These are the complete notebooks to reproduce the plots in "Unsupervised mapping of phase diagrams of 2D systems from infinite projected entangled-pair states via deep anomaly detection" by Korbinian Kottmann, Philippe Corboz, Maciej Lewenstein and Antonio Acín (arxiv link tba).
The notebooks are nummerically ordered to reproduce Figs. 1-3.
The data from the simulated PEPS (bond singular values and reduced density matrices) are in data
Intermediate results are saved for convenience in data_results.
AD_tools.py contains some functions that are used for the anomaly detection in all notebooks.
plots contains the resulting figures as well as additional images like training convergences.
CNN_data contains the parameters of the neural networks involved. Training is very fast here, so there is not really a need for it.