On the hardness of quadratic unconstrained binary optimization problems

We use exact enumeration to characterize the solutions of quadratic unconstrained binary optimization problems less than 21 variables in terms their distributions Hamming distances close-by solutions. also perform experiments with D-Wave Advantage 5.1 quantum annealer, solving many instances up 170-variable, problems. Our results demonstrate that exponents characterizing success probability a annealer solve correlate very well predictions based on distance computed for small problem instances.