These datasets were used to produce all figures in the linked arXiv paper.
We use the most popular data storage format hdf5 due to possibility of including metadata (unlike numpy), processing the data without loading the entire dataset into memory with a single command, and other features that make the workings with data easier.
Unless noted otherwise, datasets contain time evolutions for XXZ model (<Z_i(t)Z_i(0)> and <Z_i(t) Z_j(t)>) with open boundary conditions. All arrays have time as the first column.
Example readout of a dataset is presented in the notebook example_dataset_readout.ipynb. It requires installation of some hdf5 processing library. In the example we use python and tables. For a quick glimpse what the datasets contain, on linux use vitables to explore the files and arrays therein.
Groups within the hdf5 files are named according to the convention [marker][L_A]_[L_B]_[W_A]_[W_B] with 'd' - the decimal separator. For example, group named 'U12_10_6_0d5' contains Uniform random disorder realizations for different random seeds for L_A=12, L_B=10, W_A=6, W_B=0.5.
Alphabetically ordered lists with all names of the data groups contained within hdf5 files with the numbers of random realizations are in the corresponding List_[HDF5_name].txt files for convenience.
If you use the repository, please cite the paper:
@misc{szoldra2024catching,
title={Catching thermal avalanches in disordered XXZ model},
author={Tomasz Szołdra, Piotr Sierant, Maciej Lewenstein, Jakub Zakrzewski},
year={2024},
eprint={2302.01362},
archivePrefix={arXiv},
primaryClass={cond-mat.dis-nn}
}
[Parent Directory]
