(SpectrumIEEE) Research into developing analog optimizers—machines that manipulate physical components to determine the optimized solution—is providing insight into what is required to make them competitive with traditional computers. The researchers found that the higher connectivity an analog optimizer has between its components, the better its performance. To that end, the researchers compared their machine, a coherent Ising machine, to a quantum annealer built by quantum computing company D-Wave.
The main difference between the two is the connectivity difference. D-Wave’s quantum annealer uses qubits to model the problem being optimized, which as a general rule, makes it possible to only directly connect neighboring qubits and limits the overall connectivity. The coherent Ising machine, however, uses pulses of light that can be shuttled around, making it possible for any two pulses of interest to directly interact.
By testing the two systems on two types of optimization problems (the Sherrington-Kirkpatrick model and MAX-CUT), the researchers showed that for scenarios with high connectivity, the coherent Ising machine outperformed the quantum annealer. The takeaway isn’t that Ising machines are better than quantum annealers, however. It’s less about choosing between a coherent Ising machine or a quantum annealer, and more about examining how many connections are within those machines.