Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

De Gruyter eBooks

Renormalization Group Transformations as Symmetry Mappings

J. Lukieeski

Published Dec 31, 1977• 0 citations
Publisher
DOI
10.1515/9783112519585-002

Related papers

Renormalization Group Transformations as Symmetry Mappings

Jerzy Lukierski B

Fortschritte der Physik•Jan 1, 1977•0 citations

Symmetry breaking in the two-parameter Kadanoff renormalization-group transformation

Chin‐Kun Hu

Physics Letters A•May 1, 1985•0 citations

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

Xinliang Lyu, Naoki Kawashima

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.

arXiv:2510.19428•Physical review. B./Physical review. B•Mar 6, 2026•2 citations

Mathematical properties of renormalization-group transformations

Robert B. Griffiths

Physica A Statistical Mechanics and its Applications•Mar 1, 1981•40 citations

Properties of renormalization group transformations

Peter Kunszt

arXiv:hep-lat/9706019•Nuclear Physics B•Apr 1, 1998•4 citations

Some symmetry properties of renormalization-group transformations

Marko V. Jarić

For a Landau-Ginzburg-Wilson Hamiltonian of any given symmetry we show how one can find a group ${G}_{T}$ of orthogonal transformations in parameter space, which commute with renormalization-group transformations. Then a renormalization-group transformation may be expanded into covariants of ${G}_{T}$. We also present a systematic procedure for finding fixed points; they are most likely to decouple the Hamiltonian or to increase its symmetry. The merit of the conclusions obtained is illustrated using an example of a system with ${C}_{4}$ symmetry. Agreement with the results of $\ensuremath{\epsilon}$-expansion calculations has been found.

Physical review. B, Condensed matter•Sep 1, 1978•14 citations
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.
For a Landau-Ginzburg-Wilson Hamiltonian of any given symmetry we show how one can find a group GT{G}_{T}GT​ of orthogonal transformations in parameter space, which commute with renormalization-group transformations. Then a renormalization-group transformation may be expanded into covariants of GT{G}_{T}GT​. We also present a systematic procedure for finding fixed points; they are most likely to decouple the Hamiltonian or to increase its symmetry. The merit of the conclusions obtained is illustrated using an example of a system with C4{C}_{4}C4​ symmetry. Agreement with the results of $\ensuremath{\epsilon}$-expansion calculations has been found.