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Now Princeton researchers have sparked new life into static. Using millions of hours of computational time to run detailed simulations, the researchers found a way to describe static charge atom-by-atom with the mathematics of heat and work. Their paper appeared in Nature Communications on March 23.

The study looked specifically at how charge moves between materials that do not allow the free flow of electrons, called insulating materials, such as vinyl and acrylic. The researchers said there is no established view on what mechanisms drive these jolts, despite the ubiquity of static: the crackle and pop of clothes pulled from a dryer, packing peanuts that cling to a box.

“We know it’s not electrons,” said Mike Webb, assistant professor of chemical and biological engineering, who led the study. “What is it?”

Theoretical physicists employ their imaginations and their deep understanding of mathematics to decipher the underlying laws of the universe that govern particles, forces and everything in between. More and more often, theorists are doing that work with the help of machine learning.

As might be expected, the group of theorists using machine learning includes people classified as “computational” theorists. But it also includes “formal” theorists, the people interested in the self-consistency of theoretical frameworks, like string theory or quantum gravity. And it includes “phenomenologists,” the theorists who sit next to experimentalists, hypothesizing about new particles or interactions that could be tested by experiments; analyzing the data the experiments collect; and using results to construct new models and dream up how to test them experimentally.

In all areas of theory, machine-learning algorithms are speeding up processes, performing previously impossible calculations, and even causing theorists to rethink the way theoretical physics research is done.

A team at HZB has investigated a new, simple method at BESSY II that can be used to create stable radial magnetic vortices in magnetic thin films.

In some materials, spins form complex magnetic structures within the nanometre and micrometer scale in which the magnetization direction twists and curls along specific directions. Examples of such structures are magnetic bubbles, skyrmions, and magnetic vortices.

Spintronics aims to make use of such tiny magnetic structures to store data or perform logic operations with very low power consumption, compared to today’s dominant microelectronic components. However, the generation and stabilization of most of these magnetic textures is restricted to a few materials and achievable under very specific conditions (temperature, magnetic field…).

The elegant equations of classical electromagnetism written by James Clark Maxwell in 1861 display a remarkable symmetry between electric and magnetic fields except for their sources. We know about electric charges but we have not found magnetic charges. Bar magnets are dipoles with two poles, north and south, for the magnetic field, resembling the configuration of an electric field sourced by a pair of positive and negative electric charges. However, we had never seen experimental evidence for a magnetic monopole, namely a magnetic charge with only one magnetic pole, a net north or south, from where magnetic field lines emanate, just like the electric field sourced by an electric charge. In a symmetric theory of electromagnetism, magnetic monopoles should exist.

The existence of monopoles with a net magnetic charge was proposed by Paul Dirac in 1931 to explain the quantized (discrete) values of electric charges. Dirac found that magnetic charges should be an integer multiple of a fundamental unit, g_D, equal to the electron charge, e, divided by twice the fine-structure constant, or about 68.5e.

In classical physics, the existence of magnetic monopoles restores symmetry to Maxwell’s equations. But in the broader context of quantum mechanics, Gerard ‘t Hooft and Alexander Polyakov showed in 1974 that magnetic monopoles are required in Grand Unified Theories of the strong, weak and electromagnetic interactions. Since the electric charge is quantized, magnetic charges are unavoidable in these theories. Magnetic charges with the lowest mass must be stable because magnetic charge is conserved and they cannot decay into lower-mass particles.

For the first time, researchers have simulated neurological junctions called synapses using the same water and salt ingredients the brain uses, contributing to an emerging field that combines biology with electronics called iontronics.

The team from Utrecht University in the Netherlands and Sogang University in South Korea claim to have been inspired by the functioning of the human brain, which also uses charged particles called ions dissolved in water to transmit signals within neurons.

An important feature of the brain’s ability to process information is synaptic plasticity, which allows neurons to adjust the strength of connections between them in response to input history.

The potential of quantum technology is huge but is today largely limited to the extremely cold environments of laboratories. Now, researchers at Stockholm University, at the Nordic Institute for Theoretical Physics and at the Ca’ Foscari University of Venice have succeeded in demonstrating for the very first time how laser light can induce quantum behavior at room temperature — and make non-magnetic materials magnetic. The breakthrough is expected to pave the way for faster and more energy-efficient computers, information transfer and data storage.

Within a few decades, the advancement of quantum technology is expected to revolutionize several of society’s most important areas and pave the way for completely new technological possibilities in communication and energy.

Of particular interest for researchers in the field are the peculiar and bizarre properties of quantum particles — which deviate completely from the laws of classical physics and can make materials magnetic or superconducting.

The late physicist Joseph Polchinski once said the existence of magnetic monopoles is “one of the safest bets that one can make about physics not yet seen.” In its quest for these particles, which have a magnetic charge and are predicted by several theories that extend the Standard Model, the MoEDAL collaboration at the Large Hadron Collider (LHC) has not yet proven Polchinski right, but its latest findings mark a significant stride forward.

The results, reported in two papers posted on the arXiv preprint server, considerably narrow the search window for these hypothetical particles.

At the LHC, pairs of could be produced in interactions between protons or . In collisions between protons, they could be formed from a single virtual photon (the Drell–Yan mechanism) or the fusion of two virtual photons (the photon-fusion mechanism). Pairs of magnetic monopoles could also be produced from the vacuum in the enormous magnetic fields created in near-miss heavy-ion collisions, through a process called the Schwinger mechanism.

Materials that are incredibly thin, only a few atoms thick, exhibit unique properties that make them appealing for energy storage, catalysis, and water purification. Researchers at Linköping University, Sweden, have now developed a method that enables the synthesis of hundreds of new 2D materials. Their study has been published in the journal Science.

Since the discovery of graphene, the field of research in extremely thin materials, so-called 2D materials, has increased exponentially. The reason is that 2D materials have a large surface area in relation to their volume or weight. This gives rise to a range of physical phenomena and distinctive properties, such as good conductivity, high strength or heat resistance, making 2D materials of interest both within fundamental research and applications.