As a physics major, it feels like I spend the majority of my waking life solving problems. I’ve calculated the amount of water you get from mixing different ratios of steam and ice, the path of ...

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 ...

We developed a physics-informed neural network based on a mixture of Cartesian grid sampling and Latin hypercube sampling to solve forward and backward modified diffusion equations. We optimized the ...

Physics-Informed Neural Networks (PINNs) augment traditional neural architectures by embedding the governing equations of physical systems directly into the loss function. Instead of solely minimising ...