CMS

Researchers from more than 50 countries collaborate with Fermilab to develop state-of-the-art technologies and solve the mysteries of matter, energy, space and time. Take a look at 10 ways Fermilab and its partners advanced science and technology in 2021.

Whether he is on the side of a mountain or working at the Fermilab Quantum Institute, Cristián Peña likes to explore the unknown and tackle new challenges. Although he spends most of his time working on quantum communication systems for FQI, Peña dedicates time to work on the CMS experiment. His work between the two experiments, while different in practice, are conceptually similar.

Scientists from Fermilab and other institutions hoping to find new, long-lived particles at the Large Hadron Collider recently realized, with CMS, they may already have the detector to do it.

The annual Universities Research Association Thesis Award recognizes outstanding work for a thesis conducted at or in collaboration with Fermilab. Zhang’s winning Ph.D. dissertation included insights into both physics searches and equipment upgrades at the Large Hadron Collider’s CMS detector. Fermilab serves as the U.S. hub for CMS.

Fast electronics and artificial intelligence are helping physicists working on experiments with massive amounts of data, such as the CMS experiment, decide which data to keep and which to throw away.

From IRIS-HEP, April 10, 2021: Allison Hall, Fermilab LHC Physics Center researcher, is quoted in this story on the hardware upgrade to CERN’s Large LHC that will significantly boost the proton beams’ intensity.

U.S. CMS physicists from Fermilab and associated universities collaborating under the umbrella of the LPC make up a team that is the first to perform a new kind of search for “stealthy” supersymmetry that does not result in an obvious signature of large energy imbalance. Instead, the LPC team is looking for collisions that result in an unusually large number of particles in the detector. CMS recently published a briefing explaining their analysis.

Higgs-boson pairs could help scientists understand the stability of our universe. The trick is finding them.

The prodigious amount of data produced at the Large Hadron Collider presents a major challenge for data analysis. Coffea, a Python package developed by Fermilab researchers, speeds up computation and helps scientists work more efficiently. Around a dozen international LHC research groups now use Coffea, which draws on big data techniques used outside physics.

Later this decade, the Large Hadron Collider will be upgraded to the High-Luminosity LHC. What does “luminosity” mean in particle physics, and why measure it instead of collisions?