The largest neutrino experiment in the United States was named the Project of the Year by the Underground Construction Association for completing a significant and challenging underground construction project with little or no issues.

A 2022 measurement of the W boson’s mass by the CDF experiment at the Fermilab, while the most precise measurement, differed from the Standard Model prediction. Now, a new calculation of the W boson particle by the CMS collaboration agrees with the Standard Model.

A team of researchers from Fermilab, University of Chicago, Stanford University, and New York University
have developed an electronically-tunable quantum detector that significantly speeds up the search for dark photons, a leading candidate for dark matter.

Researchers at Argonne have successfully commissioned a “giant cage” detector capable of filtering out 99.99% of cosmic background noise for the Mu2e experiment at Fermilab.

Argonne researchers commissioned a device that filters out background signals in the Mu2e experiment at Fermilab, which seeks to observe a rare particle physics process. Such an observation would fundamentally change our understanding of the universe.

Chris Edwards, an Engineering Project Manager at Fermilab, discusses the collaboration with Proficio, utilizing Fermilab’s electron-beam technology to develop methods for treating water contaminated with PFAS.

Researchers at the Illinois Accelerator Research Center at Fermilab have developed powerful, compact, and mobile electron accelerators powered by SRF technologies. A compact SRF accelerator
is a cost-effective, compact version that will enable novel applications.

Fermilab and Stanford University researchers have developed XCOM, a novel network designed to synchronize quantum instrumentation and facilitate low-latency communication.

A new network architecture from Fermilab targets a key challenge in scaling quantum computing systems: low-latency, predictable communication across control hardware. The XCOM system connects multiple QICK boards in a mesh network, enabling synchronized operation and deterministic communication between distributed control electronics.

Rice University recently hosted an international workshop focused on integrating cutting-edge AI and ML technologies for the DUNE project led by Fermilab. Rice’s BioScience Research Collaborative collaborators to tackle the monumental computational challenges posed by DUNE and to strategize on leveraging AI’s transformative capabilities within the field of particle physics.