  We analyze the performance of simulated quantum annealing (SQA) on an
optimization problem for which simulated classical annealing (SA) is provably
inefficient because of a high energy barrier. We present evidence that SQA can
pass through this barrier to find the global minimum efficiently. This
demonstrates the potential for SQA to inherit some of the advantages of quantum
annealing (QA), since this problem has been previously shown to be efficiently
solvable by quantum adiabatic optimization.
