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New multiplexing scheme accelerates long-distance quantum communication

Quantum networks, systems consisting of multiple connected nodes or devices that can transmit quantum information to one another, have the potential to advance future communications. These networks typically leverage entanglement, a quantum phenomenon that prompts two or more distant particles to become highly correlated, so that measuring one instantly affects the state of the other.

To ensure that distant particles have become entangled and can transmit quantum states, some quantum scientists try to realize so-called heralded entanglement. This entails confirmation, from a detectable signal, that entanglement between nodes has been established.

Researchers at Tsinghua University and Hefei National Laboratory recently introduced a promising strategy to accelerate the generation of heralded entanglement between multiple ions (i.e., atoms with an electrical charge). Their proposed approach, outlined in a paper published in Physical Review Letters, relies on a so-called multiplexing scheme, a technique to send multiple signals through the same communication channel.

Neural networks unlock larger quantum simulations with lower computational costs

In recent years, research using artificial intelligence to predict material properties has advanced rapidly. Neural network quantum Monte Carlo methods have attracted attention as highly accurate simulation techniques. However, their extremely high computational cost has limited their application to small molecular systems. This study introduces a new computational method that overcomes this limitation.

Methods that simulate electron-level mechanisms on supercomputers are widely used to explore novel materials and understand biological phenomena. There is strong demand for new approaches that can deliver faster predictions while maintaining high accuracy.

Plasma design rules show how to preserve attosecond flashes for observing electrons

Researchers at Skoltech, together with a colleague from the Shanghai Institute of Optics and Fine Mechanics of the Chinese Academy of Sciences, working within the joint SIOM–Skoltech laboratory, have determined how to select the thickness and density of a plasma target so that a pulse passing through it retains its attosecond duration and high intensity. The results will help improve the design of plasma-based sources of ultraviolet and X-ray radiation used to study ultrafast processes in matter.

The work is published in Applied Physics Letters.

An attosecond is 10⁻¹⁸ of a second. Pulses of this duration can be compared to an ultrafast camera flash: They make it possible to effectively “freeze” the motion of electrons and investigate processes that cannot be resolved using longer pulses. This is important for studying atoms, molecules, solids and new materials.

Genome tool places large genetic sequences precisely in rice and tobacco without DNA breaks

Researchers at King Abdullah University of Science and Technology (KAUST) have developed a new way to add large pieces of genetic information to plants, overcoming a challenge that has limited plant biotechnology for decades. The advance could help scientists build more complex traits into plants in the future, supporting research into areas such as crop resilience, sustainable agriculture, biotechnology and the use of plants as scalable platforms for producing therapeutics and biologics.

Published in Nature Biotechnology, the study introduces a new genome engineering approach that allows scientists to place large genes into specific locations within plant genomes. The approach was successfully demonstrated in both tobacco and rice, opening new possibilities for future research in agricultural biotechnology, synthetic biology and plant-based biomanufacturing.

Physics-based AI could boost biomedical imaging and autonomous vehicle sensors

A research team led by UCLA and the University of Rochester has demonstrated a promising evolution of an imaging system designed to capture details within “complex media,” which scatter light, from depicting structures inside body tissue to seeing obstacles through heavy fog. The system uses physics-based machine learning to improve an existing imaging technique.

In tests with standard calibration images obscured by complex media, the new system more than doubled the signal-to-noise ratio compared with a previous generation of the technology. The system also created images in near real time—thousandths of a second. The findings are published in the journal Light: Science & Applications.

Chemists develop a molecular platform for the selective control of oxygen reaction pathways

Controlling how oxygen reacts is important for improving technologies such as batteries, fuel cells and environmentally sustainable chemical processes. A research team led by professor Seung Jun Hwang from KAIST’s Department of Chemistry has developed a molecular system capable of directing oxygen activation along a selected electron-transfer pathway.

By combining germanium with a molecular framework that can store and transfer electrons, the team established a design principle for selectively switching oxygen activation between two-and four-electron pathways. The results were published in Chem.

More connections can deepen polarization when social ties remain weak

Social networks, intended to bring people together, can actually increase polarization, new research finds, because while the links in the network may be plentiful, they’re probably weak. A research team including Cornell sociologist Michael Macy has found that while the growing number of international contacts enabled by modern communications technologies may indeed contribute to greater polarization, as shown in previous studies, the underlying mechanism does not necessarily depend on an increase in close friendships. Instead, weaker social ties appear to play a more significant role, as they are more likely to foster hierarchical structures shaped by social status.

“The most important argument in our paper is the polarizing effect of ‘status-driven dynamics’ involving weak ties,” said Macy, with “status” referring to whether an individual holds another in high or low esteem. “The importance lies in the distinction between structural and ideological polarization.”

Microscale roughness breakthrough defies 80 years of fluid dynamics

Logically, you would think a sleek surface has optimal aerodynamics—but recent research at Tohoku University turns this fundamental principle on its head. Applying an irregular microscale surface texture reduced the aerodynamic drag of a test model. The innovation has potential applications in the design of fuel-efficient vehicles. The study is published in the Journal of Fluid Mechanics.

For more than 80 years, a fundamental principle of fluid dynamics has held that smoother surfaces produce less aerodynamic drag. However, a research group led by associate professor Aiko Yakeno at the Institute of Fluid Science, Tohoku University, has overturned this long-standing assumption. By applying Distributed Micro-Roughness (DMR)—irregular microscale surface textures—to a test model, the team achieved the world’s first experimental demonstration of up to 43.6% aerodynamic drag reduction.

By reducing drag in this innovative way, researchers may be able to reduce fuel consumption and CO₂ emissions across aviation, automotive, marine and rail transportation in the future.

Detecting the body’s magnetic fields with a low-power Ramsey-based magnetometer

Our bodies generate extremely weak magnetic fields as electric currents flow through the heart, brain and other tissues. These signals are used in magnetocardiography and magnetoencephalography to assess heart function and brain activity, respectively. These fields can be detected at room temperature using diamond sensors containing nitrogen-vacancy (NV) centers, in which a carbon atom is replaced by a nitrogen atom adjacent to an empty lattice site.

However, conventional NV-center sensors typically require watt-level lasers to detect the extremely weak biomagnetic fields, which are usually below the picotesla level. These high-power lasers generate significant heat, limiting how close the sensor can be placed to biological tissue. Since biomagnetic fields rapidly weaken with distance, overcoming thermal and close-proximity challenges is essential for practical biomagnetic sensing.

A research team led by Professor Takayuki Iwasaki from the Department of Electrical and Electronic Engineering, School of Engineering, Institute of Science Tokyo, Japan, has developed a diamond quantum magnetometer using a low-power laser of just 210 mW, a light-trapping diamond waveguide and a compact microwave antenna. The new sensor limits its temperature rise to only 13 K while allowing it to be placed just 2 mm (0.08 inches) from the sample, enabling close-proximity biomagnetic measurements without compromising thermal safety.

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