data analysis

A team from Northern Illinois University isy part of the 1,400 scientists and engineers working on the Deep Underground Neutrino Experiment. In the coming year, they will be responsible for making 300 to 400 of the photon detection modules that will be part of the much larger web of thousands of such modules at the underground Long-Baseline Neutrino Facility in South Dakota.

Scientists are using a new machine learning tool called sparse convolutional neural networks, or SCNNs, to analyze data faster and more efficiently than ever before. SCNNs are expected to play a critical role in analyzing the data gathered from the upcoming DUNE experiment.

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.

From Quanta Magazine, June 8, 2023: A new novel network called sparse convolutional neural network is helping physicists accelerate the daunting challenge of data analysis. It provides the ability to focus on the relevant parts of data and screen out the rest. This is a historic change for the physics community and learn how it can be used in DUNE when the projects starts data later this decade.