Understanding large amounts of spatiotemporal data from particle-based simulations, such as molecular dynamics, often relies on the computation and analysis of aggregate measures. These, however, by virtue of aggregation, hide structural information about the space time localization of the studied phenomena. This leads to degenerate cases where the measures fail to capture distinct behaviour. In order to drill into these aggregate values, we propose a multi-scale visual exploration technique. Our novel representation, based on partial domain aggregation, enables the construction of a continuous scale-space for discrete datasets and the simultaneous exploration of scales in both space and time. We link these two scale-spaces in a scale-space space-time cube and model linked views as orthogonal slices through this cube, thus enabling the rapid identification of spatio-temporal patterns at multiple scales. To demonstrate the effectiveness of our approach, we showcase an advanced exploration of a protein-ligand simulation.
An effective means for flow visualization is the depiction of particle trajectories. When rendering large amounts of these pathlines, standard visualization techniques suffer from several weaknesses, ranging from ambiguous depth perception to high geometrical complexity and decreased interactivity. This paper addresses these problems by choosing a novel approach to pathline visualization in 3D space, which we call Virtual Tubelets. It employs billboarding techniques in combination with suitable textures to create the illusion of three-dimensional tubes, which efficiently depict the particles' trajectories, while still maintaining interactive frame rates. Certain issues concerning virtual environments and immersive displays with multiple projection screens are resolved by choosing an appropriate orientation for the billboards. The use of modern, programmable graphics hardware allows for an additional speed-up of the rendering process and a further improvement of the image quality. This results in a nearly perfect illusion of tubular geometry, including plausible intersections and consistent illumination with the rest of the scene. To prove the efficiency of our approach, rendering speed and visual quality of Virtual Tubelets and conventional, polygonal tube renderings are compared. Interactive visualization of large particle sets is required to analyze the complicated structures and formation processes in astrophysical particle simulations. While some research has been done on the development of visualization techniques for steady particle fields, only very few approaches have been proposed to interactively visualize large time-varying fields and their dynamics. Particle trajectories are known to visualize dynamic processes over time, but due to occlusion and visual cluttering such techniques have only been reported for very small particle sets so far. In this paper we present a novel technique to solve these problems, and we demonstrate the potential of our approach for the visual exploration of large astrophysical particle sequences. We present a new hierarchical space-time data structure for particle sets which allows for a scale-space analysis of trajectories in the simulated fields. In combination with visualization techniques that adapt to the respective scales, clusters of particles with homogeneous motion as well as separation and merging regions can be identified effectively. The additional use of mapping functions to modulate the color and size of trajectories allows emphasizing various particle properties like direction, speed, or particle-specific attributes like temperature. Furthermore, tracking of interactively selected particle subsets permits the user to focus on structures of interest.