Many early-career scientists continue their academic careers at the same university where they studied, a practice known as academic inbreeding. A researcher at the HSE Institute of Education analysed the impact of academic inbreeding on publication activity in the natural sciences and mathematics. The study found that the impact is ambiguous and depends on various factors, including the university's geographical location, its financial resources, and the state of the regional academic employment market. A paper with the study findings has been published in Research Policy. 

Researchers at Rice and collaborators at Oak Ridge National Laboratory and the University of Technology, Sydney report the first demonstration of low noise, room-temperature quantum emitters in h-BN made through a scalable growth technique.

An international team of scientists led by Rice University’s Pengcheng Dai has confirmed the existence of emergent photons and fractionalized spin excitations in a rare quantum spin liquid. Published in Nature Physics on June 19, their findings identify the crystalline compound cerium zirconium oxide (Ce₂Zr₂O₇) as a clear, 3D realization of this exotic state of matter.

BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs through graph partitioning, has been developed by researchers at Institute of Science Tokyo, Japan. This breakthrough framework utilizes an innovative cross-partition message quantization technique and a novel training algorithm to significantly reduce memory demands and increase computational and energy efficiency. 

Researchers from The University of Osaka have developed a way to efficiently prepare the “magic states” necessary for quantum computers to be resistant to errors. Their technique, called “zero-level distillation,” involves working with qubits at the physical or zeroth level as opposed to higher, more abstract levels. The spatial and temporal overhead of quantum computers prepared from these states using this technique is around several dozen times lower than that of those prepared from conventional methods.

NIMS and its collaborators (IHI Corporation, Kawasaki Heavy Industries, Ltd., Kansai Electric Power Co., Inc., Kobe Steel, Ltd., Electric Power Development Co., Ltd., the Japan Atomic Energy Agency, Mitsubishi Heavy Industries, Ltd. and Elix, Inc.) have developed a model designed to predict the long-term durability of a range of heat-resistant steel materials by performing machine learning while preserving the confidentiality of each organization’s data. This research was published online in Tetsu-to-Hagané on February 6, 2025.

UBC researchers are proposing a solution to a key hurdle in quantum networking: a device that can “translate” microwave to optical signals and vice versa. The technology could serve as a universal translator for quantum computers—enabling them to talk to each other over long distances and converting up to 95 per cent of a signal with virtually no noise. And it all fits on a silicon chip, the same material found in everyday computers.