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基于置换群的多粒子环上量子漫步的反馈搜索算法

姜瑶瑶 张文彬 初鹏程 马鸿洋

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基于置换群的多粒子环上量子漫步的反馈搜索算法

姜瑶瑶, 张文彬, 初鹏程, 马鸿洋

Feedback search algorithm for multi-particle quantum walks over a ring based on permutation groups

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  • 在量子计算科学中关于如何更好地构建量子搜索算法一直以来受到学者们的广泛关注, 并且基于量子漫步寻找新得搜索算法也仍吸引着学者们不断深入研究与探索. 本文正是从减少搜索过程中的时间消耗, 增加算法搜索的准确性和可控性等多方面进行考虑,提出了一种基于置换群的多粒子量子漫步搜索算法. 本文首先分析得到置换群在空间中可看成一个闭环,定义了置换集合,并且通过同构映 射将数据点所在数据集映射到定义的置换集,使得置换集合中元素数据点形成一一对应的关系. 其次,根据给定初始态和硬币算符,在数据点集与置换集合张成的搜索空间中利用多粒子的量子漫步 在环上进行目标数据搜索. 最后,根据函数$\varPhi(w)=1$找到目标数据,并用量子态存储数值,用于形成搜索算法的反馈控制;同时通过控制硬币算符从而控制量子漫步在环上行走方向,增加搜索的可操作性与准确性. 本文利用多粒子的量子漫步进行搜索,分析得到粒子数量参数j与时间复杂度呈非线性负相关;提出的量子漫步搜索算法符合零点条件与下确界条件, 且不受变量参数$ j $的影响;通过数值分析得到量子漫步搜索算法的时间复杂度等价于$\circ(\sqrt[3]{N})$,相比于Grover搜索算法提高了搜索效率.
    In quantum computing science, researchers have paid much attention to how to construct quantum search algorithms better, moreover, searching for new search algorithms based on quantum walk is still attracting scholars' continuous in-depth research and exploration. In this paper, a multi-particle quantum walk search algorithm based on permutation group is proposed from many aspects, such as reducing time consumption and increasing the accuracy and controllability of algorithm search. Firstly, the permutation group can be regarded as a closed loop in space, and the permutation set is defined. The data set of data points is mapped to the defined permutation set by isomorphism mapping, which makes the element data points in the permutation set form a one-to-one correspondence. Secondly, according to the given initial state and coin operator, the target data search is carried out on the ring by using the quantum walk of multiple particles in the search space of the data point set and the permutation set.Finally, the target data is found according to the function $\varPhi(w)=1 $, and the value is stored by the quantum state, which is used to form the feedback control of the search algorithm.At the same time, the direction of quantum walking on the ring is controlled by controlling the coin operator to increase the operability and accuracy of the search.In this paper, the quantum walk of multiple particles is used to search, and the analysis shows that the particle number parameter $j $ is negatively correlated with the time complexity, but not negatively linear. The proposed quantum walk search algorithm conforms to the zero condition and the lower bound condition, and is not affected by the variable parameter $j $.Through numerical analysis, it is found that the time complexity of the quantum walk search algorithm is equivalent to $\circ(\sqrt[3]{N})$, which improves the search efficiency compared with the Grover search algorithm.
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  • 被引次数: 0
出版历程
  • 收稿日期:  2021-05-27
  • 上网日期:  2021-10-22

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