Many physics problems involve integration in multi-dimensional space whose analytic solution is not available. The integrals can be evaluated using numerical integration methods, but it requires a ...

The integration of deep learning techniques and physics-driven designs is reforming the way we address inverse problems, in which accurate physical properties are extracted from complex observations.

Solving life's great mysteries often requires detective work, using observed outcomes to determine their cause. For instance, nuclear physicists at the U.S. Department of Energy's Thomas Jefferson ...

While atmospheric turbulence is a familiar culprit of rough flights, the chaotic movement of turbulent flows remains an unsolved problem in physics. To gain insight into the system, a team of ...

Physics AI engineering simulation tools reached production at General Motors this week, cutting a two-week aerodynamics cycle ...