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This award, totaling $2.5 million, will fund the development of a faster particle beam cooling method as well as the implementation of machine learning advancements to optimally control the system.

Fermilab has been selected to lead one of five national centers to bring about transformational advances in quantum information science as a part of the U.S. National Quantum Initiative. The initiative provides the new Superconducting Quantum Materials and Systems Center $115 million over five years with the goal of building and deploying a beyond-state-of-the-art quantum computer based on superconducting technologies.

Scientists are investigating how to equip quantum computers with artificial intelligence and machine learning approaches.

In the First-Person Science series, scientists describe how they made significant discoveries over years of research. Chris Polly is a physicist at the Department of Energy's Fermilab and co-spokesperson for the Muon g-2 project.

Scientists are preparing for the increased brightness and resolution of next-generation light sources with a computing technique that reduces the need for human calculations to reconstruct images.

A new artificial neural network model, created by Argonne scientists, handles both static and dynamic features of a power system with a relatively high degree of accuracy.

The international Deep Underground Neutrino Experiment collaboration has published a paper about its capability for performing supernova physics. It details the kind of activity DUNE expects in the detector during a supernova burst, how DUNE will know once a supernova occurs and what physics DUNE will extract from the neutrinos. DUNE's unique strength is its sensitivity to a particular type of neutrino called the electron neutrino, which will provide scientists with supernova data not available from any other experiment.

The MINOS+ and Daya Bay neutrino experiments combine results to produce most stringent test yet for the existence of sterile neutrinos.