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ZENODO
Software . 2026
License: http://www.gnu.org/licenses/gpl-3.0-standalone.html
Data sources: ZENODO
ZENODO
Software . 2026
License: https://www.gnu.org/licenses/gpl-3.0-standalone.html
Data sources: Datacite
ZENODO
Software . 2026
License: https://www.gnu.org/licenses/gpl-3.0-standalone.html
Data sources: Datacite
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Pyth-MPG

Python code to analyze magnetic point group properties
integration_instructionsResearch softwarekeyboard_double_arrow_right Software 16 Jun 2026 English Publisher:Zenodo
Authors: Urru, Andrea; Birol, Turan; Cole, Trey; Vanderbilt, David;

doi: 10.5281/zenodo.20720849 , 10.5281/zenodo.18672613

Abstract

This project provides a suite of Python codes capable of screening all of the 122 magnetic point groups (MPGs) according to the types of tensorial properties that are supported under the symmetries of each group. In particular, the codes can be used to generate data that can be used to build Excel spreadsheets capable of similar screening operations. A selection of spreadsheets constructed in this way is provided as part of the distribution.

This Zenodo record contains two files for download: Pyth-MPG-Spreadsheets-1.0.0.zip This archive contains several pre-constructed spreadsheets. It also includes the PDF User Guide, describing both the spreadsheets themselves and the python codes that generate them. Pyth-MPG-git-1.0.0.zip An archive of the GitHub repository containing the Python codes.

Related Organizations
Keywords

Crystallography, Magnetic Phenomena, Condensed matter physics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average