FI3D: Direct-Touch Interaction for the Exploration of 3D Scientific Visualization Spaces

We have performed the largest ever particle simulation of a Milky Way-sized dark matter halo, and present the most comprehensive convergence study for an individual dark matter halo carried out thus far. We have also simulated a sample of 6 ultra-highly resolved Milky-way sized halos, allowing us to estimate the halo-to-halo scatter in substructure statistics. In our largest simulation, we resolve nearly 300,000 gravitationally bound subhalos within the virialized region of the halo. Simulations of the same object differing in mass resolution by factors up to 1800 accurately reproduce the largest subhalos with the same mass, maximum circular velocity and position, and yield good convergence for the abundance and internal properties of dark matter substructures. We detect up to four generations of subhalos within subhalos, but contrary to recent claims, we find less substructure in subhalos than in the main halo when regions of equal mean overdensity are compared. The overall substructure mass fraction is much lower in subhalos than in the main halo. Extrapolating the main halo's subhalo mass spectrum down to an Earth mass, we predict the mass fraction in substructure to be well below 3% within 100 kpc, and to be below 0.1% within the Solar Circle. The inner density profiles of subhalos show no sign of converging to a fixed asymptotic slope and are well fit by gently curving profiles of Einasto form. The mean concentrations of isolated halos are accurately described by the fitting formula of Neto et al. down to maximum circular velocities of 1.5 km/s, an extrapolation over some 5 orders of magnitude in mass. However, at equal maximum circular velocity, subhalos are more concentrated than field halos, with a characteristic density that is typically ~2.6 times larger and increases towards the halo centre.

Even though interaction is an important part of information visualization (Infovis), it has garnered a relatively low level of attention from the Infovis community. A few frameworks and taxonomies of Infovis interaction techniques exist, but they typically focus on low-level operations and do not address the variety of benefits interaction provides. After conducting an extensive review of Infovis systems and their interactive capabilities, we propose seven general categories of interaction techniques widely used in Infovis: 1) Select, 2) Explore, 3) Reconfigure, 4) Encode, 5) Abstract/Elaborate, 6) Filter, and 7) Connect. These categories are organized around a user's intent while interacting with a system rather than the low-level interaction techniques provided by a system. The categories can act as a framework to help discuss and evaluate interaction techniques and hopefully lay an initial foundation toward a deeper understanding and a science of interaction.