How does a cloud stay cool under direct sunlight––or seem to vanish in infrared? In nature, phenomena like white cumulus clouds, gray storm systems, and even the hollow hairs of polar bears offer remarkable lessons in balancing temperature, color and invisibility. Inspired by these atmospheric marvels, researchers have now created a nanoscale “cloud” metasurface capable of dynamically switching between white and gray states—cooling or heating on demand––all while evading thermal detection.
Using the Australia Telescope Compact Array (ATCA), astronomers have performed large-scale radio observations of a star-forming region known as the Chamaeleon cloud complex. The observational campaign, which detected five young stars in Chamaeleon, may shed more light on the properties of this complex. The findings were detailed in a paper published June 19 on the arXiv pre-print server.
Researchers from Monash University, in collaboration with the European Biostasis Foundation and Apex Neuroscience, have revealed that although most neuroscientists agree that long-term memories depend primarily on neuronal connectivity patterns, significant uncertainties persist regarding precisely how these memories are structurally encoded.
Brains can retain memories for days, months and even across a lifetime of decades, through mechanisms that remain elusive to those at the cutting edge of neuroscience. Long-term memory enables animals to shape behaviors by linking past experiences with present contexts.
There are fragile memories, like recalling the name of someone you just met, or the location of where the keys were set down, that can seemingly escape the brain’s data capture. And there are durable memories that can survive periods of global neuronal inactivity and disruption, indicating that ongoing neural activity is not required to maintain stored information.
Inflammation, long considered a hallmark of aging, may not be a universal human experience, according to a new study from Columbia University Mailman School of Public Health. The research suggests that “inflammaging”—chronic, low-grade inflammation associated with aging—appears to be a byproduct of industrialized lifestyles and varies significantly across global populations.
The findings are published in Nature Aging.
Researchers analyzed data from four populations: two industrialized groups—the Italian InCHIANTI study and the Singapore Longitudinal Aging Study (SLAS)—and two Indigenous, non-industrialized populations—the Tsimane of the Bolivian Amazon and the Orang Asli of Peninsular Malaysia. While the inflammaging signature was similar between the two industrialized populations, it did not hold in the Indigenous groups, where inflammation levels were largely driven by infection rather than age.
A research team from the University of Wollongong’s (UOW) Institute for Superconducting and Electronic Materials (ISEM) has addressed a 40-year-old quantum puzzle, unlocking a new pathway to creating next-generation electronic devices that operate without losing energy or wasting electricity.
Published in Advanced Materials, the study is the work of UOW researchers led by Distinguished Professor Xiaolin Wang and Dr. M Nadeem, with Ph.D. candidate Syeda Amina Shabbir and Dr. Frank Fei Yun.
It introduces a new design concept to realize the elusive and highly sought-after quantum anomalous Hall (QAH) effect.
How reliable is artificial intelligence, really? An interdisciplinary research team at TU Wien has developed a method that allows for the exact calculation of how reliably a neural network operates within a defined input domain. In other words: It is now possible to mathematically guarantee that certain types of errors will not occur—a crucial step forward for the safe use of AI in sensitive applications.
From smartphones to self-driving cars, AI systems have become an everyday part of our lives. But in applications where safety is critical, one central question arises: Can we guarantee that an AI system won’t make serious mistakes—even when its input varies slightly?
A team from TU Wien—Dr. Andrey Kofnov, Dr. Daniel Kapla, Prof. Efstathia Bura and Prof. Ezio Bartocci—bringing together experts from mathematics, statistics and computer science, has now found a way to analyze neural networks, the brains of AI systems, in such a way that the possible range of outputs can be exactly determined for a given input range—and specific errors can be ruled out with certainty.
Devices taking advantage of the collective quantum behavior of spin excitations in magnetic materials—known as magnons—have the potential to improve quantum computing devices. However, using magnons in quantum devices requires an in-depth understanding of their nature and limitations. A new experimental technique uses superconducting qubits to sensitively characterize magnon behavior in previously unexplored regimes.
Researchers in the Grainger College of Engineering at the University of Illinois Urbana-Champaign have reported in the journal Physical Review Applied that highly excited magnon behavior in ferromagnetic materials can be accurately characterized by coupling the material to a superconducting qubit via a microwave cavity. This setup allowed the researchers to characterize both the number of magnons and their lifetimes when thousands of excitations are present, a regime that has not been studied well.
“To be useful in quantum computing applications, limitations on magnon systems need to be understood properly,” said Sonia Rani, the study’s lead author. “The problem is that there isn’t a good theory for when certain effects become important, and if we should expect them to lead to detrimental effects.
The race to build the first useful quantum computer is on and may revolutionize the world with brand new capabilities, from medicine to freight logistics.
Tech companies all want to take the crown, with Microsoft announcing the first of its kind quantum chip in February, only days before Google’s breakthrough on quantum error correction.
As the race heats up, companies are turning to a new ultracold solution—neutral atoms—which Swinburne University of Technology has been exploring and making discoveries in for two decades.
