Unsupervised Identification of Topological Domain Defect Nodes of YbMnO3 Based on Radar Density Algorithm

Abstract

When the ferroelectric hexagonal manganese oxide single crystal is near the Curie temperature and generates the phase transformation, the topological defects of the vortex and anti-vortex structure will be generated. Applying the Radar Density Algorithm, the representative fragment of the vortex and anti-vortex structure is analyzed. By the Radar Density Algorithm analysis, the feature of the vortex and anti-vortex structure can be translated and identified as a mathematic model and judged by the mathematic program. This provides a new algorithm and approach for intelligent identification of vortex structure nodes and the phase transition.