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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.
Scientists are testing the components and systems for the international Deep Underground Neutrino Experiment, hosted by Fermilab, with other liquid-argon particle detectors. One such detector is ICEBERG, which is over 10,000 times smaller than DUNE will be. ICEBERG’s measurements are providing insight for future neutrino experiments.
Tiffenberg shares the $100,000 prize for advances in dark matter detection technology. He and collaborators on the SENSEI experiment drove the development of innovative sensors called skipper CCDs, which are sensitive enough to be able to pick up signals from dark matter particles of low mass.
Humans and robots work together in a carefully choreographed dance to maintain peak production target performance in Mu2e’s search for new physics – direct muon-to-electron conversion.
The U.S. Department of Energy has selected Lawrence Berkeley National Laboratory to lead a DOE/NSF experiment that combines observatories at the South Pole and in Chile’s high desert. Fermilab plans to be a key partner on the experiment, called CMB-S4, which aims to undertake an unprecedented survey of the early universe.
Fermilab has been selected to lead one of five national centers to bring about transformational advances in quantum information science as a part of the U.S. National Quantum Initiative. The initiative provides the new Superconducting Quantum Materials and Systems Center — based at Fermilab and comprising 20 partner institutions — $115 million over five years with the goal of building and deploying a beyond-state-of-the-art quantum computer based on superconducting technologies. The center will also develop new quantum sensors, which could lead to the discovery of the nature of dark matter and other elusive subatomic particles.
The international Deep Underground Neutrino Experiment collaboration has published a paper about its capability for performing supernova physics. It details the kind of activity DUNE expects in the detector during a supernova burst, how DUNE will know once a supernova occurs and what physics DUNE will extract from the neutrinos. DUNE’s unique strength is its sensitivity to a particular type of neutrino called the electron neutrino, which will provide scientists with supernova data not available from any other experiment.
The MINOS+ and Daya Bay neutrino experiments combine results to produce most stringent test yet for the existence of sterile neutrinos.
Cornell University postdoc David Sweigart has won the 2020 URA Thesis Award for his dissertation analyzing the first year’s data from Fermilab’s Muon g-2 experiment. His efforts in analyzing the anomalous precession frequency of the muon could help confirm or challenge the Standard Model of particle physics.
Scientists on the Dark Energy Survey have used observations of the smallest known galaxies to better understand dark matter, the mysterious substance that makes up 85% of the matter in the universe. The smallest galaxies can contain hundreds to thousands of times more dark matter than normal visible matter, making them ideal laboratories for studying this mysterious substance. By performing a rigorous census of small galaxies surrounding our Milky Way, scientists on the Dark Energy Survey have been able to constrain the fundamental particle physics that governs dark matter.