Entanglement partitioning of quantum particles for data clustering

This paper presents a generalized quantum particle model to greatly quicken and improve data clustering. I ne 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 multidistribution high-dimensional large-scale data sets with noise. The simulations and comparisons show the effectiveness of the quantum particle model.