Machine learning has emerged as a powerful tool in condensed matter physics, offering new perspectives on the exploration of quantum many-body systems, phase transitions and exotic states of matter.

Two teams have shown how quantum approaches can solve problems faster than classical computers, bringing physics and computer science closer together. For Valeria Saggio to boot up the computer in her ...

image of Winners of the 2024 Nobel Prize in Physics, John J. Hopfield (left) and Geoffrey E. Hinton. Winners of the 2024 Nobel Prize in Physics, John J. Hopfield (left) and Geoffrey E. Hinton. Credit: ...

Two scientists have been awarded the Nobel Prize in Physics “for foundational discoveries and inventions that enable machine learning with artificial neural networks.” John Hopfield, an emeritus ...

Teaching artificial intelligence to understand simple physics concepts, such as that one solid object can’t occupy the same space as another, could lead to more capable software that takes less ...

Understanding the quantum universe is not an easy thing. Intuitive notions of space and time break down in the tiny realm of subatomic physics, allowing for behavior that seems, to our macro ...

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 ...

In his years as a physics teacher, students often asked Mark Whalley why they had to learn the subject when most of them would never directly use it in their careers. Having never been satisfied with ...

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 ...