Massively parallel tensor network methods for strongly correlated quantum chemistry

In this project we would like to develop a massively parallel implementation of the quantum chemical density matrix renormalization group method (QC-DMRG), which is a very powerful multireference method, however highly scalable implementations have not been developed yet. We would also like to develop a more flexible tree tensor network state (QC-TTNS) method, which will be able to properly describe the complex electronic structure of strongly correlated systems, taking into account the underlying entanglement more efficiently. We believe that the developed methods will open the way for computations of challenging problems in quantum chemistry where strong electron correlation plays an important role, such as bio-inorganic systems with multiple transition metal centers.