The semiconductor industry warned that there won’t be enough engineers, computer scientists and technicians in the US to support a rapid expansion this decade, threatening efforts to boost the domestic chip economy.
A scalable system for controlling quantum bits demonstrates a very low error rate, which is essential for making practical devices.
A major obstacle to the development of practical quantum computers is the difficulty of scaling up—making a device with large numbers of quantum bits (qubits) that also gives accurate results in the presence of environmental noise. Now researchers report a significant improvement in the accuracy of a technology that is already known to be much easier to scale up than conventional techniques [1]. This alternative technology uses units of magnetic flux called flux quanta to control conventional superconducting qubits. The reduction in the error rate came from physically separating the control circuits from the qubits. With further refinement, the flux-quanta technology could provide a superior pathway to practical quantum computation.
Many current efforts to carry out quantum logic operations—the basic units of computation—use short microwave pulses to control the qubits. Currently, however, this technology is difficult to scale up beyond 1,000 qubits. But the presence of environmental noise requires error-correction methods that rely on large numbers of qubits, perhaps a million or more, for an effective error-correcting system that performs useful computations, according to some estimates.
As fish wriggle, they create a complex push–pull pattern in the water that propels them forward. Many studies have shown how the motion of a fish’s tail forms a vortex around its leading edge that provides thrust; however, it has been difficult to capture how the water flow around other parts of the fish interacts with this vortex to impact the overall propulsion. Jiacheng Guo at the University of Virginia and colleagues recently demonstrated how different fins create currents that can constructively interact to improve swimming efficiency [1].
Guo and colleagues studied how the flow around the lower back—or anal—fin interacts with the flow around the tail—or caudal—fin. First, they took a high-resolution video of a swimming rainbow trout and created a computational fluid dynamics model to accurately reproduce the fish’s motion and the water currents that it induced. Then they modified the anal fin in the model to see how this would change the pattern of water flow around the trout and affect the forward thrust.
The researchers found that the anal fin increases propulsion in two ways. It creates a vortex that stabilizes and strengthens the caudal-fin vortex, and it helps maintain a pressure difference across the fish’s body that reduces drag. Changes to the size or position of the anal fin decreased the swimming efficiency, demonstrating that the natural fish physiology is optimal.
A study shows it’s possible to use laser-based systems with optical transistors to transfer information far more quickly than possible today.
Neuromorphic computers do not calculate using zeros and ones. They instead use physical phenomena to detect patterns in large data streams at blazing fast speed and in an extremely energy-efficient manner.
In their project NIMFEIA, Katrin and Helmut Schultheiß along with their team from the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) have now taken this technology a tremendous step forward. They also demonstrated that their approach can be seamlessly integrated into conventional chip manufacturing. Their findings have now been published in Nature Communications.
What the researchers have developed at the HZDR-Institute of Ion Beam Physics and Materials Research is referred to by many names. “Neuromorphic computing,” for example, is one term, as the processes resemble those that occur within the brain. “Unconventional computing” is another name, as the technology is so different from the data processing that we are accustomed to today, which uses the Boolean logic of zeros and ones.
With the launch of the Mac Pro and M2 Ultra chip at WWDC in June, all eyes are now on the next phase of Apple silicon and the highly anticipated M3 processor. And according to a new report, every Mac in Apple’s lineup will be getting in on the action.
In his latest Power On newsletter, Mark Gurman reports that an M3 Mac mini is “a sure thing,” as is a new MacBook Pro with M3 Pro and M3 Max processors. The Mac mini has previously gone years between updates, so it’s notable that Apple plans to refresh it so soon after the release of the M2 model.
Gurman previously reported that Apple is planning to launch the M3 chip alongside three new Macs: the 13-inch MacBook Air, the 13-inch MacBook Pro, and the 24-inch iMac. We can also expect to see an M3 version of the 15-inch Air, if not at the same time then within a few months of the announcement.
Halide perovskites are a family of materials that have attracted attention for their superior optoelectronic properties and potential applications in devices such as high-performance solar cells, light-emitting diodes, and lasers.
Caption :
A new MIT platform enables researchers to “grow” halide perovskite nanocrystals with precise control over the location and size of each individual crystal, integrating them into nanoscale light-emitting diodes. Pictured is a rendering of a nanocrystal array emitting light.
Head to https://linode.com/scishow to get a $100 60-day credit on a new Linode account. Linode offers simple, affordable, and accessible Linux cloud solutions and services.
Researchers have identified the processes that cause gray hair and have done experiments to reverse it. And believe it or not, we’ve had some of these options for decades.
Quantum technologies, a wide range of devices that operate by leveraging the principles of quantum mechanics, could significantly outperform classical devices on some tasks. Physicists and engineers worldwide have thus been working hard to achieve this long-sought “quantum advantage” over classical computing approaches.
A research team at Ecole Normale Supérieure de Lyon, CNRS recently developed a quantum radar that could significantly outperform all existing radars based on classical approaches. This new radar, introduced in a paper published in Nature Physics, concurrently measures an entangled probe and the idler microwave photon states occurring once this probe reflects from target objects, merging with thermal noise.
“We invented a superconducting circuit in 2020 that was able, among other things, to generate entanglement, store and manipulate microwave quantum states and count the number of photons in a microwave field,” Benjamin Huard, one of the researchers who carried out the study, told Phys.org. “We then realized that it had all the features we needed to tackle one of the biggest challenges in microwave quantum metrology: demonstrating a quantum advantage in radar sensing.”
Remember what it’s like to twirl a sparkler on a summer night? Hold it still and the fire crackles and sparks but twirl it around and the light blurs into a line tracing each whirl and jag you make.
A new patented software system developed at Sandia National Laboratories can find the curves of motion in streaming video and images from satellites, drones and far-range security cameras and turn them into signals to find and track moving objects as small as one pixel. The developers say this system can enhance the performance of any remote sensing application.
“Being able to track each pixel from a distance matters, and it is an ongoing and challenging problem,” said Tian Ma, a computer scientist and co-developer of the system. “For physical security surveillance systems, for example, the farther out you can detect a possible threat, the more time you have to prepare and respond. Often the biggest challenge is the simple fact that when objects are located far away from the sensors, their size naturally appears to be much smaller. Sensor sensitivity diminishes as the distance from the target increases.”
