This Review covers state-of-the-art reconfigurable and tunable optical components and highlights the emergence of a set of materials that offer a new toolkit for tunability and control.
Category: computing – Page 10
Quantum effect could power the next generation of battery-free devices
A new study has revealed how tiny imperfections and vibrations inside a promising quantum material could be used to control an unusual quantum effect, opening new possibilities for smaller, faster, and more efficient energy-harvesting devices.
The international team, led by Professor Dongchen Qi from the QUT School of Chemistry and Physics and Professor Xiao Renshaw Wang from Nanyang Technological University in Singapore, studied the mechanism governing the so-called nonlinear Hall effect (NLHE). The research is published in the journal Newton.
Unlike the classical Hall effect, this quantum version allows alternating electrical signals, like those found in wireless or ambient energy sources, to be converted directly into usable direct current without the need for traditional diodes or bulky components.
Why do microbes team up? A new model explains nutrient sharing in fluctuating environments
Depending on others for something you need may feel like a risky proposition—and perhaps a human one. It is actually a survival strategy found in the microbial world, and far more frequently than one might expect. Discovering why is key to understanding how microbes form stable communities across medical, industrial, and ecological settings.
A new study by bioengineering professor Sergei Maslov (CAIM co-leader), computational scientist Ashish George, and biology professor Tong Wang explores why interdependence can be such a winning move for microbial communities. Their work, published in Cell Systems, demonstrated that a mathematical model of how bacteria produce and share resources accurately predicted the outcome of experiments with living E. coli strains.
The researchers’ collaboration began during their time as colleagues at the Carl R. Woese Institute for Genomic Biology at the University of Illinois Urbana-Champaign. George continued the collaboration in his position at the Broad Institute; Wang, in his appointment at Purdue University. Maslov, who led the study, remains at Illinois and is an affiliate member of the National Institute for Theory and Mathematics in Biology.
Scientists Create Chip That Generates Brand-New Colors of Light, Cracking a Decades-Old Nonlinear Optics Challenge
For decades, scientists and engineers have steadily advanced technologies that control and manipulate light. These tools now underpin everything from ultra-precise atomic clocks to the massive data flows moving through modern data centers.
As industries increasingly rely on optical systems, the market for dependable light-based technologies has grown into a sector worth hundreds of billions of dollars worldwide.
Atom-sized gates could transform DNA sequencing and neuromorphic computing
Scientists have taken a major step toward mimicking nature’s tiniest gateways by creating ultra-small pores that rival the dimensions of biological ion channels—just a few atoms wide. The breakthrough opens new possibilities for single-molecule sensing, neuromorphic computing, and studying how matter behaves in spaces barely larger than atoms.
Cytoplasmic flow induced by a rotating wire in living cells: magnetic rotational spectroscopy and finite element simulations
How can scientists measure viscosity inside a living cell, whose entire volume is just a few picolitres? Using computer simulations, researchers evaluated magnetic rotational spectroscopy, a technique that spins microscopic magnetic wires to probe the cytoplasm. The study shows that the motion generated by the wire is extremely localized, affecting less than one percent of the cell, so the measurement does not harm the cell. The results also confirm that, under standard conditions, magnetic rotational spectroscopy accurately captures the cytoplasmic viscosity. These findings validate magnetic rotational spectroscopy as a precise and minimally invasive technique for quantifying the mechanical properties of living cells.
Read the article in Interface.
Abstract. Recent studies have highlighted intracellular viscosity as a key biomechanical property with potential as a biomarker for cancer cell metastasis.
Feedback neurons based on perovskite memristor with nickel single-atom engineered reduced graphene oxide cathode
Scientists have long looked to the human brain as the ultimate blueprint for computing, seeking to build “neuromorphic” systems that process information with the same efficiency and flexibility as our own neurons. However, replicating the brain’s complex ability to both excite and inhibit signals—essentially “talking” and “listening” simultaneously—has proven difficult with standard hardware.
The problem? Perovskites are often too chaotic. Tiny charged particles called ions tend to zip around inside the material too quickly, making the device’s behavior hard to control. Additionally, the “bottlenecks” (barriers) where the electricity enters the device often cause lopsided performance, preventing the smooth, bidirectional communication required for advanced brain-like tasks.
Li et al. report feedback neurons based on perovskite memristors with a nickel single-atom modified reduced graphene oxide cathode. The device successfully implements an unsupervised learning network with over 50% clustering accuracy and cooperative learning for solving NP-hard combinatorial optimisation problem.
Quantum algorithm beats classical tools on complement sampling tasks
Quantum computers—devices that process information using quantum mechanical effects—have long been expected to outperform classical systems on certain tasks. Over the past few decades, researchers have worked to rigorously demonstrate such advantages, ideally in ways that are provable, verifiable and experimentally realizable.
A team of researchers working at Quantinuum in the United Kingdom and QuSoft in the Netherlands has now developed a quantum algorithm that solves a specific sampling task—known as complement sampling—dramatically more efficiently than any classical algorithm. Their paper, published in Physical Review Letters, establishes a provable and verifiable quantum advantage in sample complexity: the number of samples required to solve a problem.
“We stumbled upon the core result of this work by chance while working on a different project,” Harry Buhrman, co-author of the paper, told Phys.org. “We had a set of items and two quantum states: one formed from half of the items, the other formed from the remaining half. Even though the two states are fundamentally distinct, we showed that a quantum computer may find it hard to tell which one it is given. Surprisingly, however, we then realized that transforming one state into the other is always easy, because a simple operation can swap between them.”