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:
- Issue Date:
- Research Org.:
- SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1356210
- Patent Number(s):
- 9646074
- Application Number:
- 14/482,961
- Assignee:
- The Board of Trustees of the Leland Stanford Junior University
- Patent Classifications (CPCs):
-
G - PHYSICS G06 - COMPUTING G06F - ELECTRIC DIGITAL DATA PROCESSING
- 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. 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 = {2017},
month = {5}
}
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