Toggle light / dark theme

New AI model advances fusion power research by predicting the success of experiments

Practical fusion power that can provide cheap, clean energy could be a step closer thanks to artificial intelligence. Scientists at Lawrence Livermore National Laboratory have developed a deep learning model that accurately predicted the results of a nuclear fusion experiment conducted in 2022. Accurate predictions can help speed up the design of new experiments and accelerate the quest for this virtually limitless energy source.

In a paper published in Science, researchers describe how their AI model predicted with a probability of 74% that ignition was the likely outcome of a small 2022 fusion experiment at the National Ignition Facility (NIF). This is a significant advance as the model was able to cover more parameters with greater precision than traditional supercomputers.

Currently, nuclear power comes from nuclear fission, which generates energy by splitting atoms. However, it can produce radioactive waste that remains dangerous for thousands of years. Fusion generates energy by fusing atoms, similar to what happens inside the sun. The process is safer and does not produce any long-term radioactive waste. While it is a promising energy source, it is still a long way from being a viable commercial technology.

LHCb collaboration observes ultra-rare baryon decay

Baryons, composite particles made up of three quarks bound together via the so-called strong force, make up the most visible matter and have thus been the focus of numerous physics studies. Studying the rare processes via which unstable baryons decay into other particles could potentially contribute to the discovery of new physics that is not explained by the Standard Model of particle physics.

Theoretical study reveals failure of key quark-gluon plasma probe in low-energy region

According to theoretical predictions, within a millionth of a second after the Big Bang, nucleons had not yet formed, and matter existed as a hot, dense “soup” composed of freely moving quarks and gluons. This state of matter is known as quark-gluon plasma (QGP). Finding definitive evidence for the existence of QGP is crucial for understanding cosmic evolution.

Scientists Flip the Script and Solve a Longstanding Spintronics Challenge

A breakthrough in spintronics reveals that material defects can be harnessed to boost device efficiency, overturning decades of assumptions. Scientists have discovered a way to transform what was once considered a major problem in electronics, material defects, into a powerful quantum-based advan

Rapid-response protocol promises to reveal supernovae only hours after they explode

“They shine thanks to in their cores, but once the star has burned through progressively heavier atoms—right up to the point where further fusion no longer yields energy—the core collapses. At that point, the star collapses because gravity is no longer counterbalanced; the rapid contraction raises the internal pressure dramatically and triggers the explosion.”

The first hours and days after the blast preserve direct clues to the progenitor system—information that helps distinguish competing explosion models, estimate critical parameters, and study the local environment. “The sooner we see them, the better,” Galbany notes.

Historically, obtaining such early data was difficult because most supernovae were discovered days or weeks after the explosion. Modern wide-field, high-cadence surveys—covering large swaths of sky and revisiting them frequently—are changing that picture and allowing discoveries within mere hours or days.

A smart accelerator for qubits: Spin-orbit approach boosts both speed and stability

There are high hopes for quantum computers: they are supposed to perform specific calculations much faster than current supercomputers and, therefore, solve scientific and practical problems that are insurmountable for ordinary computers. The centerpiece of a quantum computer is the quantum bit, qubit for short, which can be realized in different ways—for instance, using the energy levels of atoms or the spins of electrons.

When making such qubits, however, researchers face a dilemma. On the one hand, a qubit needs to be isolated from its environment as much as possible. Otherwise, its quantum superpositions decay in a short time and the quantum calculations are disturbed. On the other hand, one would like to drive qubits as fast as possible in analogy with the clocking of classical bits, which requires a strong interaction with the environment.

Normally, these two conditions cannot be fulfilled at the same time, as a higher driving speed automatically entails a faster decay of the superpositions and, therefore, a shorter coherence time.

Predicting the topological properties of quantum spin liquids using Rydberg atom lattices

Topological quantum systems are physical systems exhibiting properties that depend on the overall connectivity of their underlying lattice, as opposed to local interactions and their microscopic structure. Predicting the evolution of these systems over time and their long-range quantum correlations is often challenging, as their behavior is not defined by magnetization or other parameters linked to local interactions.

Topological spin textures: Scientists use micro-structured materials to control light propagation

Topological spin textures, spatially organized patterns linked to the intrinsic angular momentum of particles, have proved to be highly advantageous for the development of spintronics and quantum technologies. One of the most studied among these textures are skyrmionic textures, which are two-dimensional and stable patterns of spin orientation. Recently, the study of skyrmionic textures has gained significant attention in the field of optics and photonics, revealing novel physical properties and promising potential applications.

/* */