On the hardness of quadratic unconstrained binary optimization problems

On the hardness of quadratic unconstrained binary optimization problems

Blog Article

We use exact enumeration to characterize the solutions of quadratic unconstrained binary optimization problems of less than 21 variables in terms of their distributions of trailmaster challenger 200x Hamming distances to close-by solutions.We also perform experiments with the D-Wave Advantage 5.1 quantum annealer, solving many instances of up to 170-variable, quadratic unconstrained binary optimization problems.

Our results demonstrate that the pc850q exponents characterizing the success probability of a D-Wave annealer to solve a quadratic unconstrained binary optimization correlate very well with the predictions based on the Hamming distance distributions computed for small problem instances.