Artificial intelligence (AI) systems, particularly artificial neural networks, have proved to be highly promising tools for ...

Differential equations are fundamental tools in physics: they are used to describe phenomena ranging from fluid dynamics to general relativity. But when these equations become stiff (i.e. they involve ...

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 ...

One of the most stubborn problems in physics today is the fact that our two best theories to explain the Universe – general relativity and quantum mechanics – function perfectly well on their own, but ...

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Researchers trained a machine learning tool to capture the physics of electrons moving on a lattice using far fewer equations than would typically be required, all without sacrificing accuracy. Using ...

"Even the +, −, =, and x signs we take for granted only came into widespread use in the 17th century. Which means that the earlier algebraists we know of … all had expressed their equations mostly in ...

Werner Heisenberg won the 1932 Nobel Prize for helping to found the field of quantum mechanics and developing foundational ideas like the Copenhagen interpretation and the uncertainty principle. The ...