Distribution of Dark Matter and Stars

















The distribution of Dark Matter and stars in the simulated galaxy clusters at z=0.  Galaxies form at the center of small virialized dark matter halos residing in a much larger cluster potential.  The size of the region shown is 8h-1Mpc (10% of the entire simulation volume).

Aspherical Virial Shocks and Accretion Shocks
















A gas velocity map overlayed on the entropy map of the cluster at z=1 (left) and z=0 (right) in one of three orthogonal lines-of-sight. These maps are the average projected velocity and entropy in a 125h-1kpc (comoving) slice centered on the central density peak. The size of the region shown is 8h-1Mpc. The length of the thick vertical vector in the bottom-left corner corresponds to 400 kms; the entropy maps are color-coded on a log10 scale in units of keV cm2. These maps show that the gas accretion onto the main cluster is highly aspherical.

Formation of Shock and Cold Front in Cluster Mergers















The movie shows the formation of bow shocks and “cold fronts” (discovered by Chandra X-ray Observatory) formed during a major merger.  The panels shows X-ray surface brightness (left) and emission-weighted temperature distribution (right).  The size of the region shown is 2/h Mpc. Modern cosmological simulations of structure formation reproduce the observed properties of galaxy clusters in exquisite details.

High-Resolution Cosmological Simulation of Galaxy Clusters

















A snapshot of the cosmological hydrodynamical simulation of galaxy cluster formation in the present-day universe. From left to right, the distribution of dark matter, gas density and entropy (top) and stars, metallicity and temperature (bottom). The size of the region shown is 8h-1Mpc (10% of the simulation volume).

X-ray surface brightness and temperature
















The X-ray surface brightness (top) and emission weighted temperature (bottom) of the simulated LCDM cluster at four different redshifts. The maps are color-coded on a log10 scale in units of erg s-1 cm-2 arcmin-2 (surface brightness) and keV (temperature). Both surface brightness and temperature are calculated in the 0.5-2 keV band. The size of the volume shown is 2h-1 Mpc. Note that the cold front associated with the merging sub-cluster appears behind the merger shock front to the left of two sub-clusters (z=0.43 panel). Note also the cold front associated with the merging subclump at z=0 to the left of the cluster center and the adjacent compressed region of enhanced temperature. The subclump is trailed by a relatively cold (~1-2 keV) intergalactic gas accreted along a filament.

Formation of Shock and Cold Fronts in Clusters Mergers

















A gas velocity map overlayed on the emission-weighted temperature map of the cluster undergoing major merger at z=0.43. The map shows the average projected velocity and entropy in a 125h-1kpc (comoving) slice centered on the central density peak. The size of the region shown is 8h-1Mpc. The length of the thick vertical vector in the bottom-left corner corresponds to 400 kms; the emission-weighted temperature maps are color-coded on a log10 scale in units of Kelvin. Supersonic motion results in two large-scale bow shocks propagating in opposite surrounded by strong accretion shocks. Note, however, that the accretion shock around the cluster is very aspherical and does not penetrate into the filament; relatively low-entropy gas accreting onto cluster along the filament does not pass through the strong virial shocks and can be traced into the central region.

Temperature and Metallicity maps of a LCDM cluster
















These maps are mass-weighted temperature (top) and metallicity (bottom) maps. The size of the maps and color-coding is the same as above.

Sunyaev-Zel’dovich Effect















Maps of thermal (left) and kinematic (right) SZE SZ Effect of the simulated LCDM cluster at the present-day (z=0). The maps are color-coded on a log10 scale (Click the image to see a color-scale). The comoving size of the region shown is 2.5/hMpc centered on the minimum of cluster potential.

Chandra Cosmology Projects
















Mock Chandra photon maps of simulated unrelaxed (left) and relaxed (right) clusters. Click here for high resolution maps (from Nagai, Vikhlinin, Kravtsov 2007, ApJ, 655, 98).

Density and Entropy maps of a LCDM cluster
















The maps of projected density (top) and entropy (defined as Tn-2/3, bottom) of a cluster in a simulation with cooling and star formation. The simulation is carried our assuming a flat cosmological model with vacuum energy. The figure shows the cluster at four different redshifts in a 60-1kpc slice centered on the central density peak. The maps are color-coded on a log10 scale in units of cm-2 (column density) and keV cm2 (entropy). The size of the region shown is 8h-1Mpc (10% of the entire simulation volume). The entropy maps reveal a very complex entropy distribution of the gas.  Both the filaments and the forming cluster are directions along the merger axis. These rather strong shocks are clearly seen in the temperature map of z=0.43 epoch as regions of enhanced temperature with very sharp boundaries. Note also that the cold front associated with the merging sub-cluster appears behind one of the merger shock front.

The large-scale structure of the Universe

















This is a movie flying through the large-scale distribution of “dark matter” in the concordance CDM cosmological model of the Universe.  The box size is  100 (comoving) Mpc

Visualization

Visualizations help people see things that were not obvious to them before.  Even when data volumes are very large, patterns can be spotted easily and quickly.  As more and more data is collected and analyzed, researchers must rely increasingly on visualizations to find signals from noisy data, understand what factors influence outcomes, predict the future behaviors, and share concepts and ideas with others.  However, to be truly effective, data visualizations must be well designed, easy to use, and equipped with some level of interactivity.  In our research group, we are exploring and using a variety of data visualization techniques to enhance research, teaching, and outreach activities.