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Algorithms for magnetic symmetry operation search and identification of magnetic space group from magnetic crystal structure.

Kohei ShinoharaAtsushi TogoIsao Tanaka
Published in: Acta crystallographica. Section A, Foundations and advances (2023)
A crystal symmetry search is crucial for computational crystallography and materials science. Although algorithms and implementations for the crystal symmetry search have been developed, their extension to magnetic space groups (MSGs) remains limited. In this paper, algorithms for determining magnetic symmetry operations of magnetic crystal structures, identifying magnetic space-group types of given MSGs, searching for transformations to a Belov-Neronova-Smirnova (BNS) setting, and symmetrizing the magnetic crystal structures using the MSGs are presented. The determination of magnetic symmetry operations is numerically stable and is implemented with minimal modifications from the existing crystal symmetry search. Magnetic space-group types and transformations to the BNS setting are identified by a two-step approach combining space-group-type identification and the use of affine normalizers. Point coordinates and magnetic moments of the magnetic crystal structures are symmetrized by projection operators for the MSGs. An implementation is distributed with a permissive free software license in spglib v2.0.2: https://github.com/spglib/spglib.
Keyphrases
  • molecularly imprinted
  • machine learning
  • solid phase extraction
  • primary care
  • healthcare
  • magnetic resonance imaging
  • crystal structure
  • magnetic resonance
  • mass spectrometry
  • neural network