Particle Swarm Optimization Based Reversible Circuit Synthesis Using Mixed Control Toffoli Gates

With the sustained developments in semiconductor technology, power dissipation has become a vital concern. Several low-power design alternatives have been explored and developed to overcome this problem. The relationship between information lossless computation and low-power implementations have also been explored. Reversible logic is considered as a viable alternative in this context because of its information lossless nature, and hence has become a progressive research area. Various synthesis approaches for reversible logic circuits exist in the literature. Some of the methods try to generate optimal solutions for smaller circuits, while some try to synthesize larger circuits which lead to sub-optimal solutions. The metrics that are used for evaluation are typically Gate Count (GC) and Quantum Cost (QC). In this paper we propose a particle swarm optimization (PSO) based synthesis technique that uses both positive and negative control Toffoli gates. In this iterative approach, particles representing solutions are probabilistically mutated (modified) based on a cost-based evolution approach. Experimental results show that the method can generate solutions very fast and provide optimal solutions for many of the benchmarks.