The machine learning tool is helping physicists with the daunting challenge of analyzing large but nearly empty data sets, like those from neutrino detectors or particle colliders.
for the first SCNN, which centered the kernel only on pixels that had a nonzero value . It was this general idea that Terao brought to the world of particle physics.Terao is involved with experiments at the Fermi National Accelerator Laboratory that probe the nature of neutrinos, among the most elusive known elementary particles. They’re also the most abundant particles in the universe with mass , but they rarely show up inside a detector.
The SCNNs analyzed the simulated data faster than ordinary methods, and required significantly less computational power in doing so. The promising results mean that SCNNs will likely be used during the actual experimental run.
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