Lifeboat Foundation

The BASE experiment aims to answer this question by precisely measuring the properties of antiprotons, such as their intrinsic magnetic moment, and then comparing these measurements with those taken with protons. However, the precision the experiment can achieve is limited by its location.

“The accelerator equipment in the AD hall generates magnetic field fluctuations that limit how far we can push our precision measurements,” said BASE spokesperson Stefan Ulmer. “If we want to get an even deeper understanding of the fundamental properties of antiprotons, we need to move out.”

This is where BASE-STEP comes in. The goal is to trap antiprotons and then transfer them to a facility where scientists can study them with a greater precision. To be able to do this, they need a device that is small enough to be loaded onto a truck and can resist the bumps and vibrations that are inevitable during ground transport.

The AI system is dubbed a “quantum-tunneling deep neural network” and combines neural networks with quantum tunneling. A deep neural network is a collection of machine learning algorithms inspired by the structure and function of the brain — with multiple layers of nodes between the input and output. It can model complex non-linear relationships and, unlike conventional neural networks (which include a single layer between input and output) deep neural networks include many hidden layers.

Quantum tunneling, meanwhile, occurs when a subatomic particle, such as an electron or photon (particle of light), effectively passes through an impenetrable barrier. Because a subatomic particle like light can also behave as a wave — when it is not directly observed it is not in any fixed location — it has a small but finite probability of being on the other side of the barrier. When sufficient subatomic particles are present, some will “tunnel” through the barrier.

After the data representing the optical illusion passes through the quantum tunneling stage, the slightly altered image is processed by a deep neural network.

What is the heaviest element in the universe? Are there infinitely many elements? Where and how could superheavy elements be created naturally?

The heaviest abundant element known to exist is uranium, with 92 protons (the atomic number “Z”). But scientists have succeeded in synthesizing superheavy elements up to oganesson, with a Z of 118. Immediately before it are livermorium, with 116 protons and tennessine, which has 117.

All have short half-lives—the amount of time for half of an assembly of the element’s atoms to decay—usually less than a second and some as short as a microsecond. Creating and detecting such elements is not easy and requires powerful particle accelerators and elaborate measurements.

Researchers at the University of Chicago and Argonne National Lab have developed a new type of optical memory that stores data by transferring light from rare-earth element atoms embedded in a solid material to nearby quantum defects. They published their study in Physical Review Research.

This finding, achieved independently by a team at Pennsylvania State University published in the same journal, holds immense potential for the development of nanophotonic devices.

Manipulating the flow of light in materials at small scales is crucial for creating efficient nanophotonic chips, the building blocks for future optical devices. In the realm of electronics, scientists can control the movement of electrons using magnetic fields.

The Lorentz force, exerted by the magnetic field, dictates the electron’s trajectory. However, this approach is inapplicable to photons – the fundamental particles of light – as they lack an electrical charge.

“Dark matter searches are currently one of the hot topics in the high energy physics community. We look for weakly interacting particles in a number of different facilities ranging from accelerator experiments to tabletop laboratory setups,” Alina Kleimenova and Stefan Ghinescu, part of the NA62 Collaboration, told Phys.org.

“While LHC experiments rely on the high collision energy, smashing protons at about 14 trillion electron volts, NA62, being a fixed-target experiment, focuses on the high intensity approach with a quintillion (10¹⁸) of protons on target per year. This intensity creates a unique opportunity to probe various rare processes and beyond Standard Model scenarios.”

Dark photons, also referred to as A’, are among the hypothetical particles beyond the Standard Model whose existence could be probed by the NA62 detector. These particles could act as mediators between known visible matter and dark matter.

Heating a plasma for fusion research requires megawatts of power. One approach that research tokamaks use to achieve the necessary power input is neutral beam injection (NBI). With NBI, fast neutral particles are generated in a device called a beam source and then injected into the plasma.

Researchers have developed a new detector that analyzes antineutrinos emitted by nuclear reactors to monitor their activities from great distances.

This technology, which utilizes the phenomena of Cherenkov radiation, could revolutionize how we ensure reactors are not producing material for nuclear weapons, despite challenges from other environmental antineutrinos.

Nuclear Fission and Antimatter Monitoring.

A cornerstone of the US fusion research program, the DIII-D National Fusion Facility, has accomplished a major achievement. The nuclear fusion facility has completed its 200,000th experimental cycle.

“While completing 200,000 shots is impressive in its own right, this achievement is far more than a mere number,” said Dr Richard Buttery, Director of the DIII-D National Fusion Facility.

Nuclear fusion has long been hailed as the “holy grail” of clean energy. It is the process of nuclear fusion itself that powers the sun and stars. Unlike nuclear fission, which splits atoms and generates radioactive waste, fusion involves combining lighter atoms to form heavier ones.