Disorder induced phase transition in magnetic higher-order topological insulator: A machine learning study
Abstract
Previous studies presented the phase diagram induced by the disorder existing separately either in the higher-order topological states or in the topological trivial states, respectively. However, the influence of disorder on the system with the coexistence of the higher-order topological states and other traditional topological states has not been investigated. In this paper, we investigate the disorder induced phase transition in the magnetic higher-order topological insulator. By using the convolutional neural network and non-commutative geometry methods, two independent phase diagrams are calculated. With the comparison between these two diagrams, a topological transition from the normal insulator to the Chern insulator is confirmed. Furthermore, the network based on eigenstate wavefunction studies also presents a transition between the higher-order topological insulator and the Chern insulator.
- Publication:
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Chinese Physics B
- Pub Date:
- October 2019
- DOI:
- 10.1088/1674-1056/ab4582
- Bibcode:
- 2019ChPhB..28k7301S
- Keywords:
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- disorder effects;
- convolution neural network;
- higher-order topological states