Lattice-reflection symmetry in tensor-network renormalization group with entanglement filtering in two and three dimensions

TL;DR

This paper introduces a method to incorporate lattice-reflection symmetry into tensor-network renormalization group algorithms in 2D and 3D, enhancing the analysis of critical systems.

Contribution

It proposes a general framework and algorithms for embedding lattice-reflection symmetry into TNRG with entanglement filtering, including a transposition trick for key operations.

Findings

The method preserves lattice-reflection symmetry in TNRG maps.

Algorithms for TNRG in 2D and 3D with reflection symmetry are detailed.

Construction of linearized TNRG maps enables extraction of sector-specific scaling dimensions.

Abstract

Tensor-network renormalization group (TNRG) is an efficient real-space renormalization group method for studying the criticality in both classical and quantum lattice systems. Exploiting symmetries of a system in a TNRG algorithm can simplify the implementation of the algorithm and can help produce correct tensor RG flows. Although a general framework for considering a global on-site symmetry has been established, it is still unclear how to incorporate a lattice symmetry in TNRG. As a first step for lattice symmetries, we propose a method to incorporate the lattice-reflection symmetry in the context of a TNRG with entanglement filtering in both two and three dimensions (2D and 3D). To achieve this, we write down a general definition of lattice-reflection symmetry in tensor-network language. Then, we introduce a transposition trick for exploiting and imposing the lattice-reflection symmetry in two basic TNRG operations: projective truncations and entanglement filtering. Using the transposition trick, the detailed algorithms of the TNRG map in both 2D and 3D are laid out, where the lattice-reflection symmetry is preserved and imposed. Finally, we demonstrate how to construct the linearization of the TNRG maps in a given lattice-reflection sector, with the help of which it becomes possible to extract scaling dimensions in each sector separately. Our work paves the way for understanding the lattice-rotation symmetry in TNRG.