期刊
APPLIED SCIENCES-BASEL
卷 12, 期 24, 页码 -出版社
MDPI
DOI: 10.3390/app122412778
关键词
multipartite entanglement; G states; W states; ensemble learning
This paper introduces a method for classifying multipartite entanglement using convex hull and tangent hyperplane, and improves the accuracy of classification by applying ensemble learning of machine learning to accelerate the calculation.
Quantum entanglement becomes more complicated and capricious when more than two parties are involved. There have been methods for classifying some inequivalent multipartite entanglements, such as GHZ states and W states. In this paper, based on the fact that the set of all W states is convex, we approximate the convex hull by some critical points from the inside and propose a method of classification via the tangent hyperplane. To accelerate the calculation, we bring ensemble learning of machine learning into the algorithm, thus improving the accuracy of the classification.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据