Computing excited eigenstates using inexact Lanczos methods and tree tensor network states

Abstract: Excited eigenstates are crucial to understand the dynamics of quantum many-body systems. Tensor network states are one of the workhorses to compute ground states of many-body systems, yet the accurate computation of excited eigenstates is still challenging. Here, we develop a combination of the inexact Lanczos method, which aims at efficiently computing excited states, to tree tensor network states (TTNSs). We demonstrate our approach by computing excited vibrational states for three challenging problems: (1) 84 states in different energy intervals of acetonitrile (12-dimensional), (2) Fermi resonance states of the fluxional Zundel ion (15-dimensional), and (3) selected excited states of the fluxional and very correlated Eigen ion (33-dimensional). The proposed TTNS inexact Lanczos method is directly applicable to other quantum many-body systems.