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Atomic neighborhoods in semiconductors provide new avenue for designing microelectronics

Inside the microchips powering the device you’re reading this on, the atoms have a hidden order all their own. A team led by Lawrence Berkeley National Laboratory (Berkeley Lab) and George Washington University has confirmed that atoms in semiconductors will arrange themselves in distinctive localized patterns that change the material’s electronic behavior.

The research, published in Science, may provide a foundation for designing specialized semiconductors for quantum-computing and optoelectronic devices for defense technologies.

On the , semiconductors are crystals made of different elements arranged in repeating . Many semiconductors are made primarily of one element with a few others added to the mix in small quantities. There aren’t enough of these trace additives to cause a throughout the material, but how these atoms are arranged next to their immediate neighbors has long been a mystery.

A new approach to magnify wave functions when imaging interacting ultracold atoms

The precise imaging of many-body systems, which are comprised of many interacting particles, can help to validate theoretical models and better understand how individual particles in these systems influence each other. Ultracold quantum gases, collections of atoms cooled to temperatures close to absolute zero, are among the most promising experimental platforms for studying many-body interactions.

To study these gases, most physicists use a technique known as –resolved imaging, which allows them to detect individual atoms and probe correlations in their behavior. Despite its advantages, this imaging method has a relatively low resolution, thus it fails to pick up a system’s subtler features.

Researchers at Heidelberg University recently devised a new strategy to magnify atomic wave functions, offering a mathematical description of the system’s , which could help to overcome the limitations of conventional single-atom imaging techniques.

Theoretical model uses neuroimaging data to link brain alterations to schizophrenia

Schizophrenia is a chronic mental health disorder characterized by hallucinations, delusions, disorganized thinking and atypical movement or speech patterns. This psychiatric condition can be highly debilitating, and diagnosed individuals can report markedly different experiences.

Understanding the neurobiological basis of could be highly valuable, as it could inform the development of new interventions to reduce the risk of its emergence or treat its symptoms. The results of many neuroimaging studies carried out so far, however, were inconsistent or inconclusive, failing to clearly delineate the processes and brain regions implicated in its clinical expression.

In a recent paper published in Nature Mental Health, researchers at Taipei Medical University analyzed meta-analyses summarizing the most consistent findings of schizophrenia-related neuroimaging studies. Drawing on the results of this analysis, they developed a new theoretical model that delineates characteristic brain alterations linked to the psychiatric disorder.

Long overlooked small proteins in E. coli offer new insights into the bacteria

After the advent of antibiotics in the 1940s, scientists were certain that they were on the cusp of conquering infectious diseases, their confidence bolstered by the notion that a comprehensive knowledge of bacterial pathogens was already well documented.

Bridge recombinases, optimized for human cells, enable massive programmable DNA rearrangements

For decades, gene-editing science has been limited to making small, precise edits to human DNA, akin to correcting typos in the genetic code. Arc Institute researchers are changing that paradigm with a universal gene editing system that allows for cutting and pasting of entire genomic paragraphs, rearranging whole chapters, and even restructuring entire passages of the genomic manuscript.

Chip-scale cold atom experiments could unleash the power of quantum science in the field

Cold atom experiments are among the most powerful and precise ways of investigating and measuring the universe and exploring the quantum world. By trapping atoms and exploiting their quantum properties, scientists can discover new states of matter, sense even the faintest of signals, take ultra-precise measurements of time and gravity, and conduct quantum sensing and computing experiments.

Proven quantum advantage: Researchers cut the time for a learning task from 20 million years to 15 minutes

Amid high expectations for quantum technology, a new paper in Science reports a proven quantum advantage. In an experiment, entangled light has allowed researchers to learn a system’s noise with very few measurements.

Researchers at the Technical University of Denmark (DTU) and international partners have demonstrated that entangled light can cut the number of measurements needed to learn the behavior of a complex, noisy quantum system by an enormous factor.

“This is the first proven quantum advantage for a photonic system,” says corresponding author Ulrik Lund Andersen, a professor at DTU Physics. “Knowing that such an advantage is possible with a straightforward optical setup should help others look for areas where this approach would pay off, such as sensing and machine learning.”

Quantum random number generator combines small size and high speed

Researchers have developed a chip-based quantum random number generator that provides high-speed, high-quality operation on a miniaturized platform. This advance could help move quantum random number generators closer to being built directly into everyday devices, where they could strengthen security without sacrificing speed.

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