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https://github.com/boothgroup/momentgw

GW approximation and associated methods using moment-conserving Dyson equation solvers

https://github.com/boothgroup/momentgw

Science Score: 49.0%

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    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
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    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 2 DOI reference(s) in README
  • ○
    Academic publication links
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    Committers with academic emails
    1 of 4 committers (25.0%) from academic institutions
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    Scientific vocabulary similarity
    Low similarity (12.7%) to scientific vocabulary
Last synced: 7 months ago · JSON representation

Repository

GW approximation and associated methods using moment-conserving Dyson equation solvers

Basic Info
Statistics
  • Stars: 8
  • Watchers: 2
  • Forks: 4
  • Open Issues: 11
  • Releases: 0
Created over 3 years ago · Last pushed 9 months ago
Metadata Files
Readme License

README.md

momentGW

CI Code style

The momentGW code is a Python package for performing calculations within the GW approximation, along with other associated methods, using moment-conserving solutions to the Dyson equation. A diverse range of self-consistent schemes are available, along with dTDA and dRPA polarizabilities, unrestricted and/or periodic boundary conditions, tensor hypercontraction, optical excitations, and more.

Installation

The momentGW package, along with dependencies, can be installed as bash git clone https://github.com/BoothGroup/momentGW.git cd momentGW python -m pip install . --user

Usage

The momentGW solvers are built on top of the PySCF package, and the classes behave similarly to other post-mean-field method classes in PySCF, e.g.: python from pyscf import gto, scf from momentGW import GW mol = gto.M(atom="H 0 0 0; Li 0 0 1.64", basis="6-31g") mf = scf.RHF(mol).run() gw = GW(mf) gw.kernel(nmom_max=3) The examples directory contains more detailed usage examples.

Publications

The methods implemented in this package have been described in the following papers: - "A 'moment-conserving' reformulation of GW theory"

The data presented in the publications can be found in the benchmark directory.

Contributing

Contributions are welcome, and can be made by submitting a pull request to the master branch. The code uses NumPy-style docstrings and is formatted using black, isort, ssort, and flake8. The package includes pre-commit hooks to apply these formatting rules. To install the necessary packages for development, install the package with the dev extra: bash python -m pip install .[dev] --user

Owner

  • Name: BoothGroup
  • Login: BoothGroup
  • Kind: organization

GitHub Events

Total
  • Watch event: 1
  • Issue comment event: 1
  • Push event: 10
  • Pull request review comment event: 2
  • Pull request review event: 3
  • Pull request event: 2
  • Fork event: 1
  • Create event: 2
Last Year
  • Watch event: 1
  • Issue comment event: 1
  • Push event: 10
  • Pull request review comment event: 2
  • Pull request review event: 3
  • Pull request event: 2
  • Fork event: 1
  • Create event: 2

Committers

Last synced: 9 months ago

All Time
  • Total Commits: 643
  • Total Committers: 4
  • Avg Commits per committer: 160.75
  • Development Distribution Score (DDS): 0.196
Past Year
  • Commits: 9
  • Committers: 1
  • Avg Commits per committer: 9.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Ollie Backhouse o****e@g****m 517
mkakcl m****0@g****m 98
Charles Scott c****t@g****m 20
George Booth g****h@k****k 8
Committer Domains (Top 20 + Academic)
kcl.ac.uk: 1

Issues and Pull Requests

Last synced: 9 months ago

All Time
  • Total issues: 16
  • Total pull requests: 102
  • Average time to close issues: 1 day
  • Average time to close pull requests: 8 days
  • Total issue authors: 1
  • Total pull request authors: 3
  • Average comments per issue: 0.63
  • Average comments per pull request: 0.96
  • Merged pull requests: 93
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: about 4 hours
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • obackhouse (7)
Pull Request Authors
  • obackhouse (78)
  • mkakcl (13)
  • cjcscott (1)
Top Labels
Issue Labels
enhancement (5)
Pull Request Labels

Dependencies

.github/workflows/ci.yaml actions
  • actions/checkout v2 composite
  • actions/setup-python v2 composite
pyproject.toml pypi
  • dyson @ git+https://github.com/BoothGroup/dyson@master
  • numpy >=1.19.0
  • pyscf >=2.0.0
  • scipy <=1.10.0