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100 1 _ |a Mehta, V.
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245 _ _ |a On the hardness of quadratic unconstrained binary optimization problems
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520 _ _ |a 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 quadratic unconstrained binary optimization correlate very well with the predictions based on the Hamming distance distributions computed for small problem instances.
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700 1 _ |a Jin, F.
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700 1 _ |a Michielsen, K.
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700 1 _ |a De Raedt, H.
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773 _ _ |a 10.3389/fphy.2022.956882
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