The development of quantum processors for practical fluid flow problems is a promising yet distant goal. Recent advances in quantum linear solvers have highlighted their potential for classical fluid ...

Neural tissue normally dies quickly without oxygen. Yet bird retinas—among the most energy-demanding tissues in the animal kingdom—function permanently without it. This may be relevant in future ...

This video shows how to solve algebra problems using geometry, offering a visual approach that makes abstract equations easier to understand. By translating algebra into shapes and spatial ...

Whether you're tackling business challenges, personal decisions, or technical puzzles, real-world data gives you an edge. You learn to break problems down, challenge assumptions, and find solutions ...

Artificial intelligence is consuming enormous amounts of energy, but researchers at the University of Florida have built a chip that could change everything by using light instead of electricity for a ...

What if you could transform overwhelming, disconnected datasets into a living, breathing map of relationships, one that not only organizes your data but also reveals insights you didn’t even know you ...

Abstract: Numerical Green’s functions (NGF) encapsulate the effects of complex media as pre-calculated functions, significantly reducing the number of unknowns in electromagnetic scattering problems.

A study suggests that the first of seven key pyramids in Egypt, the Step Pyramid of Djoser, was built using a hydraulic lift. Dated to about 4,500 years ago, this would move up the introduction of ...

In this Journal feature, information about a real patient is presented in stages (boldface type) to an expert clinician, who responds to the information by sharing relevant background and reasoning ...

Have you ever stared at a tangled web of Excel formulas, wondering if there’s a better way to make sense of it all? For many, Excel’s LAMBDA function feels like a cryptic puzzle—powerful but ...

According to @transformercircuits, attribution graphs have been developed as a method to address persistent challenges in AI model interpretability. Their recent publication explains how these graphs ...