On the hardness of quadratic unconstrained binary optimization problems
Quantum Physics
2025-11-04 v1
Abstract
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 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 exponents characterizing the success probability of a D-Wave annealer to solve a QUBO correlate very well with the predictions based on the Hamming distance distributions computed for small problem instances.
Cite
@article{arxiv.2206.11689,
title = {On the hardness of quadratic unconstrained binary optimization problems},
author = {Vrinda Mehta and Fengping Jin and Kristel Michielsen and Hans De Raedt},
journal= {arXiv preprint arXiv:2206.11689},
year = {2025}
}
Comments
6 pages, 6 figures