Algorithm for Data Clustering in Pattern Recognition Problems Based on Quantum Mechanics

20 December 2001

journal article
research article
Published by American Physical Society (APS) in Physical Review Letters

Vol. 88 (1) , 018702
https://doi.org/10.1103/physrevlett.88.018702

Abstract

We propose a novel clustering method that is based on physical intuition derived from quantum mechanics. Starting with given data points, we construct a scale-space probability function. Viewing the latter as the lowest eigenstate of a Schrödinger equation, we use simple analytic operations to derive a potential function whose minima determine cluster centers. The method has one parameter, determining the scale over which cluster structures are searched. We demonstrate it on data analyzed in two dimensions (chosen from the eigenvectors of the correlation matrix). The method is applicable in higher dimensions by limiting the evaluation of the Schrödinger potential to the locations of data points.

Keywords

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