On the hardness of quadratic unconstrained binary optimization problems

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 man...

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Veröffentlicht in:Frontiers in physics Jg. 10
Hauptverfasser: Mehta, V., Jin, F., Michielsen, K., De Raedt, H.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Frontiers Media S.A 31.08.2022
Schlagworte:
hamming distance
level spacing distribution
quantum annealer
QUBO problem
success probability
ISSN:2296-424X, 2296-424X
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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 quadratic unconstrained binary optimization correlate very well with the predictions based on the Hamming distance distributions computed for small problem instances.
AbstractList 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.
Author Mehta, V.
Michielsen, K.
De Raedt, H.
Jin, F.
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Snippet We use exact enumeration to characterize the solutions of quadratic unconstrained binary optimization problems of less than 21 variables in terms of their...
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SubjectTerms hamming distance
level spacing distribution
quantum annealer
QUBO problem
success probability
Title On the hardness of quadratic unconstrained binary optimization problems
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