News

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.

In early October, crews completed the raise-bore drilling of the vertical ventilation shaft at the Lead, South Dakota, LBNF/DUNE project site and unexpectedly uncovered a geological treasure during the process.

Olivier Napoly has worked internationally on a variety of accelerator and collider projects. At Fermilab, he works as a guest scientist, helping to build the PIP-II particle accelerator. As an accelerator physicist, Napoly focuses on every aspect of PIP-II’s construction from design to assembly.

Creating a hypersensitive dark matter detector in a clean lab more than a mile underground is no mean feat in and of itself. Add a closed border and COVID restrictions to the mix, and you have the scenario that Fermilab, SNOLAB and the SENSEI collaboration faced. Undeterred, they found a way to proceed with installation.

fSHPE offers a communal experience and cultural connection for the lab’s Hispanic members, as well as meaningful outreach opportunities.

New accelerator magnets are undergoing a rigorous training program to prepare them for the extreme conditions inside the upgraded Large Hadron Collider.

This summer, a team of scientists, engineers and technicians finished installing one of the main components that will create the strong electric field within the Short-Baseline Near Detector. Now they are getting ready to assemble the rest of the detector.

The NOvA collaboration has released the result of its latest measurement of neutrino oscillations. The results provide greater insight into neutrino properties, specifically mass ordering and charge parity symmetry.

Over time, particle physics and astrophysics and computing have built upon one another’s successes. That coevolution continues today. New physics experiments require computing innovation, including cluster computing for the Tevatron, and more recently machine learning and quantum problem-solving.