DUNE, a neutrino research project, seeks to unravel the matter-antimatter imbalance mystery by tracking neutrino transformations.
Category: particle physics – Page 151
A unique photograph of the Milky Way galaxy was captured using the IceCube detector, which observes high-energy neutrinos from space.
A team from TU Dortmund University recently succeeded in producing a highly durable time crystal that lived millions of times longer than could be shown in previous experiments. By doing so, they have corroborated an extremely interesting phenomenon that Nobel Prize laureate Frank Wilczek postulated around ten years ago and which had already found its way into science fiction movies.
The results have been published in Nature Physics.
Crystals or, to be more precise, crystals in space, are periodic arrangements of atoms over large length scales. This arrangement gives crystals their fascinating appearance, with smooth facets like in gemstones.
In research that could jumpstart work toward the quantum internet, researchers at MIT and the University of Cambridge have built and tested an exquisitely small device that could allow the quick, efficient flow of quantum information over large distances.
Key to the device is a “microchiplet” made of diamond in which some of the diamond’s carbon atoms are replaced with atoms of tin. The team’s experiments indicate that the device, consisting of waveguides for the light to carry the quantum information, solves a paradox that has stymied the arrival of large, scalable quantum networks.
Quantum information in the form of quantum bits, or qubits, is easily disrupted by environmental noise, like magnetic fields, that destroys the information. So on one hand, it’s desirable to have qubits that don’t interact strongly with the environment. On the other hand, however, those qubits need to strongly interact with the light, or photons, key to carrying the information over distances.
A team of Rice University researchers mapped out how flecks of 2D materials move in liquid ⎯ knowledge that could help scientists assemble macroscopic-scale materials with the same useful properties as their 2D counterparts.
“Two-dimensional nanomaterials are extremely thin—only several atoms thick—sheet-shaped materials,” said Utana Umezaki, a Rice graduate student who is a lead author on a study published in ACS Nano. “They behave very differently from materials we’re used to in daily life and can have really useful properties: They can withstand a lot of force, resist high temperatures and so on. To take advantage of these unique properties, we have to find ways to turn them into larger-scale materials like films and fibers.”
In order to maintain their special properties in bulk form, sheets of 2D materials have to be properly aligned ⎯ a process that often occurs in solution phase. Rice researchers focused on graphene, which is made up of carbon atoms, and hexagonal boron nitride, a material with a similar structure to graphene but composed of boron and nitrogen atoms.
A consensus has arisen in the astronomical community that familiar matter made of atoms is not the dominant form of matter in the Universe. Instead, an invisible form of matter, called dark matter, is thought to be far more prevalent. However, a small group of researchers deny the existence of dark matter, instead saying our understanding of how objects move is incomplete. A recent paper in the Monthly Notices of the Royal Astronomical Society seems to have ruled this out definitively.
Stars, planets, and galaxies move under the direction of the force of gravity, and Isaac Newton worked out the laws that govern that motion, which we now call Newtonian dynamics. However, despite the enormous success of Newtonian dynamics, this success is not universal. Indeed, when Newton’s equations are applied to certain astronomical phenomena, they do not make the correct predictions. One such example is the speed at which galaxies rotate. When astronomers measure the speed of stars in the periphery of a galaxy, they move faster than can be explained by accepted theory. Instead, the galaxies should fly apart.
The solution to this mystery favored by most scientists is that beyond the familiar stars and clouds of gas, our galaxy also hosts a large amount of invisible matter, called dark matter. This dark matter adds to the gravitational force holding the galaxy together. Thus, the evidence for dark matter is indirect. It has never been observed in the laboratory; yet its ability to explain the motion of galaxies is strong circumstantial evidence that it exists.
Artificial intelligence using neural networks performs calculations digitally with the help of microelectronic chips. Physicists at Leipzig University have now created a type of neural network that works not with electricity but with so-called active colloidal particles. In their publication in Nature Communications, the researchers describe how these microparticles can be used as a physical system for artificial intelligence and the prediction of time series.
“Our neural network belongs to the field of physical reservoir computing, which uses the dynamics of physical processes, such as water surfaces, bacteria or octopus tentacle models, to make calculations,” says Professor Frank Cichos, whose research group developed the network with the support of ScaDS.AI.
“In our realization, we use synthetic self-propelled particles that are only a few micrometers in size,” explains Cichos. “We show that these can be used for calculations and at the same time present a method that suppresses the influence of disruptive effects, such as noise, in the movement of the colloidal particles.” Colloidal particles are particles that are finely dispersed in their dispersion medium (solid, gas or liquid).
The scattering of helium atoms off a crystal surface reveals how defects in the crystal’s lattice influence its ability to transport heat.
As artificial intelligence technologies such as Chat-GPT are utilized in various industries, the role of high-performance semiconductor devices for processing large amounts of information is becoming increasingly important. Among them, spin memory is attracting attention as a next-generation electronics technology because it is suitable for processing large amounts of information with lower power than silicon semiconductors that are currently mass-produced.
Utilizing recently discovered quantum materials in spin memory is expected to dramatically improve performance by improving signal ratio and reducing power, but to achieve this, it is necessary to develop technologies to control the properties of quantum materials through electrical methods such as current and voltage.
Dr. Jun Woo Choi of the Center for Spintroncs Research at the Korea Institute of Science and Technology (KIST) and Professor Se-Young Park of the Department of Physics at Soongsil University have announced the results of a collaborative study showing that ultra-low-power memory can be fabricated from quantum materials. The findings are published in the journal Nature Communications.