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.

As enrollment numbers for the introductory chemistry and physics courses reach around 600 students each this semester, the need to understand how students learn in STEM classes only becomes more ...

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 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 ...

Artificial intelligence has moved from crunching physics data in the background to actively proposing new theories and ...

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 ...

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 ...

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 ...

Any Cornell student who has taken physics class may have wondered at some point: “what makes physics so difficult to understand?” While students may be asking this out of frustration, Prof. Paula ...