基于贝叶斯模型的QCA扇出结构转换特性

Switching Characteristics of the QCA Fanout Structure Based on the Bayesian Model

基于半径为2的贝叶斯模型,量化分析了量子元胞自动机(QCA)扇出结构的转换特性。分析表明,采用半径为1的贝叶斯模型进行QCA转换特性分析将导致传输线正确概率的误差增大到40%,而半径为2的贝叶斯模型平衡了运算量和计算精度,适用于QCA的可靠性分析。仿真表明,扇出结构的正确概率随元胞尺寸和元胞间距的增大而逐渐降低,也随着输入条件和输出端的不同而改变,输入为‘1’时,扇出的拐角输出端的正确概率高于85%,而输入为‘0’时,拐角输出端的正确概率低于20%。这是由于QCA是一种基于量子机理进行工作的器件,不同的输入或不同的元胞尺寸和元胞间距都将造成元胞扭结能的改变,进而影响元胞的翻转概率。研究所得结论可为今后QCA的电路实现与设计和可靠性分析提供参考。

Abstract： The switching characteristics of the quantum-dot cellular automata （QCA） fanout structure were quantifiably analyzed based on the Bayesian model with the radius of 2. The analy- sis reveals that the error of the wire correct probability will increase to 40% by the Bayesian model with the radius of 1 to implement the switching characteristic analysis of the QCA. The Bayesian model with the radius of 2 balances the operation quantity and computation precision, and is an appropriate method to analyze the QCA reliability. The simulation results show that the correct probability of the fanout structure gradually decreases with the increase of the cell size and cell distance, and also changes with the different input conditions and output terminals. The correct probability of the corner output terminal is more than 85 % when the input is ＇ 1 % , while it is less than 20% when the input is ＇0＇. This is because the QCA is a device based on the quantum mechanism. Different inputs or cell sizes and cell distances will change the kink energy of the cell, thereby affecting the switching probability of the cell. The research conclusion provides a reference for the circuit implementation, design and reliability analysis of the future QCA.