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| Poster (Other) | FZJ-2023-04929 |
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2023
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Please use a persistent id in citations: doi:10.34734/FZJ-2023-04929
Abstract: The performance of quantum annealing has been studied well for solving optimization problems with a unique solution. One of the most common metrics of performance is the scaling of the success probability (the probability with which one finds the solution to the problem) or related quantities like time to solution (TTS) [1]. On the other hand, for problems with multiple solutions, another aspect of performance that becomes relevant is the fairness of quantum annealing in sampling the various solutions of the problem, i.e., whether or not it can sample all the solutions of the problem with comparable probabilities [2]. Using both simulations and the D-Wave Advantage_system5.1 (DWAdv) quantum annealer we study the sampling efficiency of the standard quantum annealing algorithm as well as the reverse annealing protocol, as implemented by the D-Wave systems, for solving 2-Satisfiability (SAT) problems with four satisfying assignments. We find that while the numerically obtained sampling probabilities using the standard quantum annealing algorithm are not always fair, but in agreement with the perturbation theory in the long annealing time limit, the sampling probabilities of the four ground states from DWAdv are comparable for a majority of the problems, which indicates the presence of noise and temperature effects in the latter. On the other hand, we find that the sampling probabilities for the reverse annealing protocol depend greatly on the choice of annealing times, reversal distance, waiting time, and the initial state.
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