Year: 2020
Type: article
Abstract: The authors tackle the issue of interpretability in machine learning topological quantum phases in models of Chern insulator, ${\mathbb{Z}}_{2}$ topological insulator, and ${\mathbb{Z}}_{2}$ quantum spin liquid. The authors use artificial neural network aided by physical insight underlying the feature selection through quantum loop topography to understand the artificial neural network's decision-making criteria in each of the three cases
Source: Physical Review Research
Authors: Yi Zhang, Paul Ginsparg, Eun-Ah Kim
Institutions: Peking University, Cornell University
Language: English
Subfield: Atomic and Molecular Physics, and Optics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,625
OpenAlex ID: W2996496795