This data repository contains the original figures, numerical (raw) data, and plot scripts to reproduce the figures from the publication "Non-Perturbative Feats in the Physics of Correlated Antiferromagnets" at Physical Review Research. LaTeX source files and the preprint is available on arXiv under the CC-BY license.

The CC-BY license applies to all the data, and pdf files. All distributed code is under the MIT license.

For the Python scripts and Jupyter notebooks, the following non-standard libraries have been used: correl 0.1.21 is installable via pip and available on TUgitlab

Further, an installed version of latex is needed for the plot scripts.

To obtain the source files of the DMFT calculations, the w2dynamics DMFT solver was employed.

Note that the divergence and "real-part zero-crossing" (RZ) lines have been manually extracted by interpolating (interpolate.py) from the respective zero-crossings of the generalized susceptibility eigenvalues (show.ipynb). For the mean-field generalized susceptibility eigenvalues, the RZ lines have been obtained from an approximated BSE equation with an logarithmic error near the Neel temperature, which is how ever negligible at the RZ line (correl.hubbard.meanfield.chi_smpl_loc()).

The folder structure of the repository is the following:

project
│   README.md
│   Fig2.pdf                  figure of the publication
|   Fig3.pdf                  figure of the publication
|   Fig4.pdf                  figure of the publication
|   Fig5.pdf                  figure of the publication
|   Fig6.pdf                  figure of the publication
|   Fig7.pdf                  figure of the publication
|   Fig8.pdf                  figure of the publication
|   Fig10.pdf                 figure of the publication
|
|   Fig2_matrix.ipynb         jupyter notebook for Fig2
|   Fig3_div_lines.ipynb      jupyter notebook for Fig3
|   Fig4_local_resp.ipynb     jupyter notebook for Fig4
|   Fig5_eigenvals.py         python script for Fig5 (saved from plot window)
|   Fig6_temperature_eig.py   python script for Fig6 (saved from plot window)
│   Fig7_bubble_diff.ipynb    jupyter notebook for Fig7
|   Fig8_projection.ipynb     jupyter notebook for Fig8
|   Fig10_local_spin.ipynb    jupyter notebook for Fig10
|
|   show.ipynb                jupyter notebook to extract the eigenvalues of the generalized susceptibilities
|   interpolate.py            python script to find the zero-crossing of the eigenvalues
|
└───DMFT                      DMFT data
|   |
|   |   af_div[nr].dat        extracted [nr]. divergence line in the AF phase
|   |   af_dash[nr].dat       extracted [nr]. RZ line in the AF phase
|   |   pm_div[nr].dat        [nr]. divergence line of Ref. Schäfer et al. PRB 94, 235108 (2016)
|   |   Tneel.npy             T_Neel of Ref. Kuneš PRB 83, 085102 (2011)
|   |   Uc.dat                MIT U_crit data of Ref. Blümer Ph.D. thesis (2002) via Pelz et al. PRB 108,155101(2023)
|   |
|   └───2p                    DMFT raw data from w2dynamics calculations in two-atomic basis, 
|   |   |                     on a 2D square lattice, with t=1/4 and mu=U/2 for inverse temperature
|   |   |                     [beta] = 1/T, and Hubbard interaction [U]
|   |   |
│   |   └───U[U]
|   |       |   b[beta].hdf5        two-particle w2dynamics data file
|   |       |   b[beta]_g.hdf5      one-particle w2dynamics data file
|   |       |   b[beta]_susz.hdf5   physical susceptibility w2dynamics data file
|   |
|   └───2p_pm                 DMFT raw data from w2dynamics calculations in two-atomic basis,
|       |                     on a 2D square lattice, with t=1/4 and mu=U/2 for inverse temperature
|       |                     [beta] = 1/T, Hubbard interaction [U], and with forced PM solution
|       |
│       └───U[U]
|           |   b[beta].hdf5        two-particle w2dynamics data file
|           |   b[beta]_g.hdf5      one-particle w2dynamics data file
|           |   b[beta]_susz.hdf5   physical susceptibility w2dynamics data file
|
└───LocResp                   auxiliary numpy files for the jupyter notebook Fig4_local_resp.ipynb and Fig10_local_spin.ipynb
|   | ...
│   
└───MF                        mean-field data
    |                 
    |    MF_scan.py           python script to to calculate the physical and generalized local susceptibilities
    |    MF_pm_scan.py        python script to to calculate the physical local susceptibility in the PM phase
    |    mf_dash[nr].dat      extracted [nr]. RZ line
    |    mag_U.npy            calculated mean-field magnetization
    |
    └───afX                   calculated mean-field susceptibility files
    |   | ...
    |   
    └───pmX                   calculated mean-field susceptibility files in the PM phase
        | ...