Physics-informed neural networks (PINNs) represent a burgeoning paradigm in computational science, whereby deep learning frameworks are augmented with explicit physical laws to solve both forward and ...

Complex network theory has become a key analytical framework in modern physics for studying structure, dynamics, and emergent behaviour in complex systems.

Lowry Kirkby reviews The Theoretical Minimum: What You Need to Know to Start Doing Physics by Leonard Susskind and George Hrabovsky Thirst for physics: Leonard Susskind's popular series of lectures ...

Artificial intelligence (AI) systems, particularly artificial neural networks, have proved to be highly promising tools for uncovering patterns in large amounts of data that would otherwise be ...

What is the Stokes-Einstein Equation? The Stokes-Einstein equation is a fundamental relation in physics that describes the diffusion of spherical particles through a fluid with low Reynolds number. It ...

Equations are ordered, elegant mathematical constructs used to describe specific patterns. Can you imagine some formulas depict the very opposite: chaos and randomness? What's more intriguing, they ...

A team of physicists from the University at Buffalo has developed a user-friendly method that allows researchers to solve complex quantum problems, once thought to require massive supercomputers, on ...

Maxwell’s equations of electromagnetism and the Euler equation top a poll to find the greatest equations of all time. Robert P Crease discusses the results of his reader survey First among equals – ...