Matter and antimatter particles can behave differently, but where these differences show up is still a puzzle. Scientists on the LHCb experiment at the Large Hadron Collider study much more subtle differences between matter particles and their antimatter equivalents. A recent analysis allowed them to revisit an old mystery — an asymmetry between asymmetries.
From Phys.org, Dec. 7, 2020: The CMS collaboration, a worldwide group of scientists studying particle collisions at CERN’s Large Hadron Collider, has recently observed the production of three massive gauge bosons in proton-proton collisions for the first time ever. Northwestern University postdoc and Fermilab Distinguished Researcher Saptaparna Bhattacharya talks about the triboson search.
When two heavy ions collide inside a particle accelerator, they produce a near-perfect fluid through which an assortment of fundamental particles swim. For scientists to accurately simulate even a tiny drop of this hot and dense subatomic brew with a classical computer, it would take longer than the age of the universe. Scientists show how quantum computing could be a game-changer in our understanding of quantum processes.
More than 3,500 researchers from around the world collaborate with Fermilab to develop state-of-the-art technologies and solve the mysteries of matter, energy, space and time. Here is a look at 10 ways Fermilab advanced science and technology in 2020.
From the CMS collaboration, Nov. 30, 2020: On Nov. 24, the CMS collaboration at CERN’s Large Hadron Collider announced the publication of the 1,000th paper in a peer-review journal, an exceptional achievement for a single experiment. Fermilab scientist Boaz Klima, CMS Publications Committee chair, is quoted.
A recent observation of an extremely rare subatomic process allows scientists to test the Standard Model’s boundaries.
As you can see on the side of the orange magnets, Fermilab and KEK provided these spare quadrupoles for the Large Hadron Collider.
Fermilab scientists have implemented a cloud-based machine learning framework to handle data from the CMS experiment at the Large Hadron Collider. Now they can begin to use graph neural networks to boost their pattern recognition abilities in the search for new particles.
Particle accelerators like the LHC require intricate beam dump systems to safely dispose of high-energy particles after each run.
Scientists on an experiment at the Large Hadron Collider see massive W particles emerging from collisions with electromagnetic fields. How can this happen?