AI is playing a key role in helping SLAC researchers find new galaxies and tiny neutrinos, and discover new drugs.

SLAC hosted two faculty members from institutions historically underrepresented in the research community via the Visiting Faculty Program.

The prototype DUNE 2x2 detector will capture up to 10,000 neutrino interactions per day.

They’ll work on experiments that search for dark matter particles and exotic neutrino decays that could help explain why there’s more matter than antimatter in the universe.

Four complementary analyses by Fermilab’s MicroBooNE show no signs of a theorized fourth kind of neutrino known as the sterile neutrino. Its existence is considered a possible explanation for anomalies seen in previous physics experiments.

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.

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.

Our best model of particle physics explains only about 5 percent of the universe.

SLAC researchers play an important role in the data acquisition of the largest liquid-argon neutrino detector in the world, a prototype for the future Deep Underground Neutrino Experiment.

A team of electrical designers develops specialized microchips for a broad range of scientific applications, including X-ray science and particle physics.

The event attracted 124 participants and explores the successes and challenges of the theory that describes subatomic particles and fundamental forces.