High Dimensional Event Exploration Over Multiple Simulations

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 simulations 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 the parameter space of arbitrary dimension and visualize events of interest in two dimensions. The first dimension is the tour ordering and the second dimension is usually time. This paper presents our novel approach and gives examples in the context of simulations of magnet dynamics. Our initial findings are that, while z-ordering does allow the user to analyze event families, other ordering techniques would likely improve the visualization by improving spatial locality.