By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made ...

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...

Artificial intelligence has moved from crunching physics data in the background to actively proposing new theories and experiments. The hope is that these systems might finally expose cracks 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 ...

Metals are made of randomly oriented crystals at the microscopic-length scale. The alignment of the crystal faces creates an infinite number of configurations and complex patterns, making simulations ...

Parisa Khodabakhshi is an assistant professor of mechanical engineering and mechanics in Lehigh University’s P.C. Rossin College of Engineering and Applied Science. Prior to joining the Lehigh faculty ...

As artificial intelligence explodes in popularity, two of its pioneers have nabbed the 2024 Nobel Prize in physics. The prize surprised many, as these developments are typically associated with ...

In 1930, a young physicist named Carl D. Anderson was tasked by his mentor with measuring the energies of cosmic rays—particles arriving at high speed from outer space.