Chinese researchers unveil 10x larger atom array for next-gen quantum processors.
Scientists in China have achieved a significant breakthrough in advancing quantum physics.
A team of researchers has developed the largest array of atoms for quantum computing.
The key component for a quantum computer is reportedly capable of creating arrays 10 times larger than previous systems.
A new software tool developed by Cornell researchers can model a small city’s building energy use within minutes on a standard laptop, then run simulations to help policymakers prioritize the most cost-effective approaches to decarbonization.
Using the City of Ithaca, New York, as a case study, the urban building energy model quickly mapped more than 5,000 residential and commercial buildings and their baseline energy use. Simulated investments in weatherization, electric heat pumps and rooftop solar panels, while also factoring in financial incentives, generated insights that are informing city efforts to achieve carbon neutrality by 2030.
The tool’s automated workflow, accessibility and accuracy—without advanced computing power—could be particularly valuable for smaller cities that lack resources and expertise dedicated to decarbonization, the researchers said. But they said the new model—now also supporting the county that surrounds Ithaca—could be further scaled up to serve big cities or an entire state.
While conventional computers store information in the form of bits, fundamental pieces of logic that take a value of either 0 or 1, quantum computers are based on qubits. These can have a state that is simultaneously both 0 and 1. This odd property, a quirk of quantum physics known as superposition, lies at the heart of quantum computing’s promise to ultimately solve problems that are intractable for classical computers.
Many existing quantum computers are based on superconducting electronic systems in which electrons flow without resistance at extremely low temperatures. In these systems, the quantum mechanical nature of electrons flowing through carefully designed resonators creates superconducting qubits.
These qubits are excellent at quickly performing the logical operations needed for computing. However, storing information—in this case quantum states, mathematical descriptors of particular quantum systems—is not their strong suit. Quantum engineers have been seeking a way to boost the storage times of quantum states by constructing so-called “quantum memories” for superconducting qubits.
Quantum computing. The effect reveals and manipulates hidden quantum states.
Researchers from the U.S. Department of Energy’s Ames National Laboratory and Iowa State University have identified an unusual “quantum echo” in a superconducting material. This finding offers new understanding of quantum behavior that could be applied to future quantum sensing and computing systems.
A new specialized, radiation-hardened chip has been designed for CERN’s Large Hadron Collider (LHC) upgrade.
Engineers at Columbia University have developed this analog-to-digital converter (ADC) chip.
The custom-designed chips will be used in the ATLAS detector to measure up to 1.5 billion particle collisions per second.
In nanoscale transistors, quantum mechanical effects such as tunneling and quantization significantly influence device characteristics. However, large-scale quantum transport simulation remains a challenging field, making it difficult to account for quantum mechanical effects arising from the complex device geometries. Here, based on large-scale quantum transport simulations, we demonstrate that quantum geometrical effects in stacked nanosheet GAAFETs significantly impact carrier injection characteristics. Discontinuities in confinement energy at the constriction—the junction between the bulk source/drain and nanosheet channel—cause substantial carrier backscattering. This degradation becomes more severe as electrons experience higher effective energy barriers, and is further exacerbated at lower scattering rate, lower doping concentrations, and near Schottky barriers where electron depletion regions form. Considering these quantum mechanical bottlenecks, proper device optimization for future technology nodes requires a full quantum-based device structure design at the large-scale level, which enables unique optimization strategies beyond conventional classical prediction.
Kyoung Yeon Kim and colleagues report the importance of quantum geometrical effects that serve as a bottleneck in stacked nanosheet GAAFETs. This highlights that full quantum mechanics-based device design is crucial for realizing ideal carrier injection characteristics in future technology nodes.
Researchers with the schools of science and engineering at Rensselaer Polytechnic Institute (RPI) are exploring new ways to manipulate matter with light to unlock a new generation of computer chips, photovoltaic cells and other advanced materials.
Physics professor Moussa N’Gom, Ph.D., and materials science professor Edwin Fohtung, Ph.D., have brought together their respective areas of expertise—optics and materials science —to illuminate previously unknown properties of the materials that will build the next generation of consumer, industrial and scientific devices.
“We can use almost the entire spectrum of light, from visible to X-ray, to manipulate and study materials,” Fohtung said. “We can interrogate any system, from hard condensed matter to soft biological tissue.”
Healthy brain function relies on a steady supply of blood. Disruptions in blood flow are linked to major neurological conditions like stroke, Alzheimer’s disease (AD), and traumatic brain injuries. But understanding how the brain fine-tunes this flow—especially across its smallest blood vessels—remains a challenge.
The brain’s blood supply includes a vast network of vessels, ranging from large arteries to microscopic capillaries. Between these lie transitional zone (TZ) vessels—such as penetrating arterioles, precapillary arterioles, and capillary sphincters—that bridge the gap and may play a big role in regulating flow. But their exact contribution, particularly during increased brain activity, remains a subject of scientific debate.
To explore these dynamics, researchers from the College of Engineering and Computer Science at Florida Atlantic University and the FAU Sensing Institute (I-SENSE) developed a highly detailed computer model of the mouse brain’s vasculature, treating each vessel segment as a tiny, adjustable valve.