Published September 24, 2005 | Version v1
Report

Graph-based Techniques for Orbit Classification: Early Results

Description

An important step in the quest for low-cost fusion power is the ability to perform and analyze experiments in prototype fusion reactors. An automated analysis and interpretation software toolkit allows physicists to quickly analyze their experiments and plan new ones. In this preliminary report, they consider the analysis of Poincare plots that contain the orbits generated by the particles in a fusion reactor. They describe how they can use graph-based methods to extract features from orbits. These features are then used to evaluate the accuracy of machine learning algorithms and their response on orbits with few points

Availability note (English)

Available from http://www.llnl.gov/tid/lof/documents/pdf/325446.pdf; PURL: https://www.osti.gov/servlets/purl/885147-GDYNSI/

Additional details

Publishing Information

Imprint Pagination
41 p.
Report number
UCRL-TR--215690

INIS

Country of Publication
United States
Country of Input or Organization
United States
INIS RN
37095709
Subject category
S70: PLASMA PHYSICS AND FUSION TECHNOLOGY; S99: GENERAL AND MISCELLANEOUS;
Resource subtype / Literary indicator
Non-conventional Literature
Descriptors DEI
ACCURACY; ALGORITHMS; CLASSIFICATION; LEARNING; THERMONUCLEAR REACTORS
Descriptors DEC
MATHEMATICAL LOGIC

Optional Information

Contract/Grant/Project number
W-7405-ENG-48
Notes
PDF-FILE: 41 ; SIZE: 0 KBYTES
Funding organization
US Department of Energy (United States)