The University of Tennessee, Knoxville, is launching the Knoxville Quantum Accelerator, also known as K-Quantum, to advance the region’s position as a leader in quantum technologies and systems. Unlike the digital computing systems we rely on today, quantum systems use elements of quantum mechanics — the complex behavior of atoms and subatomic particles — to process vast amounts of information quickly and in new ways. Leveraging those properties enables breakthroughs in applications ranging from drug discovery and advanced manufacturing to cryptography and optimization.

The team developed a new optical measurement technique, “Atom Camera,” using a single ultracold atom at near absolute zero temperature as a camera. The technique visualizes not only light intensity distributions but also polarization distributions with a high spatial resolution below 100 nanometers. The method is expected to be useful in quantum computing and other emerging quantum technologies.

Researchers at Bielefeld University are investigating how fans of different national teams physically respond to match events during the 2026 FIFA World Cup. A previous study of the 2025 DFB Cup final demonstrated for the first time a direct link between match action and vital functions such as heart rate and stress levels in supporters. The project is conducted in cooperation with Bielefeld’s Wissenswerkstadt [Knowledge Hub].

Researchers at the Faculty of Information Technology at the University of Jyväskylä have used artificial intelligence to speed up the analysis of colorectal cancer samples and predict the functioning of the cells’ DNA repair mechanism. The AI model's analysis can help shorten diagnosis times, reduce costs, and improve the analysis's accuracy. The research was conducted in collaboration with the Central Finland Welfare Region and is co-funded by the European Union.

As a growing share of total power output comes from wind turbines, sudden spikes in power generation from unpredictable changes in atmospheric conditions is becoming an increasingly urgent and potentially dangerous threat to grid stability. Using a 20 km-wide wind farm as a giant physics experiment, researchers have now developed a framework to predict the risk of power fluctuations for individual turbines, farms, and the whole grid, based on existing geospatial data. Their model will help establish the risk profile of existing and future developments, providing a powerful tool to ensure reliable and sustainable power generation for plant operators, grid engineers, and energy planners.