Experimental investigation of performance differences between Coherent Ising Machines and a quantum annealer

Physical annealing systems provide heuristic approaches to solving NP-hard Ising optimization problems. Here, we study the performance of two types of annealing machines—a commercially available quantum annealer built by D-Wave Systems, and measurement-feedback coherent Ising machines (CIMs) based on optical parametric oscillator networks—on two classes of problems, the Sherrington-Kirkpatrick (SK) model and MAX-CUT. The D-Wave quantum annealer outperforms the CIMs on MAX-CUT on regular graphs of degree 3. On denser problems, however, we observe an exponential penalty for the quantum annealer (exp(−α_DW*N²)) relative to CIMs (exp(−α_CIM*N)) for fixed anneal times, on both the SK model and on 50%-edge-density MAX-CUT, where the coefficients α_CIM and α_DW are problem-class-dependent. On instances with over 50 vertices, several-orders-of-magnitude improvements in performance are identified, establishing better benchmarks for quantum annealing machines.