基于增强遗传规划方法的可逆逻辑综合

M. Y. Abubakar, Low Tang Jung
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引用次数: 1

摘要

提出了一种新的增强可逆逻辑电路合成方法,该方法使用可逆门,包括NOT, CNOT (Feynman), Toffoli, Fredkin, Swap和Peres门。综合方法采用新发展的遗传规划方法。通常以前的合成方法,使用遗传算法或其他类似的进化算法遭受一个问题,称为blotting,这是一个突然不受控制的增长的个体(电路),这可能使合成效率低下,因为内存的利用,使算法难以继续运行,并最终堆栈在一个局部最小值,有一个优化可逆电路可能无法生成。在这种方法中,使用的算法是无印迹的,通过在种群中固定合适的长度和大小来仔细控制印迹。采用这种方法,大大降低了生成电路的成本,使算法能够到达最后指定代的末端,从而给出最优或接近最优的结果。使用这种方法生成的电路的结果与文献中的一些结果进行了比较,在许多情况下,我们的结果在门数和量子成本指标方面似乎更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Synthesis of Reversible Logic Using Enhanced Genetic Programming Approach
A new enhanced reversible logic circuit synthesis method was developed using reversible gates that include NOT, CNOT (Feynman), Toffoli, Fredkin, Swap, and Peres gates. The synthesis method was done using newly developed genetic programming. Usually previous synthesis methods that uses genetic algorithms or other similar evolutionary algorithms suffers a problem known as blotting which is a sudden uncontrolled growth of an individual (circuit), which may render the synthesis inefficient because of memory utilization, making the algorithm difficult to continue running and eventually stack in a local minima, there for an optimized reversible circuit may not be generated. In this method the algorithm used was blot free, the blotting was carefully controlled by fixing a suitable length and size of the individuals in the population. Following this approach, the cost of generating circuits was greatly reduced giving the algorithm to reach the end of the last designated generation to give out optimal or near optimal results. The results of the circuits generated using this method were compared with some of the results already in the literature, and in many cases, our results appeared to be better in terms of gate count and quantum cost metrics.
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