Superconductor Amoeba-Inspired Problem Solvers for Combinatorial Optimization
Naoki Takeuchi, Masashi Aono, Nobuyuki Yoshikawa · Physical Review Applied · 2019
Among advanced paradigms in the physics of computing, adiabatic quantum-flux-parametron (AQFP) logic is interesting, in that it can easily introduce stochastic processes by exploiting naturally occurring thermal fluctuations. This study proposes using AQFP logic to implement stochastic-local-search solvers. Experiments show that AQFP circuits can find solutions to simple logical constraint-satisfaction problems when moderate thermal fluctuations are applied. This result indicates the possibility of superconducting digital circuits dedicated to solving combinatorial optimization problems.