Neural networks are one typical structure on which artificial intelligence can be based. The term ›neural‹ describes their learning ability, which to some extent mimics the functioning of neurons in our brains. To be able to work, several key ingredients are required: one of them is an activation function which introduces nonlinearity into the structure. A photonic activation function has important advantages for the implementation of optical neural networks based on light propagation. Researchers in the Stiller Research Group at the Max Planck Institute for the Science of Light (MPL) and Leibniz University Hannover (LUH) in collaboration with Dirk Englund at MIT have now experimentally shown an all-optically controlled activation function based on traveling sound waves. It is suitable for a wide range of optical neural network approaches and allows operation in the so-called synthetic frequency dimension.

A team of Rice University researchers reported the first direct observation of a surprising quantum phenomenon predicted over half a century ago, opening pathways for revolutionary applications in quantum computing, communication and sensing.

Physicists at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory and Stony Brook University (SBU) have shown that particles produced in collimated sprays called jets retain information about their origins in subatomic particle smashups. The study was recently published as an Editor’s Suggestion in the journal Physical Review Letters.

Nuclear spins in a crystal can be detected and manipulated through their interactions with the more accessible electron spin of a neighboring crystal defect. This strategy has enabled nanoscale magnetic resonance imaging and other quantum applications. But a long-standing challenge has been to target a specific nuclear spin, while protecting the delicate quantum nature of the electron spin. Important progress on this challenge has now been achieved by two teams at the Delft University of Technology in the Netherlands.

A research team led by scientists at Lawrence Berkeley National Laboratory (Berkeley Lab) has developed a new fabrication technique that could improve noise robustness in superconducting qubits, a key technology to enabling large-scale quantum computers.

ACS Nano features the physics professor’s latest breakthrough, developing an advanced, scalable method for creating, brightening and directing light on a chip for quantum cryptography and photon-encrypted telecommunications of the future.

Using artificial intelligence, scientists can now identify complex quantum phases in materials in just minutes—a process that used to take months. The breakthrough, published in Newton, could significantly speed up research into quantum materials, particularly low dimensional superconductors. The study, a collaboration between Yale and Emory University, was seeded by a multi-institute collaboration initiative three years ago. Yale’s side of the research, led by Jinming Yang, a graduate research assistant, and Yu He, assistant professor of Yale’s Department of applied physics, was initiated under a Yale Materials Research Science and Engineering Centers (MRSEC) internal preparatory project awarded in 2022. Other senior authors include Fang Liu and Yao Wang, assistant professors in Emory’s Department of Chemistry.

A new study published in Nature Communications April 7 could reshape the future of magnetic and electronic technology. Scientists at Rice University have discovered how a disappearing electronic pattern in a quantum material can be revived under specific thermal conditions. The finding opens new doors for customizable quantum materials and in-situ engineering, where devices are manufactured or manipulated directly at their point of use.

In the new study, the team formulated a quantum algorithm (a set of computer instructions) that can be used in theory to find low-energy states—what physicists call local minima—of any material. Their study theoretically proves that the algorithm will perform much better than its classical counterparts.

The research team led by Professor Chang-Hee Cho from the Department of Physics and Chemistry at DGIST (President Kunwoo Lee) has successfully fine-tuned the Rabi oscillation of polaritons, quantum composite particles, by leveraging changes in electrical properties induced by crystal structure transformation. This study demonstrates that the properties of quantum particles can be controlled without the need for complex external devices, which is expected to greatly enhance the feasibility of practical quantum technology.