Article:Maida Wang, Xiao Xue, Mingyang Gao, Peter V. Coveney
Quantum-informed machine learning for predicting spatiotemporal chaos
Researchers from University College London and the University of Amsterdam have introduced QIML, a hybrid framework combining quantum generative models with classical autoregressive predictors. The method stabilises long-term forecasting of high-dimensional chaotic systems, offering practical advantages over purely classical baselines.