Scientists have developed a groundbreaking tool called Effort.jl that lets them simulate the structure of the universe using just a laptop. The team created a system that dramatically speeds up how researchers study cosmic data, turning what once took days of supercomputer time into just a few hours. This new approach helps scientists explore massive datasets, test models, and fine-tune their understanding of how galaxies form and evolve.
From the article:
“We have demonstrated that it is impossible to describe all aspects of physical reality using a computational theory of quantum gravity,” says Dr. Faizal. “Therefore, no physically complete and consistent theory of everything can be derived from computation alone. Rather, it requires a non-algorithmic understanding, which is more fundamental than the computational laws of quantum gravity and therefore more fundamental than spacetime itself.”
It’s a plot device beloved by science fiction: our entire universe might be a simulation running on some advanced civilization’s supercomputer. But new research from UBC Okanagan has mathematically proven this isn’t just unlikely—it’s impossible.
Dr. Mir Faizal, Adjunct Professor with UBC Okanagan’s Irving K. Barber Faculty of Science, and his international colleagues, Drs. Lawrence M. Krauss, Arshid Shabir and Francesco Marino have shown that the fundamental nature of reality operates in a way that no computer could ever simulate.
Their findings, published in the Journal of Holography Applications in Physics, go beyond simply suggesting that we’re not living in a simulated world like The Matrix. They prove something far more profound: the universe is built on a type of understanding that exists beyond the reach of any algorithm.
Deeper insight into PPIs is essential for advancing the development of new treatments and vaccines.
PLM-Interact offers a powerful new lens into these critical mechanisms.
The key to PLM-Interact’s success lies in its training. Leveraging the supercomputer, the researchers trained the model on as many as 421,000 human protein pairs.
Scientists at the University of Glasgow have harnessed a powerful supercomputer, normally used by astronomers and physicists to study the universe, to develop a new machine learning model which can help translate the language of proteins.
In a new study published in Nature Communications, the cross-disciplinary team developed a large language model (LLM), called PLM-Interact, to better understand protein interactions, and even predict which mutations will impact how these crucial molecules “talk” to one another.
Early tests of PLM-interact, a protein language model (PLM), show that it outperforms competing models in understanding and predicting how proteins interact with one another. The team’s research demonstrates PLM-interact could help us better understand key areas of medical science, including the development of diseases such as cancer and virus infection.
Researchers from Google Quantum AI report that their quantum processor, Willow, ran an algorithm for a quantum computer that solved a complex physics problem thousands of times faster than the world’s most powerful classical supercomputers. If verified, this would be one of the first demonstrations of practical quantum advantage, in which a quantum computer solves a real-world problem faster and more accurately than a classical computer.
In a new paper published in the journal Nature, the researchers provided details on how their algorithm, called Quantum Echoes, measured the complex behavior of particles in highly entangled quantum systems. These are systems in which multiple particles are linked so that they share the same fate even when physically separated. If you measure the property of one particle, you instantly know something about the others. This linkage makes the overall system so complex that it is difficult to model on ordinary computers.
The Quantum Echoes algorithm uses a concept called an Out-of-Time-Order Correlator (OTOC), which measures how quickly information spreads and scrambles in a quantum system. The researchers chose this specific measurement because, as they state in the paper, “OTOCs have quantum interference effects that endow them with a high sensitivity to details of the quantum dynamics and, for OTOC, also high levels of classical simulation complexity. As such, OTOCs are viable candidates for realizing practical quantum advantage.”
UB physicists have upgraded an old quantum shortcut, allowing ordinary laptops to solve problems that once needed supercomputers. A team at the University at Buffalo has made it possible to simulate complex quantum systems without needing a supercomputer. By expanding the truncated Wigner approximation, they’ve created an accessible, efficient way to model real-world quantum behavior. Their method translates dense equations into a ready-to-use format that runs on ordinary computers. It could transform how physicists explore quantum phenomena.
Picture diving deep into the quantum realm, where unimaginably small particles can exist and interact in more than a trillion possible ways at the same time.
It’s as complex as it sounds. To understand these mind-bending systems and their countless configurations, physicists usually turn to powerful supercomputers or artificial intelligence for help.
Imagine industrial processes that make materials or chemical compounds faster, cheaper, and with fewer steps than ever before. Imagine processing information in your laptop in seconds instead of minutes or a supercomputer that learns and adapts as efficiently as the human brain. These possibilities all hinge on the same thing: how electrons interact in matter.
A team of Auburn University scientists has now designed a new class of materials that gives scientists unprecedented control over these tiny particles. Their study, published in ACS Materials Letters, introduces the tunable coupling between isolated-metal molecular complexes, known as solvated electron precursors, where electrons aren’t locked to atoms but instead float freely in open spaces.
From their key role in energy transfer, bonding, and conductivity, electrons are the lifeblood of chemical synthesis and modern technology. In chemical processes, electrons drive redox reactions, enable bond formation, and are critical in catalysis. In technological applications, manipulating the flow and interactions between electrons determines the operation of electronic devices, AI algorithms, photovoltaic applications, and even quantum computing. In most materials, electrons are bound tightly to atoms, which limits how they can be used. But in electrides, electrons roam freely, creating entirely new possibilities.
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