A new review in Nature chronicles the many ways machine learning is popping up in particle physics research. Experiments at the Large Hadron Collider produce about a million gigabytes of data every ...

As particle accelerator technology moves into the high-luminosity era, the need for extreme precision and unprecedented collision energy keeps growing. Given also the Laboratory's desire to reduce ...

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 ...

A team of scientists has devised a machine learning algorithm that calculates, with low computational time, how the ATLAS detector in the Large Hadron Collider would respond to the ten times more data ...

Scientists have developed a new machine-learning platform that makes the algorithms that control particle beams and lasers smarter than ever before. Their work could help lead to the development of ...

Operators of the primary particle accelerator at the U.S. Department of Energy's Thomas Jefferson National Accelerator Facility are getting a new tool to help them quickly address issues that can ...

A team of scientists at DoE’s SLAC National Accelerator Laboratory has invented a new type of particle accelerator that delivers 10 times the energy gain over a given distance compared to current ...

A machine that will investigate the forces that hold matter together finally has a home. On Thursday, the US Department of Energy announced that the long-awaited Electron-Ion Collider (EIC), a type of ...

Operators of Jefferson Lab's primary particle accelerator are getting a new tool to help them quickly address issues that can prevent it from running smoothly. The machine learning system has passed ...