TY - JOUR T1 - Discrete optimization using quantum annealing on sparse Ising models JF - Frontiers in Physics Y1 - 2014 A1 - Bian, Zhengbing A1 - Chudak, Fabian A1 - Israel, Robert A1 - Brad Lackey A1 - Macready, William G A1 - Roy, Aidan AB - This paper discusses techniques for solving discrete optimization problems using quantum annealing. Practical issues likely to affect the computation include precision limitations, finite temperature, bounded energy range, sparse connectivity, and small numbers of qubits. To address these concerns we propose a way of finding energy representations with large classical gaps between ground and first excited states, efficient algorithms for mapping non-compatible Ising models into the hardware, and the use of decomposition methods for problems that are too large to fit in hardware. We validate the approach by describing experiments with D-Wave quantum hardware for low density parity check decoding with up to 1000 variables. PB - Frontiers VL - 2 U4 - 56 ER -