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Visualizing Nuclear Scission through a Multifield Extension of Topological Analysis.

D Duke1, H Carr, A Knoll

  • 1School of Computing, University of Leeds, UK. D.J.Duke@leeds.ac.uk

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This study introduces the Joint Contour Net (JCN) for analyzing complex nuclear science data, improving the visualization of nuclear fission and scission point identification in density functional theory simulations.

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Area of Science:

  • Nuclear Physics
  • Computational Physics

Background:

  • Density functional theory (DFT) is crucial for modeling atomic nuclei and understanding nuclear fission.
  • DFT simulations generate complex multivariate datasets, hindering the identification of key events like nuclear scission.

Purpose of the Study:

  • To apply the Joint Contour Net (JCN) data structure to analyze real-world DFT simulations.
  • To develop practical visualization methods for the JCN.
  • To gain new insights into detecting the nuclear scission point.

Main Methods:

  • Topological analysis of multivariate scalar fields using the Joint Contour Net (JCN).
  • Application of JCN to real data from DFT simulations of nuclear fission.
  • Development of visualization techniques for JCN representations.

Main Results:

  • Successful application of JCN to analyze complex DFT data for the first time.
  • Demonstration of JCN's utility in identifying the nuclear scission point and its precursors.
  • Establishment of practical methods for JCN visualization.

Conclusions:

  • The Joint Contour Net (JCN) is an effective tool for analyzing nuclear science data, particularly for nuclear fission studies.
  • JCN visualization methods provide valuable insights into complex simulation data.
  • Further research into JCN representation aesthetics can enhance its applicability.