Machine Learning Topological Invariants with Neural Networks

30 Aug 2017Pengfei ZhangHuitao ShenHui Zhai

In this Letter we supervisedly train neural networks to distinguish different topological phases in the context of topological band insulators. After training with Hamiltonians of one-dimensional insulators with chiral symmetry, the neural network can predict their topological winding numbers with nearly 100% accuracy, even for Hamiltonians with larger winding numbers that are not included in the training data... (read more)

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