Compression of Wannier functions into Gaussian-type orbitals

TL;DR

This paper introduces a greedy algorithm to compress Wannier functions into Gaussian orbitals, enabling compact storage and efficient Hamiltonian parameterization for layered 2D materials while preserving symmetry.

Contribution

A novel greedy compression method for Wannier functions into Gaussian orbitals that maintains symmetry and improves efficiency in material simulations.

Findings

Effective compression demonstrated on graphene and h-BN

Preserves symmetry of original Wannier functions

Enables efficient tight-binding Hamiltonian parameterization

Abstract

We propose a greedy algorithm for the compression of Wannier functions into Gaussian-polynomials orbitals. The so-obtained compressed Wannier functions can be stored in a very compact form, and can be used to efficiently parameterize effective tight-binding Hamiltonians for multilayer 2D materials for instance. The compression method preserves the symmetries (if any) of the original Wannier function. We provide algorithmic details, and illustrate the performance of our implementation on several examples, including graphene, hexagonal boron-nitride, single-layer FeSe, and bulk silicon in the diamond cubic structure.