2 papers
physics.flu-dyn2025
Quantum machine learning for efficient reduced order modelling of turbulent flows
Han Li, Yutong Lou, Dunhui Xiao
Accurately predicting turbulent flows remains a central challenge in fluid dynamics due to their high dimensionality and intrinsic nonlinearity. Recent developments in quantum algo…
cs.LG2025
Machine learning for modelling unstructured grid data in computational physics: a review
Sibo Cheng, Marc Bocquet, Weiping Ding +20
Unstructured grid data are essential for modelling complex geometries and dynamics in computational physics. Yet, their inherent irregularity presents significant challenges for co…