量子纠缠联想记忆  

Quantum associative memory based on entanglement

作　　者：钟艳花[1] 余晓敏[2] 

机构地区：[1]江门职业技术学院计算机系,广东江门529020 [2]暨南大学物理系,广东广州510000

出　　处：《量子电子学报》2005年第6期873-878,共6页Chinese Journal of Quantum Electronics

摘　　要：提出一种基于量子纠缠的联想记忆神经网络(QuEAM)。对比传统的联想记忆网络,QuEAM的 存储容量得到了指数级的增大。学习算法是根据纠缠量度的性质,采用Grover量子迭代算法的基本原理局域放 大量子位(qubit)的概率振幅,相当于传统计算机的按位操作,讨论了这个学习算法下的量子基本原理。最后给 出具体的例子说明了算法的有效性。An approach to constructing an artificial quantum associative memory based on entanglement （QuEAM） is discussed. The QuEAM is an exponential increase in the capacity of the memory when compared to classical associative memories such as the Hopfield network. According to the characteristics of amount of entanglement, the study algorithm based on Grover＇s well-known algorithm is locally magnified the probability amplitude for the qubit. The basic principle of entangled states is discussed. Concrete examples illustrating the properties of the proposed model are also presented.

关 键 词：量子光学 量子计算 量子联想记忆 量子神经计算 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]