An integrated exploration approach to visualizing multivariate particle data

Chad Jones; Kwan Liu Ma; Stéphane Ethier; Wei Li Lee

doi:10.1109/MCSE.2008.88

An integrated exploration approach to visualizing multivariate particle data

Chad Jones
, Kwan Liu Ma
, Stéphane Ethier
, Wei Li Lee

PPPL Computational Science

Research output: Contribution to journal › Article › peer-review

12 Scopus citations

Abstract

The authors describe a data exploration system that visualizes time-varying, multivariate, point-based data from gyrokinetic particle simulations. By using two interaction modes, their system lets researchers explore collections of densely packed particles and discover interesting aspects, such as the location and motion of particles trapped in turbulent plasma flow.

Original language	English (US)
Article number	4548201
Pages (from-to)	20-29
Number of pages	10
Journal	Computing in Science and Engineering
Volume	10
Issue number	4
DOIs	https://doi.org/10.1109/MCSE.2008.88
State	Published - Jul 2008

All Science Journal Classification (ASJC) codes

General Computer Science
General Engineering

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10.1109/MCSE.2008.88

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abstract = "The authors describe a data exploration system that visualizes time-varying, multivariate, point-based data from gyrokinetic particle simulations. By using two interaction modes, their system lets researchers explore collections of densely packed particles and discover interesting aspects, such as the location and motion of particles trapped in turbulent plasma flow.",

author = "Chad Jones and Ma, \{Kwan Liu\} and St{\'e}phane Ethier and Lee, \{Wei Li\}",

year = "2008",

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AU - Ethier, Stéphane

AU - Lee, Wei Li

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AB - The authors describe a data exploration system that visualizes time-varying, multivariate, point-based data from gyrokinetic particle simulations. By using two interaction modes, their system lets researchers explore collections of densely packed particles and discover interesting aspects, such as the location and motion of particles trapped in turbulent plasma flow.

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An integrated exploration approach to visualizing multivariate particle data

Abstract

All Science Journal Classification (ASJC) codes

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