Pseudo-fermion functional renormalization group for spin models

TL;DR

This paper reviews the pseudo-fermion and pseudo-Majorana functional renormalization group methods, highlighting their ability to model higher-dimensional frustrated quantum magnets and making their algorithms accessible to researchers.

Contribution

It provides a comprehensive review and accessible implementation details of PFFRG and PMFRG for higher-dimensional frustrated quantum magnetism.

Findings

PFFRG interprets Heisenberg models using Abrikosov pseudofermions.

The methods are effective for modeling complex frustrated magnets.

The review lowers barriers to applying these advanced numerical techniques.

Abstract

For decades, frustrated quantum magnets have been a seed for scientific progress and innovation in condensed matter. As much as the numerical tools for low-dimensional quantum magnetism have thrived and improved in recent years due to breakthroughs inspired by quantum information and quantum computation, higher-dimensional quantum magnetism can be considered as the final frontier, where strong quantum entanglement, multiple ordering channels, and manifold ways of paramagnetism culminate. At the same time, efforts in crystal synthesis have induced a significant increase in the number of tangible frustrated magnets which are generically three-dimensional in nature, creating an urgent need for quantitative theoretical modeling. We review the pseudo-fermion (PF) and pseudo-Majorana (PM) functional renormalization group (FRG) and their specific ability to address higher-dimensional frustrated quantum magnetism. First developed more than a decade ago, the PFFRG interprets a Heisenberg model Hamiltonian in terms of Abrikosov pseudofermions, which is then treated in a diagrammatic resummation scheme formulated as a renormalization group flow of $m$-particle pseudofermion vertices. The article reviews the state of the art of PFFRG and PMFRG and discusses their application to exemplary domains of frustrated magnetism, but most importantly, it makes the algorithmic and implementation details of these methods accessible to everyone. By thus lowering the entry barrier to their application, we hope that this review will contribute towards establishing PFFRG and PMFRG as the numerical methods for addressing frustrated quantum magnetism in higher spatial dimensions.