High Dimensional Event Exploration Over Multiple Simulations

In this project, we introduce a visualization technique to analyze event simulation data. In particular, we allow the user to discover families of events based on the topological evolution of discrete events across simulations. Discovering how events behave across runs of a simulation has applications in financial market analysis, military simulations, physical mechanics, and other settings. Our approach is to use established methods to produce a linearized tour through parameter space of arbitrary dimension and visualize events of interest in two dimensions, where the first dimension is the tour ordering and the second dimension is usually time. This paper presents our approach and gives examples in the context of a magnet dynamics simulation