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Mathematics 2017, 5(1), 5; doi:10.3390/math5010005

Data Clustering with Quantum Mechanics

1,2,†,* , 2,3,†
and
4,†
1
College of Physics and Optoelectronics, Taiyuan University of Technology, Taiyuan 030024, China
2
Near India Pvt Ltd., No. 71/72, Jyoti Nivas College Road, Koramangala, Bengalore 560095, India
3
EngKraft LLC, 312 Adeline Avenue, San Jose, CA 95136, USA
4
Sherman Visual Lab, Sunnyvale, CA 94085, USA
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editor: Khalide Jbilou
Received: 8 November 2016 / Revised: 15 December 2016 / Accepted: 28 December 2016 / Published: 6 January 2017
(This article belongs to the Special Issue Numerical Linear Algebra with Applications)
View Full-Text   |   Download PDF [2259 KB, uploaded 6 January 2017]   |  

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. View Full-Text
Keywords: computational quantum mechanics; Meila–Shi algorithm; quantum clustering; MATLAB computational quantum mechanics; Meila–Shi algorithm; quantum clustering; MATLAB
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Scott, T.C.; Therani, M.; Wang, X.M. Data Clustering with Quantum Mechanics. Mathematics 2017, 5, 5.

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