Deterministic Ground-State Search in a Spatial Photonic Ising Machine by Phase Retrieval

Abstract: A spatial photonic Ising machine (SPIM) solves large-scale combinatorial optimization problems by computing the Ising Hamiltonian through an optical Fourier transform. However, the ground-state search relies on the annealing process, in which spins are optimized stochastically and sequentially. We propose a ground-state search based on phase retrieval (PR), in which all spins are updated simultaneously and deterministically. By imposing an amplitude constraint in the Fourier plane, the modulated phase distribution corresponding to a spin configuration is guided toward the optimal solution. We numerically demonstrate that the proposed scheme reaches the ground state of rank-one Ising Hamiltonians with $10^4$ spins in a single iteration for all trials. Moreover, a radial rearrangement of the amplitude and the suitable design of the target pattern relaxed the search stagnation and promoted the optimization of spin configurations. The collective and deterministic spin update by phase retrieval provides a fast ground-state search for large-scale combinatorial optimization.