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

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

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

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 ...

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 ...

In 1930, a young physicist named Carl D. Anderson was tasked by his mentor with measuring the energies of cosmic ...

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 ...

The field of particle physics is approaching a critical horizon defined by challenges including unprecedented data volumes and detector complexity. Upcoming ...

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 ...

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 ...