Machine learning could help reveal undiscovered particles within data from the Large Hadron Collider

Scientists used a neural network, a type of brain-inspired machine learning algorithm, to sift through large volumes of particle collision data. Particle physicists are tasked with mining this massive and growing store of collision data for evidence of undiscovered particles. In particular, they’re searching for particles not included in the Standard Model of particle physics, our current understanding of the universe’s makeup that scientists suspect is incomplete.