.. grassmanntn documentation master file, created by sphinx-quickstart on Thu Aug 24 15:42:41 2023. You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. GrassmannTN 1.4.0 ======================================= GrassmannTN is a python package that aims to simplify the coding involving Grassmann tensor network. The goal is 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. If you have further questions about the package and how to use it, please contact me via ayosp-at-phys.sc.niigata-u.ac.jp Package structure ----------------- - `grassmanntn `_ (main module): contains most of the features. - `grassmanntn.param `_: contains technical functions such as the sign factor :math:`\sigma_I`, the parity :math:`p(I)` or the encoder-switching function :math:`\varepsilon(I)`. - `grassmann.arith `_: a new module added in v 1.3.0 to help the user build the initial tensor directly from the fermionic action/Hamiltonian. Symbolic expression is supported. Useful links ------------ - `GitHub `_ - `PyPI `_ - `full paper `_ - `arXiv `_ Prerequisites ------------- - `numpy `_ - `sparse `_ - `opt_einsum `_ - `sympy `_ Installation ------------- Installation via PyPI :: 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 :math:`\mathbb{Z}_2` gauge theory should be able to run. .. toctree:: :maxdepth: 2 :caption: Contents: releases settings examples schwinger grassmanntn/index grassmanntn.param/index grassmanntn.arith/index