Lifeboat Foundation

Scientists at the University of Florida have pioneered a method for using semiconductor technology to manufacture processors that significantly enhance the efficiency of transmitting vast amounts of data across the globe. The innovation, featured on the current cover of the journal Nature Electronics, is poised to transform the landscape of wireless communication at a time when advances in AI are dramatically increasing demand.

Traditionally, wireless communication has relied on planar processors, which, while effective, are limited by their two-dimensional structure to operate within a limited portion of electromagnetic spectrum. The UF-designed approach leverages the power of semiconductor technology to propel wireless communication into a new dimension—quite literally.

Researchers have successfully transitioned from planar to three-dimensional processors, ushering in a new era of compactness and efficiency in data transmission.

A global race to build powerful computer chips that are essential for the next generation of artificial intelligence (AI) tools could have a major impact on global politics and security.

The US is currently leading the race in the design of these chips, also known as semiconductors. But most of the manufacturing is carried out in Taiwan. The debate has been fueled by the call by Sam Altman, CEO of ChatGPT’s developer OpenAI, for a US$5 trillion to US$7 trillion (£3.9 trillion to £5.5 trillion) global investment to produce more powerful chips for the next generation of AI platforms.

The amount of money Altman called for is more than the chip industry has spent in total since it began. Whatever the facts about those numbers, overall projections for the AI market are mind blowing. The data analytics company GlobalData forecasts that the market will be worth US$909 billion by 2030.

After the advent of 5G, engineers have been trying to devise techniques to further enhance wireless communication technology. To increase these systems’ data transmission rate, they will ultimately need to extend their carrier frequency beyond 100 gigahertz, reaching the terahertz range.

Existing devices and technologies, however, have proved to be unable to achieve such high carrier frequencies. One proposed solution to reach this goal entails the use of some quantum materials that exhibit the so-called non-linear Hall effect.

Researchers at Helmholtz-Zentrum Dresden-Rossendorf (HZDR) e. V. and University of Salerno have identified a promising material for the development of next generation wireless communication systems, namely thin film elemental bismuth. Their paper, published in Nature Electronics, shows that this material exhibits a room-temperature nonlinear Hall effect.

Draw a line between P and Q. That line will intersect the curve at a third point, R. (Mathematicians have a special trick for dealing with the case where the line doesn’t intersect the curve by adding a “point at infinity.”) The reflection of R across the x-axis is your sum P + Q. Together with this addition operation, all the solutions to the curve form a mathematical object called a group.

Mathematicians use this to define the “rank” of a curve. The rank of a curve relates to the number of rational solutions it has. Rank 0 curves have a finite number of solutions. Curves with higher rank have infinite numbers of solutions whose relationship to one another using the addition operation is described by the rank.

Continue reading “Elliptic Curve ‘Murmurations’ Found With AI Take Flight” »

Scientists from the University of Rochester have developed new electrochemical approaches to clean up pollution from “forever chemicals” found in clothing, food packaging, firefighting foams, and a wide array of other products. A new Journal of Catalysis study describes nanocatalysts developed to remediate per-and polyfluoroalkyl substances known as PFAS.

The researchers, led by assistant professor of chemical engineering Astrid Müller, focused on a specific type of PFAS called Perfluorooctane sulfonate (PFOS), which was once widely used for stain-resistant products but is now banned in much of the world for its harm to human and animal health. PFOS is still widespread and persistent in the environment despite being phased out by US manufacturers in the early 2000s, continuing to show up in water supplies.

Generative AI is getting plenty of attention for its ability to create text and images. But those media represent only a fraction of the data that proliferate in our society today. Data are generated every time a patient goes through a medical system, a storm impacts a flight, or a person interacts with a software application.

Using generative AI to create realistic synthetic data around those scenarios can help organizations more effectively treat patients, reroute planes, or improve software platforms—especially in scenarios where real-world data are limited or sensitive.

For the last three years, the MIT spinout DataCebo has offered a generative software system called the Synthetic Data Vault to help organizations create synthetic data to do things like test software applications and train machine learning models.

Scientists have revealed why some white dwarfs mysteriously stop cooling—changing ideas on just how old stars really are and what happens to them when they die.

White dwarf stars are universally believed to be ‘dead stars’ that continuously cool down over time. However, in 2019, data from the European Space Agency’s (ESA’s) Gaia satellite discovered a population of white dwarf stars that have stopped cooling for more than eight billion years. This suggested that some white dwarfs can generate significant extra energy, at odds with the classical ‘dead star’ picture, and astronomers initially were not sure how this could happen.

Today, new research published in Nature, led by Dr. Antoine Bédard from the University of Warwick and Dr. Simon Blouin from the University of Victoria (Canada), unveils the mechanism behind this baffling observation.

The demonstration of a device that can triple the number of photons in a microwave signal is a key step toward making a single-microwave-photon detector.

The ability to detect a single microwave photon’s worth of energy remains beyond the capability of any tool in the photonics toolbox. Detectors for one photon’s worth of energy at other photon wavelengths mostly identify the energy via the electrical signals that the photons induce after they hit the detector and are converted into electrons. However, the energies of microwave photons are too low for this process to work effectively. Fortunately, superconducting circuits provide a platform for turning one microwave photon into many, making such photons easier to detect. In a joint effort, researchers at Grenoble Alpes University in France and at the University of Sherbrooke in Canada have now demonstrated a device that can multiply the photons in a weak microwave signal [1]. The demonstration provides a key first step in creating a single-microwave-photon detector.

While detectors for optical photons have existed for decades, scientists only started developing detectors for microwave photons in the past 15 years. The wish list for an effective microwave-photon detector is daunting: it should respond to traveling photons, and not only those localized in space [2– 5]; it should have sufficient sensitivity to register a signal from a single photon [6]; it should be able to count how many photons are in a signal [7]; it should not register so-called dark counts, hits recorded when the microwave source is off; and finally, its lag time between detections should be as short as possible. One proposed way to achieve these goals is to build a microwave-photon detector using the photon-number multiplier that Romain Albert and colleagues have now demonstrated [1, 8].

Last year was awash with claims that researchers had found new high-temperature superconductors. While some of those claims were quickly quashed, others are still being explored, such as the report that single crystals of the nickelate La₃Ni₂O₇ can superconduct at up to 78 K when under a pressure of 18 gigapascals (GPa) [1]. Now experiments performed by Jinguang Cheng of the Chinese Academy of Science and colleagues strengthen the claim that this compound is indeed a superconductor [2]. If confirmed, these results would make La₃Ni₂O₇ one of the few transition-metal compounds outside of cuprates to superconduct at temperatures above the boiling point of liquid nitrogen.

The initial report of superconductivity in La₃Ni₂O₇ came from measurements of single crystals. Those experiments showed a sudden drop in electrical resistance at around 80 K in samples held at pressures above 14 GPa. However, the report lacked measurements of two key hallmarks of a material entering the superconducting state—its resistance falling to zero and the expulsion of external magnetic fields.

For their experiments, Cheng and his colleagues studied polycrystalline samples of La₃Ni₂O₇ subjected to pressures of up to 18 GPa. The researchers chose polycrystalline samples over single-crystal ones, as they are significantly easier to prepare. Their resistance measurements indicated the zero-resistance state needed to confirm the presence of superconductivity. But the researchers’ attempts to detect the magnetic hallmark of superconductivity failed. Cheng says that recent unpublished results from their lab show that doping La₃Ni₂O₇ with the lanthanide praseodymium increases the superconducting temperature to 82.5 K. In those experiments, he says, the team observed both superconducting hallmarks.