Credit: Berkeley Lab
The diagram at left, which maps out particle distribution in a simulated high-energy heavy-ion collision, includes details on particle momentum and angles. Thousands of these images were used to train and test a neural network to identify important features in the images. At right, a neural network used the collection of images to created this “importance map” – the lighter colors represent areas that are considered more relevant to identify equation of state for the quark-gluon matter created in particle collisions.