Cell number optimization for Quantum Cellular Automata based on genetic algorithm

Quantum cellular automata (QCA) is a new nanotechnology that has attracted attentions due to its lower power consumption, smaller size and higher speed compared to CMOS technology. Majority and inverter gates together make a universal set in QCA circuits. An important step in designing QCA circuits is reducing the number of required cells. This paper introduces the structure of QCA and its basic circuits and then proposes a method to reduce the number of cells used in designing these circuits based on genetic algorithm. The results of this method compared with previous methods indicate a significant improvement in terms of number of cells used in the synthesis of QCA circuits.