Non-convex optimization moves onto a photonic chip: quantum tunneling search marks local minima and the global minimum on waveguide arrays
A non-convex objective is written into the potential term of a photonic waveguide array, where light evolves by quantum tunneling and the output intensity distribution marks where the minima sit. Experiments ran on one- and two-dimensional waveguide arrays, preparing a low-energy input state with incomplete local annealing and then adding a varying Hamiltonian to speed the search and resolve the global minimum. The authors report quantum speedup over classical stochastic gradient descent, though the main text frames that comparison as an illustrative exploration-behavior baseline.