pyTDGL

Time-dependent Ginzburg-Landau in Python

Motivation

pyTDGL solves a 2D generalized time-dependent Ginzburg-Landau (TDGL) equation, enabling simulations of vortex and phase dynamics in thin film superconducting devices.

Learn pyTDGL

The documentation for pyTDGL can be found at py-tdgl.readthedocs.io.

Try pyTDGL

Click the badge below to try pyTDGL interactively online via Google Colab:

About pyTDGL

Authors

• Primary author and maintainer: @loganbvh.

Citing pyTDGL

pyTDGL is described in the following paper:

pyTDGL: Time-dependent Ginzburg-Landau in Python, Computer Physics Communications 291, 108799 (2023), DOI: 10.1016/j.cpc.2023.108799.

If you use pyTDGL in your research, please cite the paper linked above.

% BibTeX citation
@article{
    Bishop-Van_Horn2023-wr,
    title    = "{pyTDGL}: Time-dependent {Ginzburg-Landau} in Python",
    author   = "Bishop-Van Horn, Logan",
    journal  = "Comput. Phys. Commun.",
    volume   =  291,
    pages    = "108799",
    month    =  may,
    year     =  2023,
    url      = "http://dx.doi.org/10.1016/j.cpc.2023.108799",
    issn     = "0010-4655",
    doi      = "10.1016/j.cpc.2023.108799"
}

Acknowledgments

Parts of this package have been adapted from SuperDetectorPy, a GitHub repo authored by Mattias Jönsson. Both SuperDetectorPy and py-tdgl are released under the open-source MIT License. If you use either package in an academic publication or similar, please consider citing the following in addition to the pyTDGL paper:

• Mattias Jönsson, Theory for superconducting few-photon detectors (Doctoral dissertation), KTH Royal Institute of Technology (2022) (Link)
• Mattias Jönsson, Robert Vedin, Samuel Gyger, James A. Sutton, Stephan Steinhauer, Val Zwiller, Mats Wallin, Jack Lidmar, Current crowding in nanoscale superconductors within the Ginzburg-Landau model, Phys. Rev. Applied 17, 064046 (2022) (Link)

The user interface is adapted from SuperScreen.