The Deep Underground Neutrino Experiment led by Fermilab is included in the line up of most ambitious international science projects that demonstrates how modern science transcends borders and inspires new technologies.

NVIDIA announced an expansion of the NVIDIA CUDA-Q open source platform with CUDA-Q Logical, a verifiable approach to developing useful applications for fault-tolerant quantum computers. Fermilab researchers used the platform accelerating fault-tolerant algorithm development from five months to three weeks, a 7x speedup.

Rice University’s DUNE-TECH program introduces undergraduates to the science behind DUNE, one of the nation’s most ambitious physics experiments.

A novel underwater detection experiment will continue Minnesota’s legacy of neutrino research. The Lake Vermillion neutrino detector experiment is being led by Fermilab.

Gustavo Cancelo, senior scientist at Fermilab near Chicago talks about QICK, the Quantum Instrumentation Control Kit, an open source platform developed at Fermilab that has become a widely adopted tool for quantum control and readout across four continents.

Fermilab has refined measurements of the muon’s anomalous magnetic moment by focusing on where these calculations begin at the detector. The team achieved results more consistent with existing theoretical predictions without confirming new physics.

Tyler Barrett, Charis-Kleio Koraka, Kevin Kelly and Silvia Zorzetti are the recipients of the 2026 URA Honorary Awards. The awards are presented each year by Universities Research Association to recognize significant contributions to research at Fermilab.

Fermilab’s recent reorganization brings its accelerator, physics and technology programs under three unified directorates, each charged with advancing the laboratory’s most important scientific priorities. Together, these directorates form a coordinated leadership structure designed to deliver world class research and guide Fermilab’s future.

In a project selected for funding by the Department of Energy’s Genesis Mission, Fermi National Accelerator Laboratory and partners from other national laboratories, universities and industry will apply artificial intelligence and machine learning to enable precise and adaptive resonance control in particle accelerators. Their work aims to lower operating costs by millions of dollars each year and improve accelerator performance, driving scientific discovery.

Researchers at Fermilab, Stanford University and the University of Delaware recently showed that one of the oldest precision experiments performed by physicists could also be used to search for millicharged particles.