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Materials scientists at Duke University have shown the first clear example that a material’s transition into a magnet can control instabilities in its crystalline structure that cause it to change from a conductor to an insulator.

If researchers can learn to control this unique connection between identified in hexagonal iron sulfide, it could enable new technologies such as spintronic computing. The results appear April 13 in the journal Nature Physics.

Commonly known as troilite, hexagonal iron sulfide can be found natively on Earth but is more abundant in meteorites, particularly those originating from the Moon and Mars. Rarely encountered in the Earth’s crust, most troilite on Earth is believed to have originated from space.

:oooo.


Past cosmological and astrophysical observations suggest that over one quarter of the universe’s energy density is made up of a non-conventional type of matter known as dark matter. This type of matter is believed to be composed of particles that do not absorb, emit or reflect light, and thus cannot be observed directly using conventional detection methods.

Researchers worldwide have carried out studies aimed at detecting dark matter in the universe, yet so far, none of them has been successful. Even the for dark matter, weakly interacting massive particles (WIMPs), have not yet been observed experimentally.

The China Dark Matter Experiment (CDEX) collaboration, a large team of researchers at Tsinghua University and other universities in China, has recently conducted a search for a different possible dark matter candidate known as the dark . While the search was unsuccessful, their paper, published in Physical Review Letters, identifies new constraints on a dark photon parameter that could inform future studies.

Nowadays, artificial neural networks have an impact on many areas of our day-to-day lives. They are used for a wide variety of complex tasks, such as driving cars, performing speech recognition (for example, Siri, Cortana, Alexa), suggesting shopping items and trends, or improving visual effects in movies (e.g., animated characters such as Thanos from the movie Infinity War by Marvel).

Traditionally, algorithms are handcrafted to solve complex tasks. This requires experts to spend a significant amount of time to identify the optimal strategies for various situations. Artificial neural networks — inspired by interconnected neurons in the brain — can automatically learn from data a close-to-optimal solution for the given objective. Often, the automated learning or “training” required to obtain these solutions is “supervised” through the use of supplementary information provided by an expert. Other approaches are “unsupervised” and can identify patterns in the data. The mathematical theory behind artificial neural networks has evolved over several decades, yet only recently have we developed our understanding of how to train them efficiently. The required calculations are very similar to those performed by standard video graphics cards (that contain a graphics processing unit or GPU) when rendering three-dimensional scenes in video games.

Circa 2011 essentially a magnet could be a battery and cpu and a gpu with magnonics.


Harvard physicists have expanded the possibilities for quantum engineering of novel materials such as high-temperature superconductors by coaxing ultracold atoms trapped in an optical lattice — a light crystal — to self-organize into a magnet, using only the minute disturbances resulting from quantum mechanics. The research, published in the journal Nature, is the first demonstration of such a “quantum magnet” in an optical lattice.

As modern technology depends more and more on materials with exotic quantum mechanical properties, researchers are coming up against a natural barrier.

“The problem is that what makes these materials useful often makes them extremely difficult to design,” said senior author Markus Greiner, an associate professor in Harvard’s Department of Physics. “They can become entangled, existing in multiple configurations at the same time. This hallmark of quantum mechanics is difficult for normal computers to represent, so we had to take another approach.”

Synthetic microparticles more intricate than some of the most complicated ones found in nature have been produced by a University of Michigan-led international team. They also investigated how that intricacy arises and devised a way to measure it.

The findings pave the way for more stable fluid-and-particle mixes, such as paints, and new ways to twist light—a prerequisite for holographic projectors.

The particles are composed of twisted spikes arranged into a ball a few microns, or millionths of a meter, across.

Error free qubits o.,o.


Physicists at MIT and elsewhere have observed evidence of Majorana fermions—particles that are theorized to also be their own antiparticle—on the surface of a common metal: gold. This is the first sighting of Majorana fermions on a platform that can potentially be scaled up. The results, published in the Proceedings of the National Academy of Sciences, are a major step toward isolating the particles as stable, error-proof qubits for quantum computing.

