Researchers Develop HAMSTER, A Physics-informed Machine Learning Framework For Predicting Complex Chemical System Hamiltonians

Researchers Develop HAMSTER, A Physics-informed Machine Learning Framework For Predicting Complex Chemical System Hamiltonians

This research presents a new machine learning framework that accurately predicts the optoelectronic properties of complex materials by combining fundamental physics principles with limited, precise calculations, enabling scalable predictions for systems containing tens of thousands of atoms