【摘要】 在使用Grover量子搜索算法对给定规模的无序数据库搜索时,随着搜索目标数的增加,获得正确结果的概率大幅度下降。分析了出现这种现象的原因,研究了算法中的Grover叠代过程,提出了一种新的自适应相位旋转策略。应用这一策略,当搜索目标数超过目标总数的(3-5^1/2)/8时,只需两步搜索;当搜索目标数超过目标总数的1/4时,只需一步搜索,即可获得恒等于1的成功概率。实验表明新相位旋转策略是有效的。更多还原

【Abstract】 When the Grover’s algorithm is applied to search an unordered database, the success probability usually decreases with the increase of marked items. The reason for this phenomenon was analyzed, the Grover iteration was studied, and a new adaptive phase rotation was proposed. With application of the new phase rotation, when the fraction of marked items is a rational number in range (3-5^1/2) / 8to 1/4, the success probability is equal to 1 after two Grover iterations; and when the fraction of marked items is greater than1/4, the success probability is equal to 1 after the only one Grover iteration. The effectiveness of the new phase rotation is verified by a search example.更多还原