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Controlling quantum states in germanene using only an electric field

Researchers at the University of Twente and Utrecht University demonstrated for the first time that quantum states in the ultra-narrow material germanene can be switched on and off using only an electric field. The researchers were able to vary the electric field strength very precisely, causing the special ‘topological’ states in nanoribbons to disappear or appear.

The research, titled “Electric-Field Control of Zero-Dimensional Topological States in Ultranarrow Germanene Nanoribbons,” is published in Physical Review Letters.

Quantum computers will not use zeros and ones, but instead use quantum bits that can assume both states simultaneously. In theory, this makes them superfast and powerful, but in practice, building quantum bits is an enormous challenge: they are very sensitive to noise and quickly lose their information.

Calibrating qubit charge to make quantum computers even more reliable

Quantum computers will be able to assume highly complex tasks in the future. With superconducting quantum processors, however, it has thus far been difficult to read out experimental results because measurements can cause interfering quantum state transitions.

Researchers at Karlsruhe Institute of Technology (KIT) and Université de Sherbrooke in Québec have performed experiments that improve our understanding of these processes and have shown that calibrating the charge at the qubits contributes to fault avoidance.

Their findings have been published in Physical Review Letters.

New digital state of matter could help build stable quantum computers

Scientists have taken another major step toward creating stable quantum computers. Using a specialized quantum computer chip (an essential component of a quantum computer) as a kind of tiny laboratory, a team led by Pan Jianwei at the University of Science and Technology of China has created and studied a rare and complex type of matter called higher-order nonequilibrium topological phases.

This digital matter (not conventional physical material) is unique because its key behaviors are super-stable and located only at its corners. But this stability is only maintained when the material is constantly bombarded with energy pulses.

The work is a big deal because it shows that quantum computers can be used as reliable simulators to discover and test new stable forms of matter. This will be necessary if scientists are to create quantum computers that never break down (or are at least highly reliable), because super-stable corner behaviors are the kind of error-proof properties needed to build trustworthy quantum hardware.

Natural language found more complex than it strictly needs to be—and for good reason

Human languages are complex phenomena. Around 7,000 languages are spoken worldwide, some with only a handful of remaining speakers, while others, such as Chinese, English, Spanish and Hindi, are spoken by billions. Despite their profound differences, they all share a common function: they convey information by combining individual words into phrases—groups of related words—which are then assembled into sentences. Each of these units has its own meaning, which in combination ultimately form a comprehensible whole.

“This is actually a very complex structure. Since the natural world tends toward maximizing efficiency and conserving resources, it’s perfectly reasonable to ask why the brain encodes linguistic information in such an apparently complicated way instead of digitally, like a computer,” explains Michael Hahn.

Hahn, Professor of Computational Linguistics at Saarland University, has been examining this question together with his colleague Richard Futrell from the University of California, Irvine. The paper is published in the journal Nature Human Behaviour.

Quantum Algorithm Solves Metabolic Modeling Test

A Japanese research team from Keio University demonstrated that a quantum algorithm can solve a core metabolic-modeling problem, marking one of the earliest applications of quantum computing to a biological system. The study shows quantum methods can map how cells use energy and resources.

Flux balance analysis is a method widely used in systems biology to estimate how a cell moves material through metabolic pathways. It treats the cell as a network of reactions constrained by mass balance laws, finding reaction rates that maximize biological objectives like growth or ATP production.

No. The demonstration ran on a simulator rather than physical hardware, though the model followed the structure of quantum machines expected in the first wave of fault-tolerant systems. The simulation used only six qubits.

The Weird Hybrid Material That Could Turbocharge Photonic Computing

Researchers have created gyromorphs, a new material that controls light more effectively than any structure used so far in photonic chips.

These hybrid patterns combine order and disorder in a way that stops light from entering from any angle. The discovery solves major limitations found in quasicrystals and other engineered materials. It may open the door to faster, more efficient light-powered computers.

Light-based computers and the need for better materials.

Wafer-scale uniform epitaxy of transferable 2D single crystals for gate-all-around nanosheet field effect transistors

Gate-all-around (GAA) nanosheet field-effect transistors (FETs) based on 2D semiconductors hold promise to complement silicon in future integrated circuits. Here, the authors report the wafer-scale growth of high-κ dielectric/semiconductor β-Bi2SeO5/Bi2O2Se/α-Bi2SeO5 heterostructures and their application for high performance 2D GAA FETs.

Quantum sensor based on silicon carbide qubits operates at room temperature

Over the past decades, physicists and quantum engineers introduced a wide range of systems that perform desired functions leveraging quantum mechanical effects. These include so-called quantum sensors, devices that rely on qubits (i.e., units of quantum information) to detect weak magnetic or electric fields.

Researchers at the HUN-REN Wigner Research Center for Physics, the Beijing Computational Science Research Center, the University of Science and Technology of China and other institutes recently introduced a new quantum sensing platform that utilizes silicon carbide (SiC)-based spin qubits, which store quantum information in the inherent angular momentum of electrons. This system, introduced in a paper published in Nature Materials, operates at room temperature and measures qubit signals using near-infrared light.

“Our project began with a puzzle,” Adam Gali, senior author of the paper told Phys.org. “Quantum defects that sit just a few nanometers below a surface are supposed to be fantastic sensors—but in practice, they pick up a lot of ‘junk’ signals from the surface itself. This is especially true in SiC. Its standard oxide surface is full of stray charges and spins, and those produce noise that overwhelms the quantum defects we actually want to use for sensing. We wanted to break out of this limitation.”

Can quantum computers help researchers learn about the inside of a neutron star?

A new paper published in Nature Communications could put scientists on the path to understanding one of the wildest, hottest, and most densely packed places in the universe: a neutron star.

Christine Muschik, a faculty member at the University of Waterloo Institute for Quantum Computing (IQC) and a research associate faculty member at Perimeter Institute is part of a U.S.–Canadian research group using a quantum computer to build on a theory of quantum chromodynamics that describes how different varieties of quarks and gluons (the most fundamental bits of nature) interact in nuclei.

To really understand the behavior of the quark-gluon plasma in extreme conditions like the beginning of the universe, or the inside of a neutron star, scientists need a map, a so-called “phase diagram” to describe the phase transitions in those conditions that are so extreme—so dense and complex—that classical computer simulations of the models will fail.

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