Finding hidden order in spin models with persistent homology
Code used in the article "Finding hidden order in spin models with persistent homology"
Run the code in order: run1.jl, run2.py and run3.py.
arXiv: [2009.05141] Finding hidden order in spin models with persistent homology
The Julia code of run1.jl contains the Monte Carlo simulation of the XXZ model on a pyrochlore lattice. Spin configurations are sampled and stored in HDF5 format.
Next, the Python code run2.py used GUDHI to calculate barcodes for the spin configurations in the HDF5 file. Barcodes are stored as a pickle .p file.
Finally, the Python code run3.py calculates the pairwise sliced Wasserstein distance for the barcodes loaded from the pickle file. The final distance matrix D is stored as a numpy matrix file.