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- W1654954650 abstract "It has been revealed during the last few decades that approaches originating from the physics succeeds in solving combinatorial optimization problems [1]. The simulated thermal annealing method created such a close relation between physics and optimization problems. The quantum annealing method was born as an analogue of conventional thermal annealing [2, 3]. In spite of its origin, the mechanism and formulation of quantum annealing are fundamentally different from those of simulated thermal annealing. The former is based on the dynamics in quantum mechanics, while the latter is on the classical dynamics. Furthermore the quantum annealing is basically formulated for zero temperature in contrast to finite temperature simulation of thermal annealing. Because of these differences, the quantum annealing is expected as a novel efficient method for optimization problems. In practice, an experiment using spin-glass material has shown the superiority of the quantum annealing over the thermal annealing [4]. Simulations by means of the pathintegral quantum Monte-Carlo have also shown that an optimization in the spin-glass model is achieved in a less time by the quantum annealing than by the thermal annealing [5]. However study on quantum annealing is insu.cient for establishing this method as an effective optimization method. We focus in this paper on some basic features and a new method for implementation of the simulated quantum annealing." @default.
- W1654954650 created "2016-06-24" @default.
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- W1654954650 date "2005-11-16" @default.
- W1654954650 modified "2023-10-17" @default.
- W1654954650 title "Simulated Quantum Annealing by the Real-time Evolution" @default.
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- W1654954650 doi "https://doi.org/10.1007/11526216_8" @default.
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