Over the last decade, the Density Matrix Renormalization Group (DMRG) algorithm has been established as a reliable method for treating systems with strongly correlated electrons. Recently we have made efforts on pushing DMRG towards a wider range of applications, by integrating it with (i) conventional quantum chemistry methods, such as multireference configuration interaction and n-electron valence state perturbation theory, and (ii) novel ab initio quantum embedding methods, such as density matrix embedding theory and dynamical mean field theory. For this purpose, we have developed a modular and highly scalable ab initio DMRG code with the support of property calculations such as reduced density matrix, Green’s function, linear response, spin-orbit coupling, time evolution and finite temperature simulations. We illustrate how this new computational tool can help us understand the systematic properties of cuprate superconductors and the Kondo effect at the ab initio level.

High performance ab initio density matrix renormalization group as a versatile tool for understanding realistic systems

ACS Spring 2022

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.