节点文献

Grover quantum searching algorithm based on weighted targets

  • 推荐 CAJ下载
  • PDF下载
  • 不支持迅雷等下载工具,请取消加速工具后下载。

【Author】 Li Panchi1,2 & Li Shiyong1 1. Dept. of Control Science and Engineering, Harbin Inst. of Technology, Harbin 150001, P. R. China; 2. Dept. of Computer Science and Engineering, Daqing Petroleum Inst., Daqing 163318, P. R. China

【摘要】 The current Grover quantum searching algorithm cannot identify the difference in importance of the search targets when it is applied to an unsorted quantum database, and the probability for each search target is equal. To solve this problem, a Grover searching algorithm based on weighted targets is proposed. First, each target is endowed a weight coefficient according to its importance. Applying these different weight coefficients, the targets are represented as quantum superposition states. Second, the novel Grover searching algorithm based on the quantum superposition of the weighted targets is constructed. Using this algorithm, the probability of getting each target can be approximated to the corresponding weight coefficient, which shows the flexibility of this algorithm. Finally, the validity of the algorithm is proved by a simple searching example.

【Abstract】 The current Grover quantum searching algorithm cannot identify the difference in importance of the search targets when it is applied to an unsorted quantum database, and the probability for each search target is equal. To solve this problem, a Grover searching algorithm based on weighted targets is proposed. First, each target is endowed a weight coefficient according to its importance. Applying these different weight coefficients, the targets are represented as quantum superposition states. Second, the novel Grover searching algorithm based on the quantum superposition of the weighted targets is constructed. Using this algorithm, the probability of getting each target can be approximated to the corresponding weight coefficient, which shows the flexibility of this algorithm. Finally, the validity of the algorithm is proved by a simple searching example.

【基金】 the National Natural Science Foundation of China (60773065).
  • 【文献出处】 Journal of Systems Engineering and Electronics ,系统工程与电子技术(英文版) , 编辑部邮箱 ,2008年02期
  • 【分类号】TP311.13
  • 【被引频次】6
  • 【下载频次】56
节点文献中: 

本文链接的文献网络图示:

本文的引文网络