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An international research collaboration has harnessed supercomputing power to better understand how massive slabs of ancient ocean floors are shaped as they sink hundreds of kilometers below Earth’s surface.
Sophisticated computer models developed by researchers in the UK, Switzerland and the U.S. have cast new light on the complex physical interactions which govern the sliding and sinking of the ancient ocean floor, also referred to as subducted slabs, through Earth’s mantle, a process known as subduction.
Researchers from the University of Glasgow led the study. Their paper, “The Role of the Overriding Plate and Mantle Viscosity Structure on Deep Slab Morphology,” is published in Geochemistry, Geophysics, Geosystems.
Since the early 20th century, scientists have gathered compelling evidence that the universe is expanding at an accelerating rate. This acceleration is attributed to what is known as dark energy—a fundamental property of spacetime that has a repulsive effect on galaxies.
For decades, the leading cosmological model, known as the Lambda Cold Dark Matter (ΛCDM), has assumed that dark energy is a constant entity, unchanging throughout cosmic time. While this simple assumption has served as the bedrock of modern cosmology, it has left a fundamental question unanswered: what if dark energy is not constant, but instead a time-varying property of the universe?
Recent observations have provided some of the first hints that the above-mentioned assumption may not be correct. The Dark Energy Spectroscopic Instrument (DESI), a sophisticated experiment for conducting astronomical surveys of distant galaxies, has produced data suggesting a preference for a dynamic dark energy (DDE) component.
The future of computing lies in the surprising world of quantum physics, where the rules are much different from the ones that power today’s devices. Quantum computers promise to tackle problems too complex for even the fastest supercomputers running on silicon chips. To make this vision real, scientists around the world are searching for new quantum materials with unusual, almost otherworldly properties.
One of the more intriguing candidates is called a quantum spin liquid—a state of matter where electron spins never settle down, even at the coldest temperatures in the universe. To date, however, preparing such a quantum state in a lab has proven stubbornly elusive. In a collaborative project with multiple institutions, scientists at the U.S. Department of Energy’s (DOE) Argonne National Laboratory now report coming tantalizingly closer.
As explained by Argonne Senior Physicist and Group Leader Daniel Haskel, in these materials, it’s not atoms that stay fluid as in an ordinary liquid, but the tiny magnetic orientations—or spins—of electrons. Each spin wants to “get along” with its neighbors by aligning in a way that keeps everyone content. But when the spins are pushed closer together under pressure, satisfying every neighbor becomes impossible.
In the 17th century, astronomers Christiaan Huygens and Giovanni Cassini trained their telescopes on Saturn and uncovered a startling truth: the planet’s luminous bands were not solid appendages, but vast, separate rings composed of countless nested arcs.
Centuries later, NASA’s Cassini–Huygens (Cassini) probe carried the exploration of Saturn even further. Beginning in 2005, it sent back a stream of spectacular images that transformed scientists’ understanding of the system. Among its most dramatic revelations were the towering geysers on Saturn’s icy moon Enceladus, which blasted debris into space and left behind a faint sub-ring encircling the planet.
New supercomputer simulations from the Texas Advanced Computing Center (TACC) based on the Cassini space probe’s data have found improved estimates of ice mass Enceladus is losing to space. These findings help with understanding and future robotic exploration of what’s below the surface of the icy moon, which might harbor life.
Integrated circuits form the basis of modern ‘classical’ computing. There can be hundreds of these microchips in a laptop or personal computer. Their size has meant that now mobile phones have computing power thousands of times faster than the most powerful supercomputers built in the 1980s.
Since the 1990s, supercomputers have come into their own. The most powerful supercomputer in the world, Frontier based in the US, has a million times more computing power than top-tier gaming PCs. But these devices are still based on the classical technology of integrated circuits and are therefore limited in their capabilities.
Quantum computers promise to be able to process calculations thousands, even millions of times faster than modern computers.
OpenAI and NVIDIA today announced a letter of intent for a landmark strategic partnership to deploy at least 10 gigawatts of NVIDIA systems for OpenAI’s next-generation AI infrastructure to train and run its next generation of models on the path to deploying superintelligence. To support this deployment including data center and power capacity, NVIDIA intends to invest up to $100 billion in OpenAI as the new NVIDIA systems are deployed. The first phase is targeted to come online in the second half of 2026 using the NVIDIA Vera Rubin platform.
“NVIDIA and OpenAI have pushed each other for a decade, from the first DGX supercomputer to the breakthrough of ChatGPT,” said Jensen Huang, founder and CEO of NVIDIA. “This investment and infrastructure partnership mark the next leap forward — deploying 10 gigawatts to power the next era of intelligence.”
“Everything starts with compute,” said Sam Altman, cofounder and CEO of OpenAI. “Compute infrastructure will be the basis for the economy of the future, and we will utilize what we’re building with NVIDIA to both create new AI breakthroughs and empower people and businesses with them at scale.”
Researchers have discovered a novel criterion for sorting particles in microfluidic channels, paving the way for advancements in disease diagnostics and liquid biopsies. Using the supercomputer “Fugaku,” a joint team from the University of Osaka, Kansai University and Okayama University revealed that soft particles, like biological cells, exhibit unique focusing patterns compared to rigid particles.
The outcomes, published in the Journal of Fluid Mechanics, pave the way for next-generation microfluidic devices leveraging cell and particle deformability, promising highly efficient cell sorting with biomedical applications such as early cancer detection.
Microfluidics involves manipulating fluids at a microscopic scale. Controlling particle movement within microchannels is crucial for cell sorting and diagnostics, expected to realize early cancer detection and treatment. While prior research focused on rigid particles, which typically focus near channel walls, the behavior of deformable particles remained largely unexplored.
