News

For a few days, teachers work with real-world physics data to figure out how to bring particle physics back to their classrooms during the QuarkNet Data Camp, an annual workshop for educators at Fermilab.

Unseen neutrinos, visible lives: A photographer journeys through the Midwest.

Fermilab’s Silvia Zorzetti has been awarded the prestigious Early Career Award from the U.S. DOE for her pioneering research in developing technology that will lay the foundations of the quantum internet. The project’s goal is to improve quantum sensors and sensor networks, so as to allow a more efficient conversion of information and quantum signals between different physical platforms

DOE announced $24 million in funding for three collaborative projects in quantum network research to realize distributed quantum computers. A project included in this funding is collaborative research led by Fermilab in partnership with the California Institute of Technology, the University of Illinois-Urbana-Champaign, the Northwestern University, and Argonne National Laboratory, to develop hyper-entanglement-based networking and error noise-robust correction techniques for developing advanced quantum networks for science discovery.

What is the future of muon colliders? Particle physicists are seeing less challenges in their development than ten years go and are pushing for a muon collider as the P5 report comes out this fall.

Forty years after its discovery, the W boson continues to intrigue scientists. Chris Hays describes recent progress in understanding a surprisingly high measurement of its mass using data from the former CDF experiment at Fermilab.

Current understandings of neutrino-nucleon interactions rely on data from experiments in the 1970s and ’80s. However, by using lattice quantum chromodynamics to predict stronger neutrino-nucleon interactions, scientists can determine oscillation properties of the elusive neutrinos in Fermilab’s DUNE experiment and other neutrino oscillation experiments.

The Bird Conservation Network recently shared its findings from 22 years of surveying bird populations throughout the Chicago area and compared their data to Fermilab’s decades-long bird monitoring data.

The Rubin Observatory is making education and outreach a top priority.

Scientists are using a new machine learning tool called sparse convolutional neural networks, or SCNNs, to analyze data faster and more efficiently than ever before. SCNNs are expected to play a critical role in analyzing the data gathered from the upcoming DUNE experiment.