Solving the Minimum Spanning Tree Problem with a Quantum Annealer

被引:5
|
作者
O'Quinn, Wesley [1 ]
Mao, Shiwen [1 ]
机构
[1] Auburn Univ, Dept Elect & Comp Engn, Auburn, AL 36849 USA
关键词
Quantum Computing; D-Wave Systems; Quantum Algorithms; Minimum Spanning Tree (MST); Clustering; Unsupervised Learning; MULTIPLE DESCRIPTION VIDEO;
D O I
10.1109/GCWkshps50303.2020.9367437
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Quantum annealing (QA) is a different technology from gate-model quantum computing. This research proposes a novel technique for solving the Minimum Spanning Tree (MST) (or, the minimum weight spanning tree) problem on a quantum annealer. The problem is of interest due to its applications in clustering, unsupervised learning, network design, and image processing to name a few. The advent of quantum cloud computing has provided access to quantum computing tools, previously unavailable to the general community. D-Wave systems recently released cloud access to their quantum annealer type hardware, which this project leverages to provide a novel solution method to the MST problem.
引用
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页数:6
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