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 ...

The integration of deep learning techniques and physics-driven designs is reforming the way we address inverse problems, in which accurate physical properties are extracted from complex observations.

A line of engineering research seeks to develop computers that can tackle a class of challenges called combinatorial optimization problems. These are common in real-world applications such as ...

Using a conventional computer and cutting-edge mathematical tools and code, physicists at the Center for Computational Quantum Physics (CCQ) at the Simons Foundation's Flatiron Institute and ...

Using an advanced Monte Carlo method, Caltech researchers found a way to tame the infinite complexity of Feynman diagrams and solve the long-standing polaron problem, unlocking deeper understanding of ...

Increasingly, physics graduates take jobs outside academia. Active teaching approaches lead to deeper conceptual understanding and a more varied skill set and are therefore more likely to prepare ...

A machine-learning AI can solve physics problems by simplifying them to be more symmetric. “There are many, many cases in the history of science where people thought things were more complicated than ...

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 ...

Black physicists say efforts to recruit and retain more Black students must concentrate on challenges they face at both Historically Black Colleges and Universities and Primarily White Institutions.

Multi-physics is the new buzzword in semiconductor design and analysis, but the fuzziness of the term is a reflection of just how many new and existing problems need to be addressed simultaneously in ...