This is a package that aims to simplify the coding involving Grassmann tensor network. I try to make the coding as convenient as when you use other standard packages like numpy or scipy. All the sign factors are computed automatically without explicit user inputs.

• documentation
• PyPI
• full paper
• arXiv preprint

• numpy
• sparse
• opt_einsum
• sympy

pip install grassmanntn

Once the package is installed, download example.py and try running it with

python3 example.py --show_progress

An example code of a one-flavor two-dimensional $\mathbb{Z}_2$ gauge theory should be able to run.

Please see documentation.