Quantum Density Peak Clustering Algorithm

A widely used clustering algorithm, density peak clustering (DPC), assigns different attribute values to data points through the distance between data points, and then determines the number and range of clustering by attribute values. However, DPC is inefficient when dealing with scenes with a large amount of data, and the range of parameters is not easy to determine. To fix these problems, we propose a quantum DPC (QDPC) algorithm based on a quantum [Formula: see text] circuit and a Grover circuit. The time complexity is reduced to [Formula: see text] , whereas that of the traditional algorithm is [Formula: see text]. The space complexity is also decreased from [Formula: see text] to [Formula: see text].