Machine learning is becoming an essential part of a physicist’s toolkit. How should new students learn to use it? When Radha Mastandrea started her undergraduate physics program at MIT in 2015, she ...

For grid-scale energy storage and national energy resilience, the U.S. needs better batteries. Lawrence Livermore National ...

Researchers at The University of Manchester have developed a new computational approach to help identify two-dimensional ...

Machine learning can get a boost from quantum physics. On certain types of machine learning tasks, quantum computers have an exponential advantage over standard computation, scientists report in the ...

See more of our trusted coverage when you search. Prefer Newsweek on Google to see more of our trusted coverage when you search. John Hopfield and Geoffrey Hinton were awarded the 2024 Nobel Prize in ...

A team of scientists at Los Alamos National Laboratory is applying machine-learning algorithms to subsurface imaging that will impact a variety of applications, including energy exploration, carbon ...

Researchers employ machine learning to more accurately model the boundary layer wind field of tropical cyclones. Conventional approaches to storm forecasting involve large numerical simulations run on ...

For more than 20 years in experimental particle physics and astrophysics, machine learning has been accelerating the pace of science, helping scientists tackle problems of greater and greater ...

Image courtesy by QUE.com For decades, the search for room-temperature superconductors has been one of physics' most ...

The Nobel Prize in physics has been awarded to John J. Hopfield of Princeton University and Geoffrey E. Hinton of the University of Toronto for discoveries and inventions that formed the building ...