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Rare quantum state reveals particles with quarter-electron charge

An electron’s charge is normally fixed, like a coin you can’t break into pieces. But if electrons are cooled close to absolute zero and trapped in a two-dimensional layer under a powerful magnetic field, they organize into a collective state of “quasiparticles” that seem to hold only a fraction of an electron’s charge.

This state is known as the “fractional quantum Hall effect.” A small number of these states, known as “even-denominator states,” have drawn attention because some theories predict they could contain unusual quasiparticles called “non-Abelian anyons.”

Why are these interesting? Because their quantum properties make them candidates for storing and processing information in fault-tolerant (error-resistant) topological quantum computers.

Random access quantum memory lets one processor select among seven storage cells

Classical computers can temporarily store the information required to perform specific tasks in a short-term memory component known as RAM (random access memory). This component allows computer processors to retrieve information from a chosen location without searching through all stored data.

Yet most current superconductor-based quantum computers do not have a separate RAM-like component. This is because while processors and memory components are separate in classical computers, most superconducting quantum computers rely on the same hardware for storing and processing information.

Researchers at Stanford University, University of Chicago, the SLAC National Accelerator Laboratory and other institutions have designed a new device that could serve as a random access quantum memory. Their device, presented in a paper published in Nature Physics, could pave the way for quantum computers with separate memory components and fewer signal-carrying connections.

Ultrathin materials could make quantum light circuits programmable

Quantum photonics could be a pivotal part of future quantum technology if the right materials can be created, a new review paper has found.

Photonics offers an approach to developing quantum technology using light. The authors believe a programmable photonic platform could enable technologies such as quantum neural networks and distributed quantum computing.

Many photonic components already exist and can be integrated onto a single silicon chip. The challenge is to put them together in a way that can be manipulated efficiently. Today’s technology is mostly fixed once manufactured.

Discovery confirms rare, switchable electrical property in widely used electronics material

A Husker research team’s latest research could open the door to broader use of a class of materials whose electrical properties may someday power next-generation electronics, high-density energy storage, improved computer memory and new strategies for cooling.

In a new paper published in Science, University of Nebraska–Lincoln researchers Xiaoshan Xu, Alexei Gruverman and Evgeny Tsymbal demonstrate that hafnium oxide—a tough, heat-resistant chemical compound used widely in modern electronics—is inherently antiferroelectric, a rare quality found in very few materials. Unlike hafnium oxide, also known as hafnia, many intrinsically antiferroelectric materials contain the toxin lead, which limits their widespread use.

The trio said the discovery will help settle a longstanding debate about hafnia’s properties. Though scientists have long observed the material’s antiferroelectric behavior, they have disagreed on whether it results from “true” antiferroelectricity or from an artificial effect stemming from the entrapment or redistribution of electrical charges.

How to balance quantum batteries’ high power with stable energy delivery

Quantum batteries are an emerging area of research, with progress coming from theoretical studies and proof-of-principle experiments in small quantum systems. Unlike conventional chemical batteries used in everyday life, they use quantum systems to store and transfer energy. Researchers are exploring them as potential future energy sources for quantum processors and other quantum technologies.

Previous research has focused mainly on how fast and powerfully quantum batteries can be charged. In new research, the researchers establish fundamental limits on fluctuations in both the energy delivered by a quantum battery and the rate at which it is delivered.

The work, “Fundamental Limitations on the Reliabilities of Power and Work in Quantum Batteries,” was published in PRX Quantum.

When microbial DNA is scarce, new profiling method helps separate genuine signals from contamination

In acute, life-threatening infections, rapidly characterizing the microorganisms in a patient sample can help guide diagnosis and treatment. Computational methods known as taxonomic profilers can analyze metagenome sequencing data generated from the microorganisms’ genomic information and compare it with reference genomes of individual microorganisms. However, taxonomic profilers are still under development and are not yet in common use. Current methods can produce false-positive results or inaccurate abundance estimates.

