SLAC’s Computational Astrophysics group seeks to bring the combined strength of theoretical and experimental physics to bear on some of the most fascinating problems in particle astrophysics and cosmology.
Kavli Institute for Partical Astrophysics and Cosmology (KIPAC) scientists, at work here in the "Vizlab," use computer visualizations to simulate and study the formation and evolution of the Universe.
(Matt Beardsley/SLAC National Accelerator Laboratory)
SLAC and Stanford researchers demonstrate that brain-mimicking ‘neural networks’ can revolutionize the way astrophysicists analyze their most complex data, including extreme distortions in spacetime...
Just like we orbit the sun and the moon orbits us, the Milky Way has satellite galaxies with their own satellites. Drawing from data on those galactic neighbors, a new model suggests the Milky Way should have an additional 100...
SLAC scientists find a new way to explain how a black hole’s plasma jets boost particles to the highest energies observed in the universe. The results could also prove useful for fusion and accelerator research on Earth.
SLAC and Stanford researchers demonstrate that brain-mimicking ‘neural networks’ can revolutionize the way astrophysicists analyze their most complex data, including extreme distortions in spacetime that are crucial for our understanding of the universe.
KIPAC scientists have for the first time used artificial neural networks to analyze complex distortions in spacetime, called gravitational lenses, demonstrating that the method is 10 million times faster than traditional analyses.