The path toward realizing practical quantum technologies begins with understanding the fundamental physics that govern quantum behavior — and how those phenomena can be harnessed in real materials. In the lab of Ania Jayich, Bruker Endowed Chair in Science and Engineering, Elings Chair in Quantum Science, and co-director of UC Santa Barbara’s National Science Foundation Quantum Foundry, that material of choice is laboratory-grown diamond.

A new PLOS ONE study from Lehigh University introduces a computational model that predicts how electrical stimulation affects atrial fibrillation. The framework could help optimize therapy strategies and move clinicians closer to personalized cardiac care.

Scientists at TU Delft, The Netherlands, have developed a new algorithm that allows multiple autonomous drones to work together to control and transport heavy payloads, even in windy conditions. Ideal for reaching and maintaining hard-to-reach infrastructure, like offshore wind turbines. With often harsh weather, limited payload capacity and unpredictable contact with the environment, it is difficult for current drones to operate safely and effectively. The results have been published in Science Robotics.

A new interactive web application allows for a tangible understanding of abstract concepts of quantum game theory. The Kobe University development parallels the emergent dialogue found in jazz and improvisational music and aims for a scientific exploration of creativity.

A new quantum transport theory reveals how femtosecond time scale thermoelectric fluctuations influence energy control at the nanoscale. The University of Jyväskylä, Finland, has contributed to the development of a theoretical approach that enables accurate simulations of temperature differences and electric currents in nanoscale junctions formed by single molecules. The research opens new possibilities for designing components used in quantum technologies. 

This study presents a specialized Electronic Probe Computer (EPC60) designed to efficiently address NP-complete problems—computational challenges that become increasingly complex as their size grows. The EPC60 system, constructed with 60 fully customized FPGA-based probe computing cards, utilizes a hybrid serial-parallel computational model along with seven fully parallel probe operators. In tests conducted on large-scale 3-coloring problems, the EPC60 achieved 100% accuracy on 2000-vertex graphs in under one hour, significantly surpassing the state-of-the-art solver Gurobi, which attained only 6% accuracy. Given the theoretical mutual reducibility of NP-complete problems in polynomial time, the EPC60 emerges as a universal solver for this class of problems. Additionally, the system's modular design facilitates scalable expansion, presenting a promising hardware solution for addressing real-world optimization challenges in logistics, telecommunications, and manufacturing.