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How small can optical computers get? Scaling laws reveal new strategies

The research, published in Nature Communications, addresses one of the key challenges to engineering computers that run on light instead of electricity: making those devices small enough to be practical. Just as algorithms on digital computers require time and memory to run, light-based systems also require resources to operate, including sufficient physical space for light waves to propagate, interact and perform analog computation.

Lead authors Francesco Monticone, associate professor of electrical and computer engineering, and Yandong Li, Ph.D. ‘23, postdoctoral researcher, revealed scaling laws for free-space optics and photonic circuits by analyzing how their size must grow as the tasks they perform become more complex.

New scalable single-spin qubits could simplify future processors

Quantum computers, which operate leveraging effects rooted in quantum mechanics, have the potential of tackling some computational and optimization tasks that cannot be solved by classical computers. Instead of bits (i.e., binary digits), which are the basic units of information in classical computers, quantum computers rely on so-called qubits.

Qubits, the quantum equivalent of bits, are not restricted to binary states (i.e., 0 or 1), but can exist in superpositions of these states. One common type of qubits used to fabricate quantum processors are so-called semiconductor .

Quantum dots are small electrically confined regions that can trap individual charge carriers. To manipulate these qubits, most quantum engineers currently rely on high-frequency , as opposed to low-frequency baseband signals.

Golden Fractal Jubilee: 50 Years of Bridging Art and Science

We investigate the artistic patterns generated by the pouring technique made famous by Jackson Pollock. To determine if poured patterns can be distinguished based on the artist age, we apply computer analysis techniques to paintings created under controlled conditions by children (four to six years old) and adults (18–25 years old) pouring fluid paint onto horizontal sheets of paper. Both groups of art display a high visual complexity due to the multi-scaled paint structure generated by the pouring process. However, the two groups demonstrate statistically significant differences when this structure is quantified using both multifractal and lacunarity analysis. Whereas the multifractal analysis probes the scaling characteristics of the patterns, lacunarity quantifies clustering in their spatial distributions. We find that the children’s paintings are characterized by smaller fractal dimensions (indicating a reduced contribution of fine structure) and by larger lacunarity parameters (indicating a larger clustering of this fine structure) compared to the adult paintings. We compare these results to those of two famous poured works by Jackson Pollock and Max Ernst as a preliminary step to investigating the potential origins of the fractal and lacunarity variations across artists, which includes motions related to biomechanical balance. Finally, to examine the impact on audiences, we ask observers to rate their perceptions of the paintings. These ratings indicate a rise in interest and pleasantness for paintings with lower fractal dimensions and larger lacunarity.

The interface between art and science has grown over the past three decades with the advent of statistical analysis of the visual characteristics of art works. Although such studies now encompass a broad range of artistic styles, substantial research has been devoted to paintings generated by pouring paint onto the canvas rather than by using traditional brush contact. A number of Twentieth Century artists pursued this technique, including the European Surrealists [1], the Canadian Les Automatists [2], and the American Abstract Expressionists [3]. The latter featured the most famous proponent of the ‘pouring’ technique, Jackson Pollock [4].

Celebrated as Action Painting, these poured works serve as records of the artists’ encounters with their canvases. In Pollock’s case, this encounter involved him painting in the three-dimensional space above the canvas and then letting gravity condense the fluid paint onto the two-dimensional plane of the canvas laid out across the floor. This dynamic process often unfolded at frantic painting speeds, inviting speculation from art critics and the public alike as to whether it is possible to control the pouring technique. Perhaps all artists are instead destined to generate haphazard records of their encounters with the canvas. This debate has been fueled by the lack of traditional compositional strategies displayed in typical poured works — no center of focus, no left or right, and no up or down [3, 4].

From light to logic: First complete logic gate achieved in soft material using light alone

Researchers from McMaster University and the University of Pittsburgh have created the first functionally complete logic gate—a NAND gate (short for “NOT AND”)—in a soft material using only beams of visible light. The discovery, published in Nature Communications, marks a significant advance in the field of materials that compute, in which materials themselves process information without traditional electronic circuitry.

“This project has been part of my scientific journey for over a decade,” said first author Fariha Mahmood, who began studying the gels as an undergraduate researcher at McMaster and is now pursuing postdoctoral research at the University of Cambridge. “To see these materials not only respond to light but also perform a logic operation feels like watching the material ‘think.’ It opens the door to soft systems making decisions on their own.”

Mahmood is joined by authors Anna C. Balazs, distinguished professor of chemical and petroleum engineering, and Victor V. Yashin, research assistant professor at Pitt’s Swanson School of Engineering; and corresponding author Kalaichelvi Saravanamuttu, professor of chemistry and chemical biology at McMaster.

Interfacing with the Brain: How Nanotechnology Can ContributeClick to copy article linkArticle link copied!

Interfacing artificial devices with the human brain is the central goal of neurotechnology. Yet, our imaginations are often limited by currently available paradigms and technologies. Suggestions for brain–machine interfaces have changed over time, along with the available technology. Mechanical levers and cable winches were used to move parts of the brain during the mechanical age. Sophisticated electronic wiring and remote control have arisen during the electronic age, ultimately leading to plug-and-play computer interfaces. Nonetheless, our brains are so complex that these visions, until recently, largely remained unreachable dreams. The general problem, thus far, is that most of our technology is mechanically and/or electrically engineered, whereas the brain is a living, dynamic entity. As a result, these worlds are difficult to interface with one another.

Surface-only superconductor is the strangest of its kind

Something strange goes on inside the material platinum-bismuth-two (PtBi₂). A new study by researchers at IFW Dresden and the Cluster of Excellence ct.qmat demonstrates that while PtBi₂ may look like a typical shiny gray crystal, electrons moving through it do some things never seen before.

In 2024, the research team demonstrated that the top and bottom surfaces of the material superconduct, meaning pair up and move without resistance.

Now, they reveal that this pairing works differently from any superconductor we have seen before. Enticingly, the edges around the superconducting surfaces hold long-sought-after Majorana particles, which may be used as fault-tolerant quantum bits (qubits) in quantum computers.

Princeton’s new quantum chip marks a major step toward quantum advantage

A Princeton team built a new tantalum-silicon qubit that survives for over a millisecond, far surpassing today’s best devices. The design tackles surface defects and substrate losses that have limited transmon qubits for years. Easy to integrate into existing quantum chips, the approach could make processors like Google’s vastly more powerful.

Quantum computers could be powerful enough to decrypt Bitcoin sometime after 2030, CEO of Nvidia’s quantum partner says

“You should have a few good years ahead of you but I wouldn’t hold my Bitcoin,” Peronnin said, laughing. “They need to fork [move to a stronger blockchain] by 2030, basically. Quantum computers will be ready to be a threat a bit later than that,” he said.

Quantum doesn’t just threaten Bitcoin, of course, but all banking encryption. And it is likely that in all these cases companies are developing quantum resistant tools to upgrade their existing security systems.

Defensive security algorithms are improving, Peronnin said, so it’s not certain when the blockchain will become vulnerable to a quantum attack. But “the threshold for such an event is coming closer to us year by year,” he said.

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