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Towards topological quantum batteries: Theoretical framework addresses two long-standing challenges

Researchers from the RIKEN Center for Quantum Computing and Huazhong University of Science and Technology have conducted a theoretical analysis demonstrating how a “topological quantum battery”—an innovative device that leverages the topological properties of photonic waveguides and quantum effects of two-level atoms—could be efficiently designed. The work, published in Physical Review Letters, holds promise for applications in nanoscale energy storage, optical quantum communication, and distributed quantum computing.

With increasing global awareness of the importance of environmental sustainability, developing next-generation storage devices has become a critical priority. Quantum batteries—hypothetical miniature devices that, unlike classical batteries that store energy via chemical reactions, rely on quantum properties such as superposition, entanglement, and coherence—have the potential to enhance the storage and transfer of energy.

From a mechanistic perspective, they offer potential performance advantages over classical batteries, including improved charging power, increased capacity, and superior work extraction efficiency.

Ultra-thin lenses halve incident wavelength to make infrared light visible

Physicists at ETH Zurich have developed a lens that can transform infrared light into visible light by halving the wavelength of incident light. The study is published in Advanced Materials.

Lenses are the most widely used optical devices. Camera lenses or objectives, for example, produce a sharp photo or video by directing at a focal point. The speed of evolution in the field of optics in recent decades is exemplified by the transformation of conventional bulky cameras into today’s compact smartphone cameras.

Even high-performance smartphone cameras still require a stack of lenses that often account for the thickest part of the phone. This size constraint is an inherent feature of classic design—a thick lens is crucial for bending light to capture a sharp image on the camera sensor.

Fusion project uses 3D-printed models to streamline assembly and reduce risk

The bundle of magnets at the heart of the U.S. Department of Energy’s Princeton Plasma Physics Laboratory’s (PPPL) National Spherical Torus Experiment-Upgrade (NSTX-U) is the star of the show.

Its magnets will produce the highest magnetic field of any large spherical torus, allowing for near steady-state conditions. They are critical to the design of NSTX-U. When it begins operating, it will be essential in determining whether spherical tokamaks, which are smaller and more compact than traditional doughnut-shaped tokamaks, could provide a more efficient and cost-effective model for a fusion pilot plant.

The 19-foot toroidal field (TF) magnet carries up to 4 million amps of electric current to stabilize and confine the superhot plasma in fusion experiments. It will eventually connect to 12 TF coils on the outside of the vacuum vessel. Wrapped around it like a slinky is the ohmic heating (OH) coil, a 4-kilovolt magnet that induces an , which drives an electric current into the vessel and helps to heat the plasma.

New data from ALICE may contribute to solving the cosmic muon puzzle

Cosmic rays are high-energy particles from outer space that strike Earth’s atmosphere, generating showers of secondary particles, such as muons, that can reach the planet’s surface. In recent years, ground-based experiments have detected more cosmic muons than current theoretical models predict, a discrepancy known as the muon puzzle.

Underground experiments offer good conditions for the detection of cosmic muons, because the rock or soil above the experiments absorbs the other shower components. They could therefore help to solve the muon puzzle. One example is ALICE at the Large Hadron Collider (LHC).

Designed to study the products of heavy-ion collisions, ALICE is also well-suited for detecting cosmic muons thanks to its location in a cavern 52 meters underground, shielded by 28 meters of overburden rock and an additional 1 meter of magnet yoke.

Information entropy untangles vortices and flows in turbulent plasmas

Turbulence in nature refers to the complex, time-dependent, and spatially varying fluctuations that develop in fluids such as water, air, and plasma. It is a universal phenomenon that appears across a vast range of scales and systems—from atmospheric and oceanic currents on Earth, to interstellar gas in stars and galaxies, and even within jet engines and blood flow in human arteries.

Turbulence is not merely chaotic; rather, it consists of an evolving hierarchy of interacting vortices, which may organize into large-scale structures or produce coherent flow patterns over time.

In nuclear fusion plasmas, plays a crucial role in regulating the confinement of thermal energy and the mixing of fuel particles, thereby directly impacting the performance of fusion reactors. Unlike simple fluid turbulence, plasma turbulence involves the simultaneous evolution of multiple physical fields, such as density, temperature, magnetic fields, and electric currents.

New laser smaller than a penny can measure objects at ultrafast rates

Researchers from the University of Rochester and University of California, Santa Barbara, engineered a laser device smaller than a penny that they say could power everything from the LiDAR systems used in self-driving vehicles to gravitational wave detection, one of the most delicate experiments in existence to observe and understand our universe.

Laser-based measurement techniques, known as optical metrology, can be used to study the physical properties of objects and materials. But current optical metrology requires bulky and expensive equipment to achieve delicate laser-wave control, creating a bottleneck for deploying streamlined, cost-effective systems.

The new chip-scale laser, described in a paper published in Light: Science & Applications, can conduct extremely fast and accurate measurements by very precisely changing its color across a broad spectrum of light at very fast rates—about 10 quintillion times per second.

Puzzling Material Reveals Quantum Twist: Scientists Have Uncovered the True Nature of Bismuth

Bismuth, a puzzling material in quantum research, has now revealed a surprising twist. Kobe University scientists discovered that its surface properties can obscure its true nature, challenging a foundational assumption in topological material science. For nearly two decades, scientists have puzz

Neurosymbolic AI Could Be the Answer to Hallucination in Large Language Models

The emerging field of neurosymbolic AI could solve these issues, while also reducing the enormous amounts of data required for training LLMs. So what is neurosymbolic AI and how does it work?

LLMs work using a technique called deep learning, where they are given vast amounts of text data and use advanced statistics to infer patterns that determine what the next word or phrase in any given response should be. Each model—along with all the patterns it has learned—is stored in arrays of powerful computers in large data centers known as neural networks.

LLMs can appear to reason using a process called chain-of-thought, where they generate multi-step responses that mimic how humans might logically arrive at a conclusion, based on patterns seen in the training data.

This diet can protect your brain even if started later in life, study suggests

People who follow a MIND diet, even if started later in life, were significantly less likely to develop Alzheimer’s disease or related forms of dementia, according to new research.

The MIND diet stands for “Mediterranean-DASH Intervention for Neurodegenerative Delay” and combines many elements of the Mediterranean diet and DASH (“Dietary Approaches to Stop Hypertension”). It emphasizes brain-healthy foods like leafy greens, berries, nuts and olive oil.

The study, being presented Monday at the American Society for Nutrition’s annual meeting, analyzed data from nearly 93,000 U.S. adults aged 45 to 75 starting in the 1990s.