Berkeley Lab Cosmologists Are Top Contenders in Machine Learning Challenge

The 2020 LHC Olympics challenged teams to develop a machine learning code to find a hidden signal in particle-collision data. This image shows particle-collision data captured by the ATLAS detector at CERN's Large Hadron Collider. In searching for new particles, physicists can lean on theoretical predictions that suggest some good places to look and some good ways to find them: It's like being handed a rough sketch of a needle hidden in a haystack. But blind searches are a lot more complicated, like hunting in a haystack without knowing what you are looking for. To find what conventional computer algorithms and scientists may overlook in the huge volume of data collected in particle collider experiments, the particle physics community is turning to machine learning, an application of artificial intelligence that can teach itself to improve its searching skills as it sifts through a haystack of data.