Researchers have adapted a children’s exercise program to better serve neurodivergent learners using AI-generated instructions.
To understand superconductors, researchers explore their behavior at the limits of superconductivity, such as at high temperature or under strong magnetic field. New experiments investigate superconductivity at the limits of thickness, finding unexpected vortex behavior in ultrathin films [1]. Using a high-resolution magnetic imaging technique, Nofar Fridman from the Hebrew University of Jerusalem and colleagues measured vortex sizes in superconducting samples of various thicknesses and found larger-than predicted vortices in films made up of six or fewer atomic layers. The results suggest that thin superconductors host two superconducting states: one in the bulk of the material, the other confined to the surface layers. This behavior challenges our present understanding of how superconductors behave.
When a superconductor is exposed to an external magnetic field, it generates electrical screening currents, which generate a counter magnetic field, explains team member Yonathan Anahory from the Hebrew University of Jerusalem. The net effect is the external field lines bend around the superconductor without penetrating the material.
However, the situation changes in thin superconducting films, where the material’s ability to completely expel magnetic fields is weakened. Instead of being fully excluded, the field enters the film through narrow columns, called vortices, around which superconducting screening currents flow. Inside each vortex, there is exactly one quantum of magnetic flux.
A new method for obtaining high-resolution images of cells from low-resolution ultrasound data enables longer, noninvasive monitoring of organisms.
A powerful framework allows scientists to understand and classify joint quantum measurements—procedures essential for many quantum technologies.
Two key, yet enigmatic, aspects of quantum physics are entanglement and the act of measuring a quantum system. These elements combine in unique ways in so-called joint measurements, where multiple systems are simultaneously measured in a way that accounts for their entanglement. Joint measurements are valuable because they can extract hidden information about the combined state of the systems. Remarkably, the outcome of a joint measurement can be replicated even if the systems are kept far apart, which has many practical benefits. Such “localization” procedures require local operations to be performed on each system and some extra entanglement to be shared beforehand. Now Jef Pauwels and colleagues at the University of Geneva have investigated how much of this shared entanglement is needed to localize a given joint measurement [1].
Fiber optic cable deployed on a Swiss glacier has detected the seismic signals of crevasses opening in the ice, confirming that the technology could be useful in monitoring such icequakes, according to a report at the Seismological Society of America’s Annual Meeting.
Crevassing is important to the stability of glaciers, especially as they offer a pathway for meltwater to reach the rocky glacier bed to speed up the glacier’s movement and enhance melting. The harsh environment of a crevassed glacier, however, makes it difficult to place traditional seismic instruments to measure icequakes.
The source of seismic signals in an icequake differs from the shear forces of a tectonic earthquake or the explosive source of a chemical or nuclear detonation, explained Tom Hudson of ETH Zürich. A crevasse is a “crack source, where you have pure opening of a fracture just in one direction,” he said.
Crucially, they demonstrated that the hydrogen present in this material was intrinsic, and not from contamination. This suggests that the material which our planet was built from was far richer in hydrogen than previously thought.
Scientists have unveiled a new food source designed to sustain honey bee colonies indefinitely without natural pollen.
Published in the journal Proceedings of the Royal Society B, the research from Washington State University and APIX Biosciences NV in Wingene, Belgium, details successful trials where nutritionally stressed colonies, deployed for commercial crop pollination in Washington state, thrived on the new food source.
This innovation, which resembles the man-made diets fed to livestock and pets all their lives, contains all the nutrients honey bees need. It’s expected to become a potent strategy for combating the escalating rates of colony collapse and safeguarding global food supplies reliant on bee pollination.
An international study published in Communications Earth & Environment has advanced earthquake simulations to better anticipate the rupture process of large earthquakes.
Using data for the Turkey earthquake of February 2023, the scientists have developed a detailed 3D dynamic model that provides a more accurate understanding of the strong shaking during this earthquake and hence information for future seismic hazard assessments. The research was led by King Abdullah University of Science and Technology (KAUST) Professor Martin Mai and scientist Bo Li.
The Turkey earthquake was responsible for the death of tens of thousands of people. It was marked by a doublet, which describes two major earthquakes separated by a short time. The first rupture fractured a long stretch of the fault approximately 350 km long, breaking different sections in succession. Just hours later, a second massive rupture followed, amplifying the destruction. Doublets do not show typical aftershock behavior and are a challenge to mathematically describe.
A team of researchers at UCL and UCLH have identified the key brain regions that are essential for logical thinking and problem solving.
The findings, published in Brain, help to increase our understanding of how the human brain supports our ability to comprehend, draw conclusions, and deal with new and novel problems—otherwise known as reasoning skills.
To determine which brain areas are necessary for a certain ability, researchers study patients with brain lesions (an area of damage in the brain) caused by stroke or brain tumors. This approach, known as “lesion-deficit mapping,” is the most powerful method for localizing function in the human brain.
Penn Engineers have developed the first programmable chip that can train nonlinear neural networks using light—a breakthrough that could dramatically speed up AI training, reduce energy use and even pave the way for fully light-powered computers.
While today’s AI chips are electronic and rely on electricity to perform calculations, the new chip is photonic, meaning it uses beams of light instead. Described in Nature Photonics, the chip reshapes how light behaves to carry out the nonlinear mathematics at the heart of modern AI.
“Nonlinear functions are critical for training deep neural networks,” says Liang Feng, Professor in Materials Science and Engineering (MSE) and in Electrical and Systems Engineering (ESE), and the paper’s senior author. “Our aim was to make this happen in photonics for the first time.”