SymClosestWannier
CMT-MU / SymClosestWannier
Categories are inferred from the README
Overview
A Python library for Symmetry-Adapted Closest Wannier (SymCW) Tight-Binding model based on Plane-Wave DFT calculation.
README
SymClosestWannier
Overview: A Python library to create Symmetry-adapted Closest Wannier (SymCW) tight-binding models [1] based on the Symmetry-Adapted Multipole Basis (SAMB) [2] and the Closest Wannier formalism developed by Taisuke Ozaki [3].
[1] Rikuto Oiwa, Akane Inda, Satoru Hayami, Takuya Nomoto, Ryotaro Arita, and Hiroaki Kusunose, Symmetry-adapted closest Wannier modeling based on complete multipole basis set, Phys. Rev. B 112, 035116 (2025). DOI: https://doi.org/10.1103/2s5q-p42x
[2] Hiroaki Kusunose, Rikuto Oiwa, and Satoru Hayami, Symmetry-adapted modeling for molecules and crystals, Phys. Rev. B 107, 195118 (2023). DOI: https://doi.org/10.1103/PhysRevB.107.195118.
[3] Taisuke Ozaki, Closest Wannier functions to a given set of localized orbitals, Phys. Rev. B 110, 125115, (2024). DOI: https://doi.org/10.1103/PhysRevB.110.125115.
Authors: Rikuto Oiwa
Installation: SymClosestWannier can be installed from PyPI using pip on Python >= 3.9:
pip install symclosestwannierCiting SymClosestWannier: If you are using SymClosestWannier in your scientific research, please help our scientific visibility by citing our work:
[1] Rikuto Oiwa, Akane Inda, Satoru Hayami, Takuya Nomoto, Ryotaro Arita, and Hiroaki Kusunose, Symmetry-adapted closest Wannier modeling based on complete multipole basis set, Phys. Rev. B 112, 035116 (2025). DOI: https://doi.org/10.1103/2s5q-p42x
[2] Hiroaki Kusunose, Rikuto Oiwa, and Satoru Hayami, Symmetry-adapted modeling for molecules and crystals, Phys. Rev. B 107, 195118 (2023). DOI: https://doi.org/10.1103/PhysRevB.107.195118.
[3] Taisuke Ozaki, Closest Wannier functions to a given set of localized orbitals, Phys. Rev. B 110, 125115, (2024). DOI: https://doi.org/10.1103/PhysRevB.110.125115.
Requirements:
See also:
Source: https://github.com/CMT-MU/SymClosestWannier README
Richness
Richness = how many of docs / examples / tests are in place, shown as 0–3 stars (1 star = 1 item; the checklist below is the breakdown). Software listed by hand (without repository data) is not assessed and is left out when filtering by a richness of 1 or more.
- Yes: README
- Yes: LICENSE
- Yes: docs
- Yes: examples
- No: tests
- No: CITATION
- Yes: release
Information
- Primary language
- Python
- Languages
- Python, Redcode, Gnuplot, TeX, Shell
- License
- GPL-2.0
- Provider
- github