Researchers at the Helmholtz Centre for Infection Research (HZI) have developed a new taxonomic profiler called Metax. By using information about how sequencing reads are distributed across microbial reference genomes, Metax can distinguish true microbial signals from artifacts more reliably and improve both taxonomic identification and abundance estimation. The study was published in the journal Cell.

“In clinical samples, for example, microbial profiling can provide important information about microorganisms that may be relevant for an infection,” explains Alice McHardy, a professor and head of the research group “Computational Biology for Infection Research” at HZI. “Such information can complement established diagnostic approaches and help researchers and clinicians investigate potential pathogens. But taxonomic profiling is equally important far beyond clinical applications, from human microbiome research to environmental monitoring.”

Saltwater sensor turns touch into electrical signals like skin, with prosthetic potential

You pick up a fragile glass from the table. Without thinking about it, you feel its surface against your fingertips and continuously adjust your grip. You hold it firmly enough to keep it from slipping out of your hand, but not so tightly that it breaks.

For you, this is a simple maneuver. But beneath the skin, you set off a sophisticated interplay of processes. The pressure from your fingertips opens tiny gates in the skin’s sensory cells, allowing electrically charged atoms to flow in. This shifts the electrical balance and triggers a nerve signal that travels toward the brain. There, the signal becomes part of the information that allows you to feel the touch and continuously adjust your grip.

Clever.

Self-powered artificial synapse combines sensing and memory in flexible electronics

Neuromorphic devices, which are designed to emulate aspects of biological neural networks, are promising candidates for low-power, intelligent sensing technologies, including wearable applications.

Among the architectures explored for neuromorphic computing, graphene-channel ion-gel-gated transistors (g-IGTs) are attractive because of their electronic properties, flexibility, low-voltage operation and ability to modulate synaptic weights to mimic biological synapses. However, most current g-IGTs still rely on external power supplies, limiting their practical use in wearable neuromorphic systems.

To address this challenge, a research team led by professor Sejoon Lee of the Department of System Semiconductor at Dongguk University in South Korea has developed a battery-free, self-powered, flexible g-IGT device driven by a triboelectric nanogenerator (TENG). TENGs convert mechanical stimuli, such as body movement, touch or vibration, into electrical signals.

Pressurized wind tunnel experiments could help wind farms generate more power

The world needs more wind energy. But anyone designing new wind turbines or trying to squeeze more power out of existing ones faces a stiff challenge when testing new approaches. That’s because the atmosphere is a tough place for a controlled experiment.

Some researchers use wind tunnels to conduct tests, but tests of scaled-down wind turbines in traditional wind tunnels can differ widely from field conditions. (Wind turbines are the largest rotating machines ever made.) The problem hampers not only the development of better wind turbines but also our understanding of basic questions like how much power to expect from a turbine when winds change direction.

In a new open-access paper published in PNAS Nexus, researchers closed the gap between experiments in the field and the lab by using a highly pressurized wind tunnel to simulate the flow physics of the atmosphere. With this approach, the researchers determined how the turbine’s alignment and its tip speed relative to the wind influence the power it generates, offering new insights into how to get more power from existing wind farms.

Misleading AI-generated summaries can distort human memory

AI-generated summaries are becoming increasingly prevalent—from news article previews to workplace meeting transcriptions to high-stakes settings like police body camera footage—despite studies showing that AI can generate misleading or inaccurate information.

A new study from a team of researchers at Georgetown University and the University of Washington suggests that when prompted to summarize a video, AI systems that produce incorrect information can manipulate people’s memory and perceptions of truth.

The study, “AI-Enabled Human Memory Manipulation: Misleading AI-Generated Summaries Distort Human Memory,” was published on the preprint server arXiv and will be presented at the Ninth AAAI/ACM Conference on AI, Ethics and Society (AIES), taking place in October 2026.

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