Neural Representations of Correlated Quantum Matter in and Out of Equilibrium
Jannes Nys, ETHZ
Leuchs-Russell-Auditorium, A.1.500, Staudtstr. 2
Abstract:
Understanding how quantum many-body systems interact and give rise to emergent collective phenomena is essential in various fields of science and technology development, including designing new quantum materials with targeted properties, advancing analog quantum simulations, and designing quantum computational devices. However, when strong correlations play a significant role, the existing computational and theoretical tools inevitably face challenges. In this talk, I will introduce a new class of machine-learning-inspired computational methods to advance our understanding of both equilibrium and non-equilibrium properties of strongly correlated matter, with a focus on fermionic systems.
