success rate and computational complexity shows that our algorithm has higher accuracy and efficiency than DHA algorithm. Finally, a simulation experiment based on Cirq is performed to verify its feasibility.
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Acknowledgements
The authors would like to express heartfelt gratitude to the anonymous reviewers and editor for their comments that improved the quality of this paper. This work was supported by the Natural Science Foundation of China under Grant Nos. 62071240 and 61802002, the Natural Science Foundation of Jiangsu Higher Education Institutions of China under Grant No. 19KJB520028, the Graduate Research and Innovation Projects of Jiangsu Province under Grant No. KYCX20_0978, the Jiangsu Students’ Platform for Innovation and Entrepreneurship Training Program under Grant No. 201910300140Y, and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).
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Liu, W., Wu, Q., Shen, J. et al. An optimized quantum minimum searching algorithm with sure-success probability and its experiment simulation with Cirq. J Ambient Intell Human Comput 12, 10425–10434 (2021). https://doi.org/10.1007/s12652-020-02840-z
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DOI: https://doi.org/10.1007/s12652-020-02840-z