Quantum Dimensional Transition in Spin-$\frac{1}{2}$ Antiferromagnetic Heisenberg Model on A Square Lattice and Space Reduction in Matrix Product State

TL;DR

This paper investigates a quantum phase transition in a spin-$rac{1}{2}$ antiferromagnetic Heisenberg model on a square lattice, revealing a critical width where symmetry breaks and demonstrating an efficient matrix product state approach for large systems.

Contribution

It identifies a critical lattice width for symmetry breaking and introduces a space-reducing MPS method that efficiently handles large quasi-1D quantum systems.

Findings

Critical width $N_c=10$ for symmetry breaking.

Faster convergence of ground state energy with respect to $N$.

Efficient MPS algorithm with space reduction for large $N$.

Abstract

We study the spin-$\frac{1}{2}$ antiferromagnetic Heisenberg model on an infinity-by-$N$ square lattice for even $N$'s up to $14$. Previously, the nonlinear sigma model perturbatively predicts that its spin rotational symmetry asymptotically breaks when $N\rightarrow \infty$, i.e., when it is two-dimensional (2D). However, we identified a critical width $N_c = 10$ for which this symmetry breaks spontaneously. It defines a dimensional transition from one-dimension (1D) including quasi-1D to 2D. The finite-size effect differs from that of the $N$-by-$N$ lattice. The ground state (GS) energy per site approaches the thermodynamic limit value, in agreement with the previously accepted value, by one order of $1/N$ faster than when using $N$-by-$N$ lattices in the literature. We build and variationally solve a matrix product state (MPS) on a chain, converting the $N$ sites in the rung into an effective site. We show that the area law of entanglement entropy does not apply when $N$ increases in our method, and show that the reduced density matrix of each effective site will have a saturating number of dominant diagonal elements with increasing $N$. These two characteristics make the MPS rank needed to obtain a demanded energy accuracy quickly saturate when $N$ is large, making our algorithm efficient for large $N$'s. And, the latter enables space reduction in MPS. Within the framework of MPS, we prove a theorem that the spin-spin correlation at infinite separation is the square of staggered magnetization and demonstrate that the eigenvalue structure of a building MPS unit of $\langle g\mid g\rangle$, $\mid g\rangle$ being the GS, is responsible for order, disorder and quasi-long-range order.