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- W2611869023 abstract "Classical and quantum annealing are two heuristic optimization methods that search for an optimal solution by slowly decreasing thermal or quantum fluctuations. Optimizing annealing schedules is important both for performance and fair comparisons between classical annealing, quantum annealing, and other algorithms. Here we present a heuristic approach for the optimization of annealing schedules for quantum annealing and apply it to 3D Ising spin glass problems. We find that if both classical and quantum annealing schedules are similarly optimized, classical annealing outperforms quantum annealing for these problems when considering the residual energy obtained in slow annealing. However, when performing many repetitions of fast annealing, simulated quantum annealing is seen to outperform classical annealing for our benchmark problems." @default.
- W2611869023 created "2017-05-12" @default.
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- W2611869023 date "2017-05-01" @default.
- W2611869023 modified "2023-09-25" @default.
- W2611869023 title "Optimizing Schedules for Quantum Annealing" @default.
- W2611869023 hasPublicationYear "2017" @default.
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