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 and navigate to docs/notebooks/ to try pyTDGL interactively online via Binder

Install pyTDGL

pyTDGL requires python 3.8, 3.9, or 3.10. We recommend installing pyTDGL in a conda environment, e.g.

conda create --name tdgl python="3.10"
conda activate tdgl

Install via pip

From PyPI, the Python Package index:

pip install tdgl

From this GitHub repository:

pip install git+https://github.com/loganbvh/py-tdgl.git

Editable installation:

git clone https://github.com/loganbvh/py-tdgl.git
cd py-tdgl
pip install -e ".[dev,docs]"

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:

• 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.