From Wired, July 16, 2023: The use of a machine learning tool known as sparse convolutional neural network is now being used by researchers to accelerate real-time data analysis. SCNNs have been used in simulations of the data expected from DUNE and analyzed the simulated data faster than ordinary methods while requiring significantly less computational power.
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Particle physicists are building innovative machine-learning algorithms to enhance Monte Carlo simulations with the power of AI.
From the Black Hills Pioneer, July 7, 2023: Over 2,000 people in Lead, South Dakota celebrated Neutrino Day on July 8, organized by the Sanford Underground Research Facility with LBNF and DUNE members participating. The event featured a science comedian, interactive science booths, virtual underground tours as well as speakers on renewable energy and the Long Baseline Neutrino Facility for DUNE.
A large number of scientists are working on improving the Standard Model prediction of the value of muon g-2 using new data and new lattice calculations. By measuring and calculating this number to ultra-high precision, scientists can test whether the Standard Model is complete.
Using superconducting nanowires and cryogenic electronics, experts from different fields combine their know-how to develop a completely new type of particle detector. The goal: detect particles in ultracold environments, even in the presence of strong magnetic fields where other technologies fail.
During a routine test, two HL-LHC magnets unexpectedly flatlined. Was it just a coincidence, or did they have a common foe?
More than 70% of the excavation of the South Dakota portion of the Long-Baseline Neutrino Facility for the Deep Underground Neutrino Experiment is complete. Preparations for turning the huge caverns into usable laboratory space are underway.
While studying at the University of Manchester, Green analyzed data from a liquid argon neutrino detector at Fermilab, developing new techniques to identify muons that would hint at new particles.
Jonathan Jarvis, head of Fermilab’s Accelerator Research Department, received the University Research Association’s 2023 Early Career Award for his work experimentally demonstrating optical stochastic cooling.
From Phys.org, July 5, 2023: Researchers from Ames Laboratory announced important research results done with Fermilab’s SQMS Center that will improve the quantum circuit quality of a vital qubit component. The research was an important step in quantum computing development and proves that collaborative research groups like SQMS with Ames can lead to solving very complex technological and scientific problems.