量子模式识别中的相变
Phase Transitions in Quantum Pattern Recognition
摘要：
借助于量子力学，人们可以建立一个具有最佳存储容量的联想记忆模型。我通过引入一个起有效温度作用的参数来推广这个模型。相应的热力学提供了调整量子模式识别效率的标准。我表明，联想记忆经历了一个相变从无序的高温阶段，没有输入和输出之间的相关性，以一个有序的，低温阶段，最小的输入-输出汉明距离。
英文摘要：
With the help of quantum mechanics one can formulate a model of associative memory with optimal storage capacity. I generalize this model by introducing a parameter playing the role of an effective temperature. The corresponding thermodynamics provides criteria to tune the efficiency of quantum pattern recognition. I show that the associative memory undergoes a phase transition from a disordered high-temperature phase with no correlation between input and output to an ordered, low-temperature phase with minimal input-output Hamming distance.
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