The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

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 ...

A particle collision reconstructed using the new CMS machine-learning-based particle-flow (MLPF) algorithm. The HFEM and HFHAD signals come from the ...

Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...

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 ...

The volume of data particle physicists have to sort through at the Large Hadron Collider is staggering, and it’s about to increase by an order of magnitude. To cope with this torrent of data, CERN is ...

There have been many attempts at teaching robots how to grab delicate objects, but they tend to rely on rough approximations that quickly fall apart in real life. MIT researchers may have a better ...

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 ...