Researchers have fully mapped how noise spreads through quantum computers over time to show that glitches link together across different moments, creating a form of 'memory' that undermines calculations.

For the first time worldwide, we have achieved remote, real-time control of fusion plasma using a digital twin running on a supercomputer located about 1,000 km away (round-trip network path ~2,000 km).

In magnetic confinement fusion power, sustaining and precisely controlling plasma at temperatures exceeding 100 million ℃ over long durations is essential. Yet “predicting-while-controlling” has been challenging due to model accuracy limits, computation speed, and unresolved physics. Our team has developed a system that applies data assimilation, continuously updating the predictive model with real-time measurements to improve accuracy and using accelerated parallel prediction to determine optimal unrehearsed control actions.

A research team from Kyoto University, the National Institute for Fusion Science (NIFS), the National Institutes for Quantum Science and Technology (QST), and the Institute of Statistical Mathematics (ISM), has connected the Large Helical Device (LHD) in Toki, Gifu, Japan to the new “Plasma Simulator” supercomputer in Rokkasho, Aomori, jointly procured by NIFS and QST, via the high-quality, high-bandwidth academic network SINET6. By exclusively using more than 20,000 Central Processing Unit (CPU) cores and minimizing communication latency, the team has realized real-time predictive control of LHD from a remote supercomputer. This approach — linking a large experimental facility and a large computing system over a ~2,000 km network loop — can serve as a foundation for real-time control beyond fusion.

Researchers at McMaster University have developed a new database that brings together more than 100 years of historical epidemiological data from across Canada, which will help to predict future patterns of infectious disease.