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Title: Method for discovering relationships in data by dynamic quantum clustering

Abstract

Data clustering is provided according to a dynamical framework based on quantum mechanical time evolution of states corresponding to data points. To expedite computations, we can approximate the time-dependent Hamiltonian formalism by a truncated calculation within a set of Gaussian wave-functions (coherent states) centered around the original points. This allows for analytic evaluation of the time evolution of all such states, opening up the possibility of exploration of relationships among data-points through observation of varying dynamical-distances among points and convergence of points into clusters. This formalism may be further supplemented by preprocessing, such as dimensional reduction through singular value decomposition and/or feature filtering.

Inventors:
;
Publication Date:
Research Org.:
SLAC National Accelerator Lab., Menlo Park, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1356210
Patent Number(s):
9,646,074
Application Number:
14/482,961
Assignee:
The Board of Trustees of the Leland Stanford Junior University SLAC
DOE Contract Number:  
AC02-76SF00515
Resource Type:
Patent
Resource Relation:
Patent File Date: 2014 Sep 10
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Weinstein, Marvin, and Horn, David. Method for discovering relationships in data by dynamic quantum clustering. United States: N. p., 2017. Web.
Weinstein, Marvin, & Horn, David. Method for discovering relationships in data by dynamic quantum clustering. United States.
Weinstein, Marvin, and Horn, David. Tue . "Method for discovering relationships in data by dynamic quantum clustering". United States. doi:. https://www.osti.gov/servlets/purl/1356210.
@article{osti_1356210,
title = {Method for discovering relationships in data by dynamic quantum clustering},
author = {Weinstein, Marvin and Horn, David},
abstractNote = {Data clustering is provided according to a dynamical framework based on quantum mechanical time evolution of states corresponding to data points. To expedite computations, we can approximate the time-dependent Hamiltonian formalism by a truncated calculation within a set of Gaussian wave-functions (coherent states) centered around the original points. This allows for analytic evaluation of the time evolution of all such states, opening up the possibility of exploration of relationships among data-points through observation of varying dynamical-distances among points and convergence of points into clusters. This formalism may be further supplemented by preprocessing, such as dimensional reduction through singular value decomposition and/or feature filtering.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue May 09 00:00:00 EDT 2017},
month = {Tue May 09 00:00:00 EDT 2017}
}

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