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Category: particle physics – Page 9

A research team led by The Hong Kong University of Science and Technology (HKUST) has achieved a groundbreaking quantum simulation of the non-Hermitian skin effect in two dimensions using ultracold fermions, marking a significant advance in quantum physics research.

Quantum mechanics, which typically considers a well-isolated system from its environment, describes ubiquitous phenomena ranging from electron behavior in solids to information processing in quantum devices. This description typically requires a real-valued observable—specifically, a Hermitian model (Hamiltonian).

The hermiticity of the model, which guarantees conserved energy with real eigenvalues, breaks down when a quantum system exchanges particles and energy with its environment. Such an open quantum system can be effectively described by a non-Hermitian Hamiltonian, providing crucial insights into , curved space, non-trivial topological phases, and even black holes. Nevertheless, many questions about non-Hermitian quantum dynamics remain unanswered, especially in higher dimensions.

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Glass might seem to be an ordinary material we encounter every day, but the physics at play inside are actually quite complex and still not completely understood by scientists. Some panes of glass, such as the stained-glass windows in many medieval buildings, have remained rigid for centuries, as their constituent molecules are perpetually frozen in a state of disorder.

Similarly, supercooled liquids are not quite solid, in the sense that their fundamental particles do not stick to a lattice pattern with , but they are also not ordinary liquids, because the particles also lack the energy to move freely. More research is required to reveal the physics of these complex systems.

In a study published in Nature Materials, researchers from the Institute of Industrial Science, the University of Tokyo have used advanced computer simulations to model the behavior of in a glassy supercooled liquid. Their approach was based on the concept of the Arrhenius activation energy, which is the a process must overcome to proceed.

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The intricate relationship between quantum mechanics and classical physics has long puzzled scientists. Quantum mechanics operates in a bizarre world where particles can exist in multiple states simultaneously, a concept known as superposition. However, this principle appears to break down in the macroscopic realm.

Planets, stars, and even the universe itself don’t exhibit such superpositions, creating a significant challenge in understanding how the universe transitions from quantum to classical behavior.

At the heart of this enigma is the question: how does the universe, if fundamentally quantum, adhere to classical laws like general relativity? This puzzle has led to groundbreaking work by researchers such as Matteo Carlesso and his colleagues at the University of Trieste.

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Beyond fermions and bosons: unveiling new particle behaviors in mechanics.

In the world, particles traditionally fall into two categories: fermions (like electrons) and bosons (like photons), each obeying distinct exchange rules. These “exchange statistics” shape the behaviors of particles, from the structure of atoms to the glow of lasers. In two dimensions, a peculiar third type, called anyons, has been theorized and observed, adding a twist to this framework. But could there be even more possibilities?

This study ventures into uncharted territory by revisiting “parastatistics,” an idea from theory that goes beyond fermions and bosons. Previously dismissed as merely theoretical and equivalent to the known particle types, parastatistics now emerges in a new light. The researchers reveal that particles obeying non-trivial parastatistics can exist in real physical systems and behave in fundamentally different ways. These “paraparticles” follow unique rules of exclusion, resulting in strange and exotic thermodynamic behaviors unlike any seen in fermions or bosons.

To bring this concept to life, the team developed a mathematical framework for paraparticles, showing how they naturally fit within the broader universe. They designed solvable models where paraparticles arise as quasiparticles—tiny, particle-like excitations in materials—observable through their distinct exchange behavior. Remarkably, these models work in both one and two dimensions, demonstrating the tangible potential of paraparticles in real-world systems.

The findings hint at exciting possibilities: a new class of quasiparticles in condensed matter physics and, perhaps more provocatively, the existence of elementary particles governed by entirely novel statistics. This discovery could expand our understanding of the world and open the door to unimagined phenomena in both theory and experiment.

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Scientists at Brown University have discovered a new class of quantum particles known as fractional excitons, which exhibit both fermion and boson characteristics.

This groundbreaking finding could pave the way for new phases of matter and enhance quantum computing by providing unique ways to manipulate quantum states.

Novel Quantum Particles Discovered

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An international research team, working with cutting-edge technology at the University of Nebraska–Lincoln, has made a discovery that may dramatically expand the materials used in next-generation, energy-efficient memory and logic devices.

The team, which includes Nebraska’s Abdelghani Laraoui, assistant professor of mechanical and materials engineering, successfully demonstrated for the first time the imaging of magnetic skyrmions at room temperature in composition engineered . The team observed the tiny, vortex-like particles in these magnetic materials using a nitrogen-vacancy scanning probe in Laraoui’s lab. The findings are published in ACS Nano.

“This discovery is a huge step forward because, until now, scientists could only observe these skyrmions in bulk chiral magnetic materials at very low temperatures,” Laraoui said. “Being able to study them at room temperature opens up a whole new world of applications and possibilities.”

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Bimetallic particles, composed of a noble metal and a base metal, exhibit unique catalytic properties in selective heterogeneous hydrogenations due to their distinct geometric and electronic structures. At the molecular level, effective and selective hydrogenation requires site-specific interactions where the active atoms on the catalyst particle selectively engage with the functional group targeted for transformation in the substrate.

Reducing the particle to nanoscale atomic clusters and single-atom alloys enhances surface dispersion and improves the efficient utilization of atoms. These size reductions also simultaneously change the electronic structure of the , which significantly impacts the intrinsic activity or product distributions.

By precisely tuning the bonding structures of noble metal single atoms with the base metal host, reactants are flexibly accommodated and the electronic properties are fine-tuned to activate specific functional groups. However, the fabrication of such atomically precise active sites remains a challenge.

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How does the Earth generate its magnetic field? While the basic mechanisms seem to be understood, many details remain unresolved. A team of researchers from the Center for Advanced Systems Understanding at the Helmholtz-Zentrum Dresden-Rossendorf, Sandia National Laboratories (U.S.) and the French Alternative Energies and Atomic Energy Commission has introduced a simulation method that promises new insights into the Earth’s core.

The method, presented in the Proceedings of the National Academy of Sciences, simulates not only the behavior of atoms, but also the magnetic properties of materials. The approach is significant for geophysics and could support the development of neuromorphic computing—an approach to more efficient AI systems.

The Earth’s magnetic field is essential for sustaining life, as it shields the planet from cosmic radiation and solar wind. It is generated by the geodynamo effect. “We know that the Earth’s core is primarily composed of iron,” explains Attila Cangi, Head of the Machine Learning for Materials Design department at CASUS.

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