A new report outlines suggestions for federal investments needed for the next generation of transformative discoveries in particle physics and cosmology, including priority projects at SLAC.

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.

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.

Tais Gorkhover, Michael Kagan, Kazuhiro Terao and Joshua Turner will each receive $2.5 million for research that studies fundamental particles, nanoscale objects, quantum materials and machine learning.

This neutrino-watchers season preview will give you the rundown on what to expect to come out of neutrino research in the coming years.

The accomplished particle physicist will prepare the lab for its role in DUNE, a next-generation experiment designed to demystify neutrinos and their fundamental role in the universe.

Scientists are using cutting-edge machine-learning techniques to analyze physics data.