The dynamics of strongly correlated quantum fields is at the heart of many pressing questions of modern theoretical physics. How does the Quark-Gluon-Plasma in a heavy-ion collision develop over time? How is energy and momentum exchanged among the microscopic constituents of ultracold quantum gases? Neither of these questions has been answered from first principles to date.
Machine learning has developed at an astonishing pace over the past decade. In DeepRTP we apply deep learning to the exploration of real-time dynamics of quantum fields in two ways. On the one hand we develop novel methods to extract real-time dynamics from conventional Euclidean time simulations. On the other hand we attempt to use machine learning to implement direct simulations in Minkowski time.
We welcome our newest project member Gaurang Parkar, who will work on his PhD as part of the DeepRTP project.
DeepRTP attended the Deep Learning and Physics (DLAP) workshop at the Yukawa Institute at the University of Kyoto.
Principal Investigator & Team Leader
Collaborator at Heidelberg University
Collaborator at UiS