Machine Learning Topological Phases with a Solid-State Quantum Simulator
Machine Learning Topological Phases with a Solid-State Quantum Simulator
We report an experimental demonstration of a machine learning approach to identify exotic topological phases, with a focus on the three-dimensional chiral topological insulators. We show that the convolutional neural networks---a class of deep feed-forward artificial neural networks with widespread applications in machine learning---can be trained to successfully identify different …