Data Clustering with Quantum Mechanics

Tony C. Scott, Madhusudan Therani and Xing M. Wang
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Tony C. Scott: College of Physics and Optoelectronics, Taiyuan University of Technology, Taiyuan 030024, China
Madhusudan Therani: Near India Pvt Ltd., No. 71/72, Jyoti Nivas College Road, Koramangala, Bengalore 560095, India
Xing M. Wang: Sherman Visual Lab, Sunnyvale, CA 94085, USA

Mathematics, 2017, vol. 5, issue 1, 1-17

Abstract: Data clustering is a vital tool for data analysis. This work shows that some existing useful methods in data clustering are actually based on quantum mechanics and can be assembled into a powerful and accurate data clustering method where the efficiency of computational quantum chemistry eigenvalue methods is therefore applicable. These methods can be applied to scientific data, engineering data and even text.

Keywords: computational quantum mechanics; Meila–Shi algorithm; quantum clustering; MATLAB (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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