In particle physics, fermions are a class of elementary particles that includes electrons, protons, neutrons, and quarks, all of which make up the building blocks of matter. For the most part, these particles are considered Dirac fermions, after the English physicist Paul Dirac, who first predicted that all fermionic fundamental particles should have a counterpart, somewhere in the universe, in the form of an antiparticle—essentially, an identical twin of opposite charge.

In 1937, the Italian theoretical physicist Ettore Majorana extended Dirac’s theory, predicting that among fermions, there should be some particles, since named Majorana fermions, that are indistinguishable from their antiparticles. Mysteriously, the physicist disappeared during a ferry trip off the Italian coast just a year after making his prediction. Scientists have been looking for Majorana’s enigmatic particle ever since. It has been suggested, but not proven, that the neutrino may be a Majorana particle. On the other hand, theorists have predicted that Majorana fermions may also exist in solids under special conditions.

O,.,o.


Since their invention in the 1930s, electron microscopes have helped scientists peer into the atomic structure of ordinary materials like steel, and even exotic graphene. But despite these advances, such imaging techniques cannot precisely map out the 3D atomic structure of materials in a liquid solution, such as a catalyst in a hydrogen fuel cell, or the electrolytes in your car’s battery.

Now, researchers at Berkeley Lab, in collaboration with the Institute for Basic Science in South Korea, Monash University in Australia, and UC Berkeley, have developed a technique that produces atomic-scale 3D images of nanoparticles tumbling in liquid between sheets of graphene, the thinnest material possible.

3D images of platinum particles between 2-3 nm in diameter shown rotating in liquid under an electron microscope

3D images of platinum particles between 2–3 nm in diameter shown rotating in liquid under an electron microscope. Each nanoparticle has approximately 600 atoms. White spheres indicate the position of each atom in a nanoparticle. (Image: IBS)

In nuclear physics, like much of science, detailed theories alone aren’t always enough to unlock solid predictions. There are often too many pieces, interacting in complex ways, for researchers to follow the logic of a theory through to its end. It’s one reason there are still so many mysteries in nature, including how the universe’s basic building blocks coalesce and form stars and galaxies. The same is true in high-energy experiments, in which particles like protons smash together at incredible speeds to create extreme conditions similar to those just after the Big Bang.

Fortunately, scientists can often wield simulations to cut through the intricacies. A represents the important aspects of one system—such as a plane, a town’s traffic flow or an atom—as part of another, more accessible system (like a or a scale model). Researchers have used their creativity to make simulations cheaper, quicker or easier to work with than the formidable subjects they investigate—like proton collisions or black holes.

Simulations go beyond a matter of convenience; they are essential for tackling cases that are both too difficult to directly observe in experiments and too complex for scientists to tease out every logical conclusion from basic principles. Diverse research breakthroughs—from modeling the complex interactions of the molecules behind life to predicting the experimental signatures that ultimately allowed the identification of the Higgs boson—have resulted from the ingenious use of simulations.

Since the original work on Bose–Einstein condensation1,2, the use of quantum degenerate gases of atoms has enabled the quantum emulation of important systems in condensed matter and nuclear physics, as well as the study of many-body states that have no analogue in other fields of physics3. Ultracold molecules in the micro- and nanokelvin regimes are expected to bring powerful capabilities to quantum emulation4 and quantum computing5, owing to their rich internal degrees of freedom compared to atoms, and to facilitate precision measurement and the study of quantum chemistry6. Quantum gases of ultracold atoms can be created using collision-based cooling schemes such as evaporative cooling, but thermalization and collisional cooling have not yet been realized for ultracold molecules. Other techniques, such as the use of supersonic jets and cryogenic buffer gases, have reached temperatures limited to above 10 millikelvin7,8. Here we show cooling of NaLi molecules to micro- and nanokelvin temperatures through collisions with ultracold Na atoms, with both molecules and atoms prepared in their stretched hyperfine spin states. We find a lower bound on the ratio of elastic to inelastic molecule–atom collisions that is greater than 50—large enough to support sustained collisional cooling. By employing two stages of evaporation, we increase the phase-space density of the molecules by a factor of 20, achieving temperatures as low as 220 nanokelvin. The favourable collisional properties of the Na–NaLi system could enable the creation of deeply quantum degenerate dipolar molecules and raises the possibility of using stretched spin states in the cooling of other molecules.