Toggle light / dark theme

Quantum field theory suggests that the very structure of the universe could change, altering cosmos as we know it. A new quantum machine might help probe this elusive phenomenon, while also helping improve quantum computers.

Nearly 50 years ago, quantum field theory researchers proposed that the universe exists in a “false vacuum”. This would mean that the stable appearance of the cosmos and its physical laws might be on the verge of collapse. The universe, according to this theory, could be transitioning to a “true vacuum” state.

The theory comes from predictions about the behaviour of the Higgs field associated with the Higgs boson, which Cosmos first looked at nearly a decade ago – the article is worth reading.

Superconductors can carry electricity without losing energy, a superpower that makes them invaluable for a range of sought-after applications, from maglev trains to quantum computers. Generally, this comes at the price of having to keep them extremely cold, an opportunity cost that has frequently hindered widespread use.

Understanding of how work has also progressed, but there still remains a great deal about them that is unknown. For example, among many materials known to have , some do not behave according to conventional theory.

One such puzzling material is strontium ruthenate or Sr2RuO4, which has challenged scientists since it was discovered to be a superconductor in 1994. Initially, researchers thought this material had a special type of called a “spin-triplet” state, which is notable for its spin supercurrent. But even after considerable investigation, a full understanding of its behavior has remained a mystery.

In order to find rare processes from collider data, scientists use computer algorithms to determine the type and properties of particles based on the faint signals that they leave in the detector. One such particle is the tau lepton, which is produced, for example, in the decay of the Higgs boson.

The leaves a spray or jet of low-energy , the subtle pattern of which in the jet allows one to distinguish them from jets produced by other particles. The jet also contains about the energy of the tau lepton, which is distributed among the daughter particles, and on the way is decayed. Currently, the best algorithms use multiple steps of combinatorics and computer vision.

ChatGPT has shown much stronger performance in rejecting backgrounds than computer-vision based methods. In this paper, researchers showed that such language-based models can find the tau leptons from the jet patterns, and also determine the energy and decay properties more accurately than before.

For the first time, a team of researchers at Lawrence Livermore National Laboratory (LLNL) quantified and rigorously studied the effect of metal strength on accurately modeling coupled metal/high explosive (HE) experiments, shedding light on an elusive variable in an important model for national security and defense applications.

The team used a Bayesian approach to quantify with tantalum and two common explosive materials and integrated it into a coupled metal/HE . Their findings could lead to more accurate models for equation-of-state-studies, which assess the state of matter a material exists in under different conditions. Their paper —featured as an editor’s pick in the Journal of Applied Physics —also suggested that metal strength uncertainty may have an insignificant effect on result.

“There has been a long-standing field lore that HE model calibrations are sensitive to the metal strength,” said Matt Nelms, the paper’s first author and a group leader in LLNL’s Computational Engineering Division (CED). “By using a rigorous Bayesian approach, we found that this is not the case, at least when using tantalum.”

Antimony is widely used in the production of materials for electronics, as well as metal alloys resistant to corrosion and high temperatures.

“Antimony melt is interesting because near the melting point, the atoms in this melt can form bound structures in the form of compact clusters or extended chains and remain in a bound state for quite a long time. We found out that the basic unit of these structures are linked triplets of adjacent atoms, and the centers of mass of these linked atoms are located at the vertices of right triangles. It is from these triplets that larger structures are formed, the presence of which causes anomalous structural features detected in neutron and X-ray diffraction experiments,” explains Dr. Anatolii Mokshin, study supervisor and Chair of the Department of Computational Physics and Modeling of Physical Processes.

The computer modeling method based on quantum-chemical calculations made it possible to reproduce anomalies in the structure of molten with high accuracy.

Aurora consists of four photonically interconnected modular and independent server racks, containing 35 photonic chips and 13km of fiber optics. The system operates at room temperature and is fully automated, which Xanadu says makes it capable of running “for hours without any human intervention.”

The company added that in principle, Aurora could be scaled up to “thousands of server racks and millions of qubits today, realizing the ultimate goal of a quantum data center.” In a blog post detailing Aurora, Xanadu CTO Zachary Vernon said the machine represents the “very first time [Xanadu] – or anyone else for that matter – have combined all the subsystems necessary to implement universal and fault-tolerant quantum computation in a photonic architecture.”

Researchers have created a unique wristwatch that contains multiple modules, including a sensor array, a microfluidic chip, signal processing, and a data display system to monitor chemicals in human sweat. Their study is published in the journal ACS Nano.

“It can continuously and accurately monitor the levels of potassium (K+), sodium (Na+), and calcium (Ca2+) ions, offering both real-time and long-term tracking capabilities,” said senior researcher Prof. Huang Xingjiu from the Institute of Solid State Physics at the Hefei Institutes of Physical Sciences of Chinese Academy of Sciences.

Tremendous progress has been made in sweat sensors based on electrochemical methods, making it easier to track body changes. The stability of the sensor chip is crucial for its application effect and , which is the key to ensuring the long-term reliable operation of the sensor.

The electronics of the future can be made even smaller and more efficient by getting more memory cells to fit in less space. One way to achieve this is by adding the noble gas xenon when manufacturing digital memories.

This has been demonstrated by researchers at Linköping University in a study published in Nature Communications. This technology enables a more even material coating even in small cavities.

Twenty-five years ago, a camera memory card could hold 64 megabytes of information. Today, the same physical size memory card can hold 4 terabytes—over 60,000 times more information.