Quantum speedup of branch-and-bound algorithms

Branch-and-bound is a widely used technique for solving combinatorial optimization problems where one has access to two procedures: a branching procedure that splits a set of potential solutions into subsets, and a cost procedure that determines a lower bound on the cost of any solution in a given subset. Here we describe a quantum algorithm that can accelerate classical branch-and-bound algorithms near-quadratically in a very general setting. We show that the quantum algorithm can find exact ground states for most instances of the Sherrington-Kirkpatrick model in time O(2^{0.226n}), which is substantially more efficient than Grover's algorithm.