varipeps_python
variPEPS -- Versatile tensor network library for variational ground state simulations in two spatial dimensions
Science Score: 67.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 11 DOI reference(s) in README -
✓Academic publication links
Links to: arxiv.org, zenodo.org -
○Academic email domains
-
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (14.4%) to scientific vocabulary
Keywords
Repository
variPEPS -- Versatile tensor network library for variational ground state simulations in two spatial dimensions
Basic Info
- Host: GitHub
- Owner: variPEPS
- License: gpl-3.0
- Language: Python
- Default Branch: main
- Homepage: https://varipeps.readthedocs.io/en/stable/
- Size: 2.63 MB
Statistics
- Stars: 13
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 33
Topics
Metadata Files
README.md
variPEPS -- Versatile tensor network library for variational ground state simulations in two spatial dimensions.
variPEPS is the Python variant of the tensor network library developed for variational ground state simulations in two spatial dimensions applying gradient optimization using automatic differentation.
For a detailed report on the method, please see our publication currently available as preprint on arXiv: https://arxiv.org/abs/2308.12358.
Installation
Installation using pip
The current version of the variPEPS Python package is available on PyPI. It can be easily installed by using the Python package manager pip:
bash
$ python3 -m pip install variPEPS
Usage
For detailed information how to use the package we want to point out to the documentation of the project.
Citation
We are happy if you want to use the framework for your research. For the citation of our work we ask to use the following references (the publication with the method description, the Zenodo reference for this Git repository and the repository itself): * J. Naumann, E. L. Weerda, M. Rizzi, J. Eisert, and P. Schmoll, An introduction to infinite projected entangled-pair state methods for variational ground state simulations using automatic differentiation, SciPost Phys. Lect. Notes 86 (2024), doi:10.21468/SciPostPhysLectNotes.86. * J. Naumann, P. Schmoll, F. Wilde, and F. Krein, variPEPS (Python version), Zenodo.
The BibTeX code for these references are: ```bibtex @article{10.21468/SciPostPhysLectNotes.86, title={{An introduction to infinite projected entangled-pair state methods for variational ground state simulations using automatic differentiation}}, author={Jan Naumann and Erik Lennart Weerda and Matteo Rizzi and Jens Eisert and Philipp Schmoll}, journal={SciPost Phys. Lect. Notes}, pages={86}, year={2024}, publisher={SciPost}, doi={10.21468/SciPostPhysLectNotes.86}, url={https://scipost.org/10.21468/SciPostPhysLectNotes.86}, }
@misc{naumann2025variationallyoptimizinginfiniteprojected, title={Variationally optimizing infinite projected entangled-pair states at large bond dimensions: A split-CTMRG approach}, author={Jan Naumann and Erik Lennart Weerda and Jens Eisert and Matteo Rizzi and Philipp Schmoll}, year={2025}, eprint={2502.10298}, archivePrefix={arXiv}, primaryClass={cond-mat.str-el}, url={https://arxiv.org/abs/2502.10298}, }
@software{naumann24varipepspython, author = {Jan Naumann and Philipp Schmoll and Frederik Wilde and Finn Krein}, title = {{variPEPS (Python version)}}, howpublished = {Zenodo}, url = {https://doi.org/10.5281/ZENODO.10852390}, doi = {10.5281/ZENODO.10852390}, } ```
Owner
- Name: variPEPS
- Login: variPEPS
- Kind: organization
- Repositories: 1
- Profile: https://github.com/variPEPS
Citation (CITATION.cff)
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: variPEPS (Python version)
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- given-names: Jan
family-names: Naumann
email: j.naumann@fu-berlin.de
affiliation: Freie Universität Berlin
orcid: 'https://orcid.org/0000-0003-4513-5139'
- given-names: Schmoll
family-names: Philipp
affiliation: Freie Universität Berlin
orcid: 'https://orcid.org/0000-0001-5534-6103'
email: philipp.schmoll@fu-berlin.de
- given-names: Wilde
orcid: 'https://orcid.org/0000-0002-6224-1964'
family-names: Frederik
affiliation: Freie Universität Berlin
- given-names: Krein
family-names: Finn
identifiers:
- type: doi
value: 10.21468/SciPostPhysLectNotes.86
description: Journal article with the description of the method
- type: doi
value: 10.48550/arXiv.2502.10298
description: Prepribt with the description of the split-CTMRG method
- type: doi
value: 10.5281/zenodo.10852390
description: Zenodo DOI for current version of the code
repository-code: 'https://github.com/variPEPS/variPEPS_Python'
url: 'https://varipeps.readthedocs.io/en/stable'
abstract: >-
A versatile tensor network library for variational ground
state simulations in two spatial dimensions
keywords:
- physics
- automatic-differentiation
- peps
- tensor-networks
- variational-optimization
- quantum-many-body
- quantum-many-body-physics
license: GPL-3.0-or-later
GitHub Events
Total
- Release event: 15
- Watch event: 4
- Push event: 42
- Create event: 13
Last Year
- Release event: 15
- Watch event: 4
- Push event: 42
- Create event: 13
Dependencies
- sphinx >=4.4.0
- sphinx_autodoc_defaultargs >=0.1.2
- sphinx_rtd_theme >=1.0.0
- sphinx_subfigure >=0.2.4
- 132 dependencies
- black >=21.8-beta.0 develop
- flake8 >=3.9.2 develop
- ipython >=7.27.0 develop
- jupyter >=1.0.0 develop
- mypy >=0.910 develop
- pylint >=2.10.2 develop
- h5py >=3.6.0
- jax >=0.3.16
- numpy >=1.21.2
- poethepoet >=0.10.0
- python >=3.9,<4.0
- scipy >=1.7.1
- tensornetwork >=0.4.5
- tqdm >=4.64.1
- tqdm-loggable ^0.1.3
- actions/checkout v4 composite
- actions/download-artifact v4 composite
- actions/setup-python v5 composite
- actions/upload-artifact v4 composite
- pypa/gh-action-pypi-publish release/v1 composite