Tensor network states for quantum spin ladders

TL;DR

This paper introduces an efficient tensor network algorithm for infinite-size quantum spin ladders, enabling accurate ground-state wave functions and phase transition detection, advancing the understanding of quantum many-body physics.

Contribution

The paper presents a novel tensor network method for spin ladders that accurately computes ground states and phase diagrams, outperforming previous techniques like DMRG.

Findings

Successfully captures quantum criticalities in spin ladders.

Produces reliable phase diagrams for two-leg and three-leg ladders.

Demonstrates the effectiveness of ground-state fidelity per lattice site as a phase transition marker.

Abstract

We have developed an efficient tensor network algorithm for spin ladders, which generates ground-state wave functions for infinite-size quantum spin ladders. The algorithm is able to efficiently compute the ground-state fidelity per lattice site, a universal phase transition marker, thus offering a powerful tool to unveil quantum many-body physics underlying spin ladders. To illustrate our scheme, we consider the two-leg and three-leg Heisenberg spin ladders with staggering dimerization. The ground-state phase diagram thus yielded is reliable, compared with the previous studies based on the density matrix renormalization group. Our results indicate that the ground-state fidelity per lattice site successfully captures quantum criticalities in spin ladders.