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arXiv:1104.3246

HYBRID QUANTUM ANNEALING FOR CLUSTERING PROBLEMS

Shu Tanaka, Ryo Tamura, Issei Sato, Kenichi Kurihara

Published Dec 1, 2012• 1 citation
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Abstract

We develop a hybrid type of quantum annealing in which we control temperature and quantum field simultaneously. We study the efficiency of proposed quantum annealing and find a good schedule of changing thermal fluctuation and quantum fluctuation. In this paper, we focus on clustering problems which are important topics in information science and engineering. We obtain the better solution of the clustering problem than the standard simulated annealing by proposed quantum annealing.

DOI
10.1142/9789814425988_0006

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Quantum annealing method has been widely attracted attention in statistical physics and information science since it is expected to be a powerful method to obtain the best solution of optimization problem as well as simulated annealing. The quantum annealing method was incubated in quantum statistical physics. This is an alternative method of the simulated annealing which is well-adopted for many optimization problems. In the simulated annealing, we obtain a solution of optimization problem by decreasing temperature (thermal fluctuation) gradually. In the quantum annealing, in contrast, we decrease quantum field (quantum fluctuation) gradually and obtain a solution. In this paper we review how to implement quantum annealing and show some quantum fluctuation effects in frustrated Ising spin systems.