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Category: computing

Gold clusters mimic atomic spin properties for scalable quantum computing applications

The efficiency of quantum computers, sensors and other applications often relies on the properties of electrons, including how they are spinning. One of the most accurate systems for high-performance quantum applications relies on tapping into the spin properties of electrons of atoms trapped in a gas, but these systems are difficult to scale up for use in larger quantum devices like quantum computers.

Now, a team of researchers from Penn State and Colorado State has demonstrated how a gold cluster can mimic these gaseous, trapped atoms, allowing scientists to take advantage of these spin properties in a system that can be easily scaled up.

“For the first time, we show that have the same key spin properties as the current state-of-the-art methods for quantum information systems,” said Ken Knappenberger, department head and professor of chemistry in the Penn State Eberly College of Science and leader of the research team.

From cosmic strings to computer chips: Cooling rate triggers phase transitions in silicon surfaces

Solar cells and computer chips need silicon layers that are as perfect as possible. Every imperfection in the crystalline structure increases the risk of reduced efficiency or defective switching processes.

If you know how arrange themselves to form a on a thin surface, you gain fundamental insights into controlling crystal growth. To this end, an international research team analyzed the behavior of silicon that was flash-frozen. The study is published in the journal Physical Review Letters.

The results show that the speed of cooling has a major impact on the structure of silicon surfaces. The underlying mechanism may also have occurred during phase transitions in the early universe shortly after the Big Bang.

The dawn of quantum advantage

Quantum computing is about to enter an important stage — the era of quantum advantage. The first claims of quantum advantage are emerging, and over the next few years, we expect researchers and developers to continue presenting compelling hypotheses for quantum advantages. In turn, the broader community will either disprove these hypotheses with cutting-edge techniques — or the advantage holds.

Put simply, quantum advantage means that a quantum computer can run a computation more accurately, cheaply, or efficiently than a classical computer. Between now and the end of 2026, we predict that the quantum community will have uncovered the first quantum advantages. But there’s more to it than that.

We have arrived already at a place where quantum computing is a useful scientific tool capable of performing computations that even the best exact classical algorithms can’t. We and our partners are already conducting a range of experiments on quantum computers that are competitive with the leading classical approximation methods. At the same time, computing researchers are testing advantage claims with innovative new classical approaches.

3,500 Websites Hijacked to Secretly Mine Crypto Using Stealth JavaScript and WebSocket Tactics

A new attack campaign has compromised more than 3,500 websites worldwide with JavaScript cryptocurrency miners, marking the return of browser-based cryptojacking attacks once popularized by the likes of CoinHive.

Although the service has since shuttered after browser makers took steps to ban miner-related apps and add-ons, researchers from the c/side said they found evidence of a stealthy miner packed within obfuscated JavaScript that assesses the computational power of a device and spawns background Web Workers to execute mining tasks in parallel without raising any alarm.

More importantly, the activity has been found to leverage WebSockets to fetch mining tasks from an external server, so as to dynamically adjust the mining intensity based on the device capabilities and accordingly throttle resource consumption to maintain stealth.

NVIDIA Brings Reasoning Models to Consumers Ranging from 1.5B to 32B Parameters

Today, NVIDIA unveiled OpenReasoning-Nemotron, a quartet of distilled reasoning models with 1.5B, 7B, 14B, and 32B parameters, all derived from the 671B-parameter DeepSeek R1 0528. By compressing that massive teacher into four leaner Qwen‑2.5-based students, NVIDIA is making advanced reasoning experiments accessible even on standard gaming rigs, without the need to worry about hefty GPU bills and cloud usage. The key is not some elaborate trick but raw data. Using the NeMo Skills pipeline, NVIDIA generated five million math, science, and code solutions, and then fine-tuned each one purely with supervised learning. Already, the 32B model hits an 89.2 on AIME24 and 73.8 on the HMMT February contest, while even the 1.5B variant manages a solid 55.5 and 31.5.

CHIP and aging: a key regulator of proteostasis and cellular senescence

Degradation of proteostasis, mitochondrial function, and cellular stress resistance results in a build-up of damaged proteins, oxidative insult, and chronic inflammation, characteristic of aging. CHIP is essential for maintaining protein quality control and cellular homeostasis by having dual E3 ubiquitin ligase and co-chaperone activities. CHIP facilitates proteostasis by maintaining proteostasis in misfolded, aggregated proteins by promoting their degradation. Mitochondrial dysfunction, oxidative imbalance, and cellular senescence are caused by its age-associated decline and contribute to neurodegenerative, cardiovascular, and oncogenic disease pathogenesis. Examples of recent pharmacological and gene-based strategies to correct CHIP and restore stress resilience have been made.

2D Materials for Integrated Electronics

As many in the field would agree, the growing interest in two-dimensional (2D) materials is not just a trend, it reflects real progress and curiosity. Materials like graphene and MoS2 have shown fascinating behaviour, particularly because they are atomically thin and yet still possess strong electrical, optical, and mechanical properties. These features make them promising candidates for new directions in electronics. That said, turning this promise into reliable technology is still a work in progress.

This Collection focuses on how 2D materials are being developed and used in integrated electronics. The emphasis is not only on device performance, but also on the actual process of bringing these materials into practical systems. From what I have seen, some of the most exciting results come from experiments where 2D materials are added into traditional semiconductor setups, whether that is in transistors, photodetectors, or memory elements. But challenges like scalability, environmental stability, and material quality remain real obstacles.

We’re interested in contributions across the board: device demonstrations, growth techniques, interface studies, or even theoretical modelling that can guide experimental designs. For instance, studies on how these materials interact with metal contacts, or how to reduce contact resistance, are very relevant here. So are efforts to pattern or align 2D layers over large areas, which is a challenge still not fully solved.

Quantum Teleportation Was Achieved Over Internet For The First Time

In 2024, a quantum state of light was successfully teleported through more than 30 kilometers (around 18 miles) of fiber optic cable amid a torrent of internet traffic – a feat of engineering once considered impossible.

The impressive demonstration by researchers in the US may not help you beam to work to beat the morning traffic, or download your favourite cat videos faster.

However, the ability to teleport quantum states through existing infrastructure represents a monumental step towards achieving a quantum-connected computing network, enhanced encryption, or powerful new methods of sensing.

Engineers achieve efficient integration of quantum dot lasers on silicon chiplets

Lasers that are fabricated directly onto silicon photonic chips offer several advantages over external laser sources, such as greater scalability. Furthermore, photonic chips with these “monolithically” integrated lasers can be commercially viable if they can be manufactured in standard semiconductor foundries.

III-V semiconductor lasers can be monolithically integrated with photonic chips by directly growing a crystalline layer of material, such as indium arsenide, on silicon substrate. However, photonic chips with such integrated laser source are challenging to manufacture due to mismatch between structures or properties of III-V semiconductor material and silicon. “Coupling loss” or the loss of optical power during transfer from laser source to silicon waveguides in the photonic chip is yet another concern when manufacturing with monolithically integrated lasers.

In a study that was recently published in the Journal of Lightwave Technology, Dr. Rosalyn Koscica from the University of California, United States, and her team successfully integrated quantum dot (QD) lasers monolithically on silicon photonics chiplets.