QAOA’s speed advantage over classical algorithms

Determine whether the Quantum Approximate Optimization Algorithm (QAOA) achieves a practical runtime speedup over classical optimization algorithms when solving combinatorial optimization problems.

Background

QAOA is a hybrid variational algorithm intended to leverage quantum circuits to sample high-quality solutions, with a classical optimizer tuning parameters. The authors note results indicating that, for low circuit depths, the average objective value within QAOA can be efficiently computed classically, which suggests classical parameter tuning may suffice.

This situation raises doubts about whether QAOA confers a genuine speed advantage over classical methods, leaving the question unresolved given current knowledge and hardware capabilities.