varipeps_python

variPEPS -- Versatile tensor network library for variational ground state simulations in two spatial dimensions

https://github.com/varipeps/varipeps_python

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

automatic-differentiation ground-state-energy jax peps physics physics-simulation quantum-many-body quantum-many-body-physics tensornetwork tensornetworks tensors variational-method
Last synced: 4 months ago · JSON representation ·

Repository

variPEPS -- Versatile tensor network library for variational ground state simulations in two spatial dimensions

Basic Info
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  • Stars: 13
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 33
Topics
automatic-differentiation ground-state-energy jax peps physics physics-simulation quantum-many-body quantum-many-body-physics tensornetwork tensornetworks tensors variational-method
Created almost 2 years ago · Last pushed 4 months ago
Metadata Files
Readme License Citation Zenodo

README.md

variPEPS -- Versatile tensor network library for variational ground state simulations in two spatial dimensions.

DOI Documentation Status PyPI - Version

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

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

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  • Release event: 15
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  • Push event: 42
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Last Year
  • Release event: 15
  • Watch event: 4
  • Push event: 42
  • Create event: 13

Dependencies

docs/requirements.txt pypi
  • sphinx >=4.4.0
  • sphinx_autodoc_defaultargs >=0.1.2
  • sphinx_rtd_theme >=1.0.0
  • sphinx_subfigure >=0.2.4
poetry.lock pypi
  • 132 dependencies
pyproject.toml pypi
  • 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
.github/workflows/release.yml actions
  • 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