Tree tensor network state study of the ionic-neutral curve crossing of LiF

TL;DR

This paper introduces a tree tensor network state (TTNS) approach to study the ionic-neutral curve crossing in LiF, offering a potentially more efficient alternative to DMRG by exploiting entanglement properties.

Contribution

The study applies TTNS to quantum chemistry, demonstrating reduced computational cost and analyzing entanglement for optimizing tensor network topology.

Findings

TTNS captures long-range correlations with polynomial cost

Optimization of tensor topology improves accuracy

Localization of avoided crossing enhances understanding of electronic states

Abstract

We present a tree-tensor-network-state (TTNS) method study of the ionic-neutral curve crossing of LiF. For this ansatz, the long-range correlation deviates from the mean-field value polynomially with distance, thus for quantum chemical applications the computational cost could be significantly smaller than that of previous attempts using the density matrix renormalization group (DMRG) method. Optimization of the tensor network topology and localization of the avoided crossing are discussed in terms of entanglement.