The project is focused on developing novel techniques using quantum tensor networks for simulating, describing and classifying strongly correlated quantum many body systems. Tensor networks provide a novel language for tackling the ubiquitous quantum many body problem, and this project aims at exploring the full range of possibilities that this new "language" provides. In particular, the project consists of three subprojects:
1. the study of the manifold of tensor networks and its associated optimization algorithms
2. the study of post-tensor network methods, with the aim of describing dynamical properties
3. the study of gauge theories and the classification of strongly correlated states of matter
During the project, we have achieved all envisioned objectives, but we also have been able to formulate and solve completely new problems, mainly related to the characterization of quantum topological phases of matter and to the construction of powerful numerical algorithms for contracting quantum tensor networks.