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Data Clustering with Quantum Mechanics

by 1,2,*,†, 2,3,† and 4,†
College of Physics and Optoelectronics, Taiyuan University of Technology, Taiyuan 030024, China
Near India Pvt Ltd., No. 71/72, Jyoti Nivas College Road, Koramangala, Bengalore 560095, India
EngKraft LLC, 312 Adeline Avenue, San Jose, CA 95136, USA
Sherman Visual Lab, Sunnyvale, CA 94085, USA
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editor: Khalide Jbilou
Mathematics 2017, 5(1), 5;
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)
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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MDPI and ACS Style

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

AMA Style

Scott TC, Therani M, Wang XM. Data Clustering with Quantum Mechanics. Mathematics. 2017; 5(1):5.

Chicago/Turabian Style

Scott, Tony C.; Therani, Madhusudan; Wang, Xing M. 2017. "Data Clustering with Quantum Mechanics" Mathematics 5, no. 1: 5.

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