October 2022

Untangling quantum entanglement

An Oak Ridge-led team identifies a promising so-called entanglement witnesses to identify pairs of entangled magnetic particles.

May 2019

AI and deep learning for fusion

Princeton researchers apply deep learning to a new code, Fusion Recurrent Neural Network (FRNN), to forecast events that disrupt fusion reactions.

July 2018

Predicting magnetic explosions

Supercomputer simulations and theoretical analysis shed new light on when and how fast reconnection occurs.