Efficient Cartesian Genetic Programming-Based Automatic Synthesis Framework for Reversible Quantum-Flux-Parametron Logic Circuits

Abstract

Reversible computing has garnered significant attention as a promising avenue for achieving energy-efficient computing systems, particularly within the realm of quantum computing. The reversible quantum-flux-parametron (RQFP) is the first practical reversible logic gate utilizing adiabatic superconducting devices, with experimental evidence supporting both its logical and physical reversibility. Each RQFP logic gate operates on alternating current (AC) power and features three input ports and three output ports. Notably, each output port is capable of implementing a majority function while driving only a single fan-out. Additionally, the three inputs to each gate must arrive in the same clock phase. These inherent characteristics present substantial challenges in the design of RQFP logic circuits. To address these challenges, this article proposes an automatic synthesis framework for RQFP logic circuit design based on efficient Cartesian genetic programming (CGP). The framework aims to minimize both the number of RQFP logic gates and the number of garbage outputs within the generated RQFP logic circuit. It incorporates the specific characteristics of the RQFP logic circuit by encoding them into the genotype of a CGP individual. It also introduces several point mutation operations to facilitate the generation of new individuals. Furthermore, the framework integrates circuit simulation with formal verification to assess the functional equivalence between the parent and its offspring. Experimental results on RevLib and reversible reciprocal circuit benchmarks demonstrate the effectiveness of our framework.