Visualizing Nuclear Scission through a Multifield Extension of Topological Analysis.

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.