  Quantum processing units (QPUs) executing annealing algorithms have shown
promise in optimization and simulation applications. Hybrid algorithms are a
natural bridge to additional applications of larger scale. We present a
straightforward and effective method for solving larger-than-QPU
lattice-structured Ising optimization problems. Performance is compared against
simulated annealing with promising results, and improvement is shown as a
function of the generation of D-Wave QPU used.
