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 ...

The course is devoted to analytical methods for partial differential equations of mathematical physics. Review of separation of variables. Laplace Equation: potential theory, eigenfunction expansions, ...

The mathematical physics underpinning electromagnetic fields and wave equations provides a rigorous framework for understanding the behaviour of electric and magnetic phenomena in both classical and ...

Breakthroughs in physics sometimes require an assist from the field of mathematics—and vice versa. In 1912, Albert Einstein, then a 33-year-old theoretical physicist at the Eidgenössische Technische ...

On the morning of January 13, the results of the 2009 State Top Scientific and Technological Award were announced and the award went to Gu Chaohao. Gu is an academician at the Chinese Academy of ...

Introduces ordinary differential equations, systems of linear equations, matrices, determinants, vector spaces, linear transformations, and systems of linear differential equations. Prereq., APPM 1360 ...

Modern mathematical physics was born from the attempts to gain mathematical understanding of quantum field theory and statistical mechanics. In those fields powerful new methods were developed around ...

This post originally appered in Business Insider. Mathematics is all around us, and it has shaped our understanding of the world in countless ways. 1) The Pythagorean theorem: This theorem is ...

Work with experts to tackle some of the biggest ideas in science and expand your understanding of advanced mathematical tools. Apply now for 2026 entry or register your interest to find out about ...