Neuromorphic computers modeled after the human brain can now solve the complex equations behind physics simulations — something once thought possible only with energy-hungry supercomputers. The ...

The currents of the oceans, the roiling surface of the sun, and the clouds of smoke billowing off a forest fire—all are ...

The team used an AI method known as equation discovery to develop a model to simulate the interactions between small eddies—circular, vortex-like currents—and large-scale ones. These interactions are ...

While it's no replacement for either computer, the new device is a powerful alternative for addressing some very practical ...

During the 2026 Winter Olympics, athletes will leap off ramps, slide across ice and spin through the air. These performances will look different to my students who have studied physics through ...

For nearly a century, some of the simplest questions in quantum theory have stubbornly resisted clean answers, turning basic ...

This puzzle is known as the problem of time, and it remains one of the most persistent obstacles to a unified theory of ...

Abstract: One of the primary objectives of 2-D inverse scattering problems (ISPs) is to accurately characterize the nature of an unknown tomographic domain based on the collected scattered field data.

Abstract: Physics-informed neural networks (PINNs) have shown their potential for solving direct problems in many engineering domains including electromagnetics. We employ fully connected and ...

What began as a disagreement over a basic physics concept quickly escalated into a $10,000 wager. The bet wasn’t about ego, but about confidence in long-accepted assumptions. As the argument unfolded, ...