  The coherent Ising machine is expected to find a near-optimal solution in
various combinatorial optimization problems, which has been experimentally
confirmed with optical parametric oscillators (OPOs) and a field programmable
gate array (FPGA) circuit. The similar mathematical models were proposed three
decades ago by J. J. Hopfield, et al. in the context of classical neural
networks. In this article, we compare the computational performance of both
models.
