# 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:
- 1162103

- Patent Number(s):
- 8,874,412

- Application Number:
- 12/586,036

- Assignee:
- The Board of Trustees of the Leland Stanford Junior University (Palo Alto, CA) SLAC

- DOE Contract Number:
- AC02-76SF00515

- Resource Type:
- Patent

- Resource Relation:
- Patent File Date: 2009 Sep 15

- 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., 2014.
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/1162103.
```

```
@article{osti_1162103,
```

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 Oct 28 00:00:00 EDT 2014},

month = {Tue Oct 28 00:00:00 EDT 2014}

}