CMS

The Fermilab LHC Physics Center and Northwestern University recently hosted about 40 participants – experimentalists at the LHC experiments and theorists — for a two-day workshop titled “Multibosons at the Energy Frontier.” Discussions focused on strategies to best exploit the LHC data in the study of multiboson events.

For years, U.S. institutions have been working to upgrade the hardware in the behemoth CMS particle detector at the Large Hadron Collider, enabling it to profit fully from the LHC’s increasing collision energy and intensity. With CD-4 approval, the Department of Energy formally recognized that the USCMS collaboration, managed by Fermilab, met every stated goal of the upgrade program — on time and under budget.

A new machine learning technology tested by Fermilab scientists and collaborators can spot specific particle signatures among an ocean of LHC data in the blink of an eye, much faster than standard methods. Sophisticated and swift, its performance gives a glimpse into the game-changing role machine learning will play in making future discoveries in particle physics as data sets get bigger and more complex.

Fermilab runs several vibrant programs aimed at educating students of all ages in all of our myriad technical endeavors, be they scientific, engineering or computational. All departments participate in these programs, but the CMS Department was especially luckily this summer. We were able to attract over a dozen exceptional young interns who participated in a broad swath of CMS activities, spanning analysis, detector upgrades and computer infrastructure.

A pioneer in particle physics and high-performance computing, Fermilab has launched HEPCloud, a cloud computing service that will enable the lab’s demanding experiments to make the best, most efficient use of computing resources. This flagship project lets experiments rent computing resources from external sources during peak demand, reducing the costs of providing for local resources while also providing failsafe redundancy.