Using real images of galaxies from astronomical surveys of our Universe, a neural network can be trained to classify these with impressive accuracy. This visualization shows the output of the penultimate layer of a deep neural network during training as it is learning to classify two types of galaxies: spirals and ellipticals. Training is shown
A research team led by Princeton University is using supercomputers at Argonne National Laboratory to perform large-scale 3D simulations aimed at determining the mechanism of core-collapse supernova explosions. This visualization shows the neutrino-driven roiling convection of the nuclear material behind the newly reenergized supernova shock wave that surrounds the newly birthed neutron star, just hundreds of
Researchers from Stanford University are using ALCF computing resources to perform large-eddy simulations of flow over a realistic aircraft geometry. This volumetric visualization shows density gradients (numerical Schlieren) of flow over the high lift JAXA standard model at an angle of attack of 18.6 degrees. Inset graphics show sectional pressure comparisons against experimental measurements at
Researchers from Argonne National Laboratory and Northwestern University are using ALCF supercomputing resources to develop new methods for nanoscale x-ray imaging of 3D objects. This visualization first shows the simulated propagation of a plane wave through a thick Fresnel zone plate, which is a widely used type of x-ray focusing optic. The zone plate is
Volume rendering of entropy from a high-fidelity 3D simulation of massive stellar core collapse including rotation and magnetic fields leading up to a supernova explosion. This simulation is part of a first-of-its-kind exploration of the impact of rotation and magnetic fields on the neutrino-driven supernova mechanism and is being used to help us understand the