Project title: Learning ground-state properties of quantum materials using neural network states
PI: Vlatko Vedral
The interesting behaviours exhibited by new quantum materials are difficult to simulate accurately using conventional methods because of their complex interactions. Neural network representation of quantum states is promising in solving quantum problems. This project will apply quantum-inspired neural networks and quantum machine learning to efficiently capture the complex correlations in materials, which will then be applied to find the most stable configuration of quantum materials.
