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Visualizing Nuclear Scission through a Multifield Extension of Topological Analysis
Dec. 2012 (vol. 18 no. 12)
pp. 2033-2040
David Duke, University of Leeds, UK
Hamish Carr, University of Leeds, UK
Aaron Knoll, Argonne National Lab, USA
Nicolas Schunck, Lawrence Livermore National Lab, USA
Hai Ah Nam, Oak Ridge National Lab, USA
Andrzej Staszczak, University Marie Curie-Skłodowska, Poland
In nuclear science, density functional theory (DFT) is a powerful tool to model the complex interactions within the atomic nucleus, and is the primary theoretical approach used by physicists seeking a better understanding of fission. However DFT simulations result in complex multivariate datasets in which it is difficult to locate the crucial ‘scission’ point at which one nucleus fragments into two, and to identify the precursors to scission. The Joint Contour Net (JCN) has recently been proposed as a new data structure for the topological analysis of multivariate scalar fields, analogous to the contour tree for univariate fields. This paper reports the analysis of DFT simulations using the JCN, the first application of the JCN technique to real data. It makes three contributions to visualization: (i) a set of practical methods for visualizing the JCN, (ii) new insight into the detection of nuclear scission, and (iii) an analysis of aesthetic criteria to drive further work on representing the JCN.
Index Terms:
Topology,Data visualization,Discrete Fourier transforms,Nuclear physics,Trajectory,Approximation methods,multifields,Topology,scalar fields
David Duke, Hamish Carr, Aaron Knoll, Nicolas Schunck, Hai Ah Nam, Andrzej Staszczak, "Visualizing Nuclear Scission through a Multifield Extension of Topological Analysis," IEEE Transactions on Visualization and Computer Graphics, vol. 18, no. 12, pp. 2033-2040, Dec. 2012, doi:10.1109/TVCG.2012.287
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