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.

Solving life's great mysteries often requires detective work, using observed outcomes to determine their cause. For instance, nuclear physicists at the U.S. Department of Energy's Thomas Jefferson ...

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 ...

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 ...

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 ...

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 ...

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.