IEEE Annual International Computer Software and Applications Conference (COMPSAC)

Entanglement Partitioning of Quantum Particles for Data Clustering

Dianxun Shuai, Cunpai Lu, Bin Zhang

Published Jan 1, 2006• 1 citation

Abstract

This paper presents a generalized quantum particle model to greatly quicken and improve data clustering. The proposed model uses the random dynamics and quantum entanglement of quantum particles on a particle array. In comparison with classical nonquantum methods, the quantum particle model not only clusters much faster, but also has better clustering quality for multi-shape multi-distribution high-dimensional large-scale data sets with noise. The simulations and comparisons show the effectiveness of the quantum particle model

DOI: 10.1109/compsac.2006.131

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