4 papers
Quantum Neural Physics: Solving Partial Differential Equations on Quantum Simulators using Quantum Convolutional Neural Networks
Jucai Zhai, Muhammad Abdullah, Boyang Chen +6
Neural Physics recasts local discretisations of partial differential equations (PDEs) as fixed convolutional operators, providing a physics-preserving alternative to data-driven su…
NeuralFVM: Neural-physics-based Finite Volume Method for Turbulent Flows Using the - Model
Tingkai Xue, Yu Jiao, Te Ba +9
In this work, we develop a neural-physics solver based on finite volume method (FVM), namely NeuralFVM, for turbulent flows by implementing the standard - model designed for…
An AI-driven framework for the prediction of personalised health response to air pollution
Nazanin Zounemat-Kermani, Sadjad Naderi, Claire H. Dilliway +10
Air pollution is a growing global health threat, exacerbated by climate change and linked to cardiovascular and respiratory diseases. While personal sensing devices enable real-tim…
Neural Physics: Using AI Libraries to Develop Physics-Based Solvers for Incompressible Computational Fluid Dynamics
Boyang Chen, Claire E. Heaney, Christopher C. Pain
Numerical discretisations of partial differential equations (PDEs) can be written as discrete convolutions, which, themselves, are a key tool in AI libraries and used in convolutio…