Prompt decision method for ground-state searches of natural computing architecture using 2D ising spin model
Mitsuki Ito, Masayuki Shiomura, Takahiro Saito, Yusuke Kihara, S. Sakai, Jun‐ichi Shirakashi · 2017
Recently, the ability to analyze big data has been required for the optimization of social systems and the development of artificial intelligence. Consequently, the solution of combinatorial optimization problems has become important in recent years, especially for the suitable operation of infrastructures. However, combinatorial optimization problems have unique properties that the number of candidate solutions increases explosively as the number of parameters is increased. One possible resolution of this issue involves artificial and/or simulated Ising spin system. In this work, we have implemented such a spin system using “prompt decision logic”. The convergence operation was successfully observed in prompt decision method for spin interaction. Therefore, it is indicated that Ising computing by prompt decision logic could resolve combinatorial optimization problems.