• CMTJ
  • Table of contents
  • Short description
  • Web GUI
  • Quickstart
    • Installation 🚀
    • Extra dependencies
  • Documentation and examples
  • Extensions
  • Citing
• Development
  • Acknowledgements
  • Contributions
  • Docker
  • Precommit
  • Documentation builds

The cmtj name may be misleading -- the MTJ (Magnetic Tunnel Junctions) are not the only structures that may be simulated. The library allows for macromagnetic simulation of various multilayer spintronic structures. The package uses C++ implementation of (s)LLGS (stochastic Landau-Lifschitz-Gilbert-Slonczewski) equation with various field contributions included for instance: anisotropy, interlayer exchange coupling, demagnetisation, dipole fields etc. It is also possible to connect devices in parallel or in series to have electrically coupled arrays.

Check out the streamlit hosted demo here. You can simulate PIMM spectra and Spin-Diode spectra there. Let us know if you have any issues with the demo.

The recommended way is to use the pip package manager and virtualenv (or conda). Installation is as easy as doing:

1. With virtualenv (recommended):

$(bash) python -m venv .my-venv
$(bash) source .my-venv/bin/activate
$(.my-venv) python -m pip install cmtj

2. Straight from pip:

python3 -m pip install cmtj

3. Straight from source:

python3 -m pip install git+https://github.com/LemurPwned/cmtj.git

4. Clone the repository:

git clone https://github.com/LemurPwned/cmtj.git
python3 -m pip install .

The package requires (if utils subpackage is used):

- numpy
- scipy
- matplotlib

Documentation: https://lemurpwned.github.io/cmtj. There are many examples available, check out the examples section in the docs

There's a GUI version available! If you wish to conduct a subset of simulations, mainly for experimental modelling, please see the PyMag project. It uses CMTJ as a backend for fast computation.

We would appreciate citing either of the listed work if you decide to use the project or using the cite button on the right hand side panel of the repository:

cmtj: Simulation package for analysis of multilayer spintronic devices

@article{mojsiejuk_cmtj_2023,
	title = {cmtj: Simulation package for analysis of multilayer spintronic devices},
	volume = {9},
	issn = {2057-3960},
	url = {https://www.nature.com/articles/s41524-023-01002-x},
	doi = {10.1038/s41524-023-01002-x},
	pages = {54},
	number = {1},
	journaltitle = {npj Comput Mater},
	author = {Mojsiejuk, Jakub and Ziętek, Sławomir and Grochot, Krzysztof and Skowroński, Witold and Stobiecki, Tomasz},
	date = {2023-04-06},
}

Many thanks to professor Jack Sankey for his help with the development of thermal contributions, with inspiration from the macrospinmob project.

All contributions are welcome, please leave an issue if you've encountered any trouble with setup or running the library.

In the docker directory there's a Dockerfile that can be used to build a docker image with the library installed. Dockerfile.app is used for streamlit development.

There's a .pre-commit-config.yaml that does some basic python and cpp lints and checks. More static analysis to come in the future. This may be run with:

pre-commit run -v

or

pre-commit run -a (or --files core/* cmtj/*)

There are couple of stages to building the documentation

1. Build Doxygen documentation

   doxygen Doxyfile
   

   This is mostly for the C++ documentation. Furture changes may couple C++ and Python docs.
2. Build stubs The stubgen is pybind11-stubgen or mypy stubgen with the latter being preferred now. Before running the stubgen, make sure to install the package with:

   python3 -m pip install .
   

   avoid using -e flag as it may cause issues with the stubgen. Then to generate, for instance, Stack module stubs we can do:

   stubgen -m cmtj.stack -o target-stub-dir/
   

   or

   python3 -c "import mypy.stubgen; mypy.stubgen.main(['-p', 'cmtj.stack', '-o', 'target-stub-dir/'])"
   

   More info here: https://mypy.readthedocs.io/en/stable/stubgen.html.
3. Parse stubs to Markdown. This stage is done by running: python3 docs/docgen.py The deployment of the documentation is done via:

   mkdocs gh-deploy

   But first, worth a check:

   mkdocs serve