Unsupervised learning eigenstate phases of matter
Unsupervised learning eigenstate phases of matter
Supervised learning has been successfully used to produce phase diagrams and identify phase boundaries when local order parameters are unavailable. Here, we apply unsupervised learning to this task. By using readily available clustering algorithms, we are able to extract the distinct eigenstate phases of matter within the transverse-field Ising model …