Abstract
Gyrokinetic particle simulations are critical to the study of anomalous energy transport associated with plasma microturbulence in magnetic confinement fusion experiments. The simulations are conducted on massively parallel computers and produce large quantities of particles, variables, and time steps, thus presenting a formidable challenge to data analysis tasks. We present two new visualization techniques for scientists to improve their understanding of the time-varying, multivariate particle data. One technique allows scientists to examine correlations in multivariate particle data with tightly coupled views of the data in both physical space and variable space, and to visually identify and track features of interest. The second technique, built into SCIRun, allows scientists to perform range-based queries over a series of time slices and visualize the resulting particles using glyphs. The ability to navigate the multiple dimensions of the particle data, as well as query individual or a collection of particles, enables scientists to not only validate their simulations but also discover new phenomena in their data.
| Original language | English (US) |
|---|---|
| Article number | 012033 |
| Journal | Journal of Physics: Conference Series |
| Volume | 78 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jul 1 2007 |
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ASJC Scopus subject areas
- Physics and Astronomy(all)
Cite this
Visual interrogation of gyrokinetic particle simulations. / Jones, Chad; Ma, Kwan-Liu; Sanderson, Allen; Myers, Lee Roy.
In: Journal of Physics: Conference Series, Vol. 78, No. 1, 012033, 01.07.2007.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Visual interrogation of gyrokinetic particle simulations
AU - Jones, Chad
AU - Ma, Kwan-Liu
AU - Sanderson, Allen
AU - Myers, Lee Roy
PY - 2007/7/1
Y1 - 2007/7/1
N2 - Gyrokinetic particle simulations are critical to the study of anomalous energy transport associated with plasma microturbulence in magnetic confinement fusion experiments. The simulations are conducted on massively parallel computers and produce large quantities of particles, variables, and time steps, thus presenting a formidable challenge to data analysis tasks. We present two new visualization techniques for scientists to improve their understanding of the time-varying, multivariate particle data. One technique allows scientists to examine correlations in multivariate particle data with tightly coupled views of the data in both physical space and variable space, and to visually identify and track features of interest. The second technique, built into SCIRun, allows scientists to perform range-based queries over a series of time slices and visualize the resulting particles using glyphs. The ability to navigate the multiple dimensions of the particle data, as well as query individual or a collection of particles, enables scientists to not only validate their simulations but also discover new phenomena in their data.
AB - Gyrokinetic particle simulations are critical to the study of anomalous energy transport associated with plasma microturbulence in magnetic confinement fusion experiments. The simulations are conducted on massively parallel computers and produce large quantities of particles, variables, and time steps, thus presenting a formidable challenge to data analysis tasks. We present two new visualization techniques for scientists to improve their understanding of the time-varying, multivariate particle data. One technique allows scientists to examine correlations in multivariate particle data with tightly coupled views of the data in both physical space and variable space, and to visually identify and track features of interest. The second technique, built into SCIRun, allows scientists to perform range-based queries over a series of time slices and visualize the resulting particles using glyphs. The ability to navigate the multiple dimensions of the particle data, as well as query individual or a collection of particles, enables scientists to not only validate their simulations but also discover new phenomena in their data.
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U2 - 10.1088/1742-6596/78/1/012033
DO - 10.1088/1742-6596/78/1/012033
M3 - Article
VL - 78
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
SN - 1742-6588
IS - 1
M1 - 012033
ER -