Method for discovering relationships in data by dynamic quantum clustering
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.
- Research Organization:
- SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC02-76SF00515
- Assignee:
- The Board of Trustees of the Leland Stanford Junior University (Palo Alto, CA)
- Patent Number(s):
- 8,874,412
- Application Number:
- 12/586,036
- OSTI ID:
- 1162103
- Resource Relation:
- Patent File Date: 2009 Sep 15
- Country of Publication:
- United States
- Language:
- English
Similar Records
Systems and methods for determining optimal parameters for dynamic quantum clustering analyses
Dynamic Quantum Clustering: A Tool for Unsupervised Exploration of Structures in Data