Studying Quantum Many-Body Systems with Artificial Neural Networks, June 15 - June 19

This course is part of the 2026 Undergraduate Summer School curriculum. This course introduces modern artificial neural network architectures and explores how they can be used to study quantum many-body systems as key models underlying quantum computation and condensed matter physics. Students will learn the basics of quantum many-body theory and artificial neural networks and see how these tools can be combined to represent quantum states, analyze data, and optimize quantum experiments. The course provides both conceptual foundations and practical insight into how artificial intelligence is transforming the study of complex quantum systems.