Integrated explorer for cosmological evolution

Our system design is motivated by the need to simultaneously observe multiple data modalities. The main output from the cosmological simulation is a set of particle data, where each particle represents a dark matter parcel which coalesces into larger structures over time. Next, the data is run through a halo finding algorithm (Rockstar [1]), which detects groups of gravitationally bound particles and identifies them as halos. Lastly, a merger tree generation tool (Consistent Trees [2]) analyzes the hierarchical evolution of halos as they continue to merge into larger structures. Although each of these data modalities are generated through an iterative process, an understanding of their interplay is essential. Since information about the raw particle data and the extracted halos inform one another, we designed a multi-view exploration tool and enhance these views with both qualitative and quantitative information. Because of the scale of the data and the multitude of features, we aim to provide capability to both locate and focus analysis on specific features of interest.