Nearly 75 years after the puzzling first detection of the kaon, scientists are still looking to the particle for hints of physics beyond their current understanding.
Daniel Ratner, head of SLAC’s machine learning initiative, explains the lab’s unique opportunities to advance scientific discovery through machine learning.
A cheap technique could detect neutrinos in polar ice, eventually allowing researchers to expand the energy reach of IceCube without breaking the bank.
Matching up maps of matter and light from the Dark Energy Survey and Fermi Gamma-ray Space Telescope may help astrophysicists understand what causes a faint cosmic gamma-ray glow.
An “out there” theory inspired the development of the Dark Matter Radio, a device that could explain the mysterious matter that makes up 85 percent of the mass of our universe.
The complete data from the EXO-200 experiment provide new information on neutrinoless double beta decay and set the stage for future experiments that will search for the hypothetical process.
At SLAC’s FACET facility, researchers have produced an intense electron beam by 'sneaking’ electrons into plasma, demonstrating a method that could be used in future compact discovery machines that explore the subatomic world.