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New superconductors identified, unlocking process that could yield thousands more

An international team of quantum researchers has shown how machine learning can be used to filter a practically infinite number of possible material combinations to identify candidates for superconductivity. Thanks to the breakthrough, new superconductors can now be found much faster, says Aalto University Professor Päivi Törmä, who leads the SuperC consortium behind the research.

Superconductors carry electric current with zero resistance, thanks to a quantum effect appearing only at extremely low temperatures. They power not only quantum computers but many other things, from neuroimaging to fusion reactors and maglev trains.

However, these unicorn materials are prohibitively hard to identify. Any endlessly variable combination of elements could be a superconductor—yet few actually are. And the ones already discovered require expensive cooling equipment to bring them to the near-absolute-zero temperatures that give them their quantum properties.

Disorder creates direction-dependent optics in compound semiconductors

An international research team has demonstrated that the intrinsic disorder of the compound semiconductor CuInSnS₄ can be exploited to influence its optical properties. While the atomic vibrations also sense the local disorder, their response is averaged over many different local environments and therefore appears isotropic, as expected for a cubic crystal.

In contrast, the optical excitations, known as excitons, are much more sensitive to the local arrangement of atoms. Surprisingly, they show a direction-dependent optical response even though the average crystal structure is cubic. These findings shed new light on the relationship between disorder and material properties, opening new options for targeted “disorder engineering” in optoelectronic and photocatalytic devices.

Crystals are typically characterized by a periodic arrangement of atoms, in which each element occupies well-defined crystallographic sites throughout the structure. In compound semiconductors such as CuInSnS₄, a member of the adamantine chalcogenide family, the cations are ideally distributed over specific positions in the crystal structure.

World’s largest particle smasher halts for upgrade to boost hunt for dark matter

The world’s most powerful particle accelerator will shutter operations Monday for four years of renovations to dramatically boost its collision capacity and the potential for unlocking one of the greatest mysteries of the universe: dark matter.

The Large Hadron Collider (LHC)—a 27-kilometer (17-mile) proton-smashing circular tunnel at the heart of Europe’s physics lab CERN near Geneva—has most famously been used to prove the existence of the Higgs boson, dubbed “the God particle.”

In the tunnel, running about 100 meters (330 feet) below the French-Swiss border area, superconducting magnets and accelerating structures propel particles to extreme energies and then smash them together at phenomenal speeds.

Physicists Solve a “Quantum-Only” Problem Using an Ordinary Laptop

A problem once touted as requiring a quantum computer has now been solved on a laptop.

Using advanced mathematical techniques and sophisticated software, physicists at the Center for Computational Quantum Physics (CCQ) at the Simons Foundation’s Flatiron Institute and collaborators at Boston University showed that a conventional computer can successfully simulate a notoriously difficult quantum system previously claimed to be beyond the reach of classical computing.

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