中国物理B ›› 2015, Vol. 24 ›› Issue (11): 110309-110309.doi: 10.1088/1674-1056/24/11/110309

• GENERAL • 上一篇    下一篇

Optimized quantum random-walk search algorithm for multi-solution search

张宇超a b, 鲍皖苏a b, 汪翔a b, 付向群a b   

  1. a Zhengzhou Information Science and Technology Institute, Zhengzhou 450004, China;
    b Synergetic Innovation Center of Quantum Information and Quantum Physics, University of Science and Technology of China, Hefei 230026, China
  • 收稿日期:2015-07-11 修回日期:2015-10-10 出版日期:2015-11-05 发布日期:2015-11-05
  • 通讯作者: Bao Wan-Su E-mail:2010thzz@sina.com
  • 基金资助:
    Project supported by the National Basic Research Program of China (Grant No. 2013CB338002).

Optimized quantum random-walk search algorithm for multi-solution search

Zhang Yu-Chao (张宇超)a b, Bao Wan-Su (鲍皖苏)a b, Wang Xiang (汪翔)a b, Fu Xiang-Qun (付向群)a b   

  1. a Zhengzhou Information Science and Technology Institute, Zhengzhou 450004, China;
    b Synergetic Innovation Center of Quantum Information and Quantum Physics, University of Science and Technology of China, Hefei 230026, China
  • Received:2015-07-11 Revised:2015-10-10 Online:2015-11-05 Published:2015-11-05
  • Contact: Bao Wan-Su E-mail:2010thzz@sina.com
  • Supported by:
    Project supported by the National Basic Research Program of China (Grant No. 2013CB338002).

摘要: This study investigates the multi-solution search of the optimized quantum random-walk search algorithm on the hypercube. Through generalizing the abstract search algorithm which is a general tool for analyzing the search on the graph to the multi-solution case, it can be applied to analyze the multi-solution case of quantum random-walk search on the graph directly. Thus, the computational complexity of the optimized quantum random-walk search algorithm for the multi-solution search is obtained. Through numerical simulations and analysis, we obtain a critical value of the proportion of solutions q. For a given q, we derive the relationship between the success rate of the algorithm and the number of iterations when q is no longer than the critical value.

关键词: quantum search algorithm, quantum random walk, multi-solution, abstract search algorithm

Abstract: This study investigates the multi-solution search of the optimized quantum random-walk search algorithm on the hypercube. Through generalizing the abstract search algorithm which is a general tool for analyzing the search on the graph to the multi-solution case, it can be applied to analyze the multi-solution case of quantum random-walk search on the graph directly. Thus, the computational complexity of the optimized quantum random-walk search algorithm for the multi-solution search is obtained. Through numerical simulations and analysis, we obtain a critical value of the proportion of solutions q. For a given q, we derive the relationship between the success rate of the algorithm and the number of iterations when q is no longer than the critical value.

Key words: quantum search algorithm, quantum random walk, multi-solution, abstract search algorithm

中图分类号:  (Quantum computation architectures and implementations)

  • 03.67.Lx
03.67.Ac (Quantum algorithms, protocols, and simulations)