Deep learning topological invariants of band insulators
In this work we design and train deep neural networks to predict topological invariants for one-dimensional four-band insulators in AIII class whose topological invariant is the winding number, and two-dimensional two-band insulators in A class whose topological invariant is the Chern number. Given...
Main Authors: | Sun, Ning, Yi, Jinmin, Zhang, Pengfei, Zhai, Hui, Shen, Huitao |
---|---|
Other Authors: | Massachusetts Institute of Technology. Department of Physics |
Format: | Article |
Language: | English |
Published: |
American Physical Society
2018
|
Online Access: | http://hdl.handle.net/1721.1/117272 https://orcid.org/0000-0003-1667-8011 |
Similar Items
-
Machine Learning Topological Invariants with Neural Networks
by: Zhang, Pengfei, et al.
Published: (2018) -
Simplified Topological Invariants for Interacting Insulators
by: Zhong Wang, et al.
Published: (2012-08-01) -
Inverse design of multi-band acoustic topology insulator based on deep learning
by: Yao Qin, et al.
Published: (2023-05-01) -
Probing the topology in band insulators
by: Chen, Kuang-Ting, Ph. D. Massachusetts Institute of Technology
Published: (2013) -
Topological Invariants and Ground-State Wave functions of Topological Insulators on a Torus
by: Zhong Wang, et al.
Published: (2014-01-01)