GenericTensorNetworks
Generic tensor networks for solution space properties.
Science Score: 54.0%
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✓CITATION.cff file
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✓codemeta.json file
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✓Academic publication links
Links to: arxiv.org -
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○Scientific vocabulary similarity
Low similarity (11.5%) to scientific vocabulary
Keywords
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Repository
Generic tensor networks for solution space properties.
Basic Info
- Host: GitHub
- Owner: QuEraComputing
- License: other
- Language: Julia
- Default Branch: master
- Homepage: https://queracomputing.github.io/GenericTensorNetworks.jl/dev/
- Size: 6.69 MB
Statistics
- Stars: 110
- Watchers: 3
- Forks: 13
- Open Issues: 5
- Releases: 47
Topics
Metadata Files
README.md
GenericTensorNetworks
This package implements generic tensor networks to compute solution space properties of a class of hard combinatorial optimization problems. The solution space properties include * The maximum/minimum solution sizes, * The number of solutions at certain sizes, * The enumeration/sampling of solutions at certain sizes.
The types of problems that can be solved using this package include Independent set problem, Maximal independent set problem, Spin-glass problem, Cutting problem, Vertex matching problem, Binary paint shop problem, Coloring problem, Dominating set problem, Set packing problem, Satisfiability problem and Set covering problem.
Installation
GenericTensorNetworks is a
julia
pkg> add GenericTensorNetworks
To update, just type up in the package mode.
We recommend that you use Julia version >= 1.7; otherwise, your program may suffer from significant (exponential in the tensor dimension) overheads when permuting the dimensions of a large tensor.
If you have to use an older version of Julia, you can overwrite the LinearAlgebra.permutedims! by adding the following patch to your own project.
```julia
only required when your Julia version is < 1.7
using TensorOperations, LinearAlgebra function LinearAlgebra.permutedims!(C::Array{T,N}, A::StridedArray{T,N}, perm) where {T,N} if isbitstype(T) TensorOperations.tensorcopy!(A, ntuple(identity,N), C, perm) else invoke(permutedims!, Tuple{Any,AbstractArray,Any}, C, A, perm) end end ```
Supporting and Citing
Much of the software in this ecosystem was developed as a part of an academic research project. If you would like to help support it, please star the repository. If you use our software as part of your research, teaching, or other activities, we would like to request you to cite our work. The CITATION.bib file in the root of this repository lists the relevant papers.
Questions and Contributions
You can
* Post a question on Julia Discourse forum and ping the package maintainer with @1115.
* Discuss in the #graphs channel of the Julia Slack and ping the package maintainer with @JinGuo Liu.
* Open an issue if you encounter any problems, or have any feature request.
Owner
- Name: QuEra Computing Inc.
- Login: QuEraComputing
- Kind: organization
- Email: info@quera.com
- Location: United States of America
- Website: https://www.quera.com/
- Twitter: QueraComputing
- Repositories: 8
- Profile: https://github.com/QuEraComputing
Building scalable quantum machines to make impossible problems simple.
Citation (CITATION.bib)
@ARTICLE{Liu2022Computing,
author = {{Liu}, Jin-Guo and {Gao}, Xun and {Cain}, Madelyn and {Lukin}, Mikhail D. and {Wang}, Sheng-Tao},
title = "{Computing solution space properties of combinatorial optimization problems via generic tensor networks}",
journal = {arXiv e-prints},
keywords = {Condensed Matter - Statistical Mechanics},
year = 2022,
month = may,
eid = {arXiv:2205.03718},
pages = {arXiv:2205.03718},
archivePrefix = {arXiv},
eprint = {2205.03718},
primaryClass = {cond-mat.stat-mech},
adsurl = {https://ui.adsabs.harvard.edu/abs/2022arXiv220503718L},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
@article{Ebadi_2022,
doi = {10.1126/science.abo6587},
url = {https://doi.org/10.1126%2Fscience.abo6587},
year = 2022,
month = {jun},
publisher = {American Association for the Advancement of Science ({AAAS})},
volume = {376},
number = {6598},
pages = {1209--1215},
author = {S. Ebadi and A. Keesling and M. Cain and T. T. Wang and H. Levine and D. Bluvstein and G. Semeghini and A. Omran and J.-G. Liu and R. Samajdar and X.-Z. Luo and B. Nash and X. Gao and B. Barak and E. Farhi and S. Sachdev and N. Gemelke and L. Zhou and S. Choi and H. Pichler and S.-T. Wang and M. Greiner and V. Vuleti{\'{c}
} and M. D. Lukin},
title = {Quantum optimization of maximum independent set using Rydberg atom arrays},
journal = {Science}
}
@article{Liu_2021,
doi = {10.1103/physrevlett.126.090506},
url = {https://doi.org/10.1103%2Fphysrevlett.126.090506},
year = 2021,
month = {mar},
publisher = {American Physical Society ({APS})},
volume = {126},
number = {9},
author = {Jin-Guo Liu and Lei Wang and Pan Zhang},
title = {Tropical Tensor Network for Ground States of Spin Glasses},
journal = {Physical Review Letters}
}
GitHub Events
Total
- Create event: 12
- Issues event: 4
- Release event: 6
- Watch event: 16
- Delete event: 5
- Issue comment event: 24
- Push event: 28
- Pull request review event: 2
- Pull request event: 19
- Fork event: 4
Last Year
- Create event: 12
- Issues event: 4
- Release event: 6
- Watch event: 16
- Delete event: 5
- Issue comment event: 24
- Push event: 28
- Pull request review event: 2
- Pull request event: 19
- Fork event: 4
Committers
Last synced: 8 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| GiggleLiu | c****9@g****m | 278 |
| github-actions[bot] | 4****] | 4 |
| CompatHelper Julia | c****y@j****g | 2 |
| c-allergic | 1****c | 1 |
| Zhongyi Ni | 1****7 | 1 |
| Shengtao Wang | W****o | 1 |
| Pietro Monticone | 3****e | 1 |
| Feng Pan | f****s@1****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 19
- Total pull requests: 80
- Average time to close issues: about 1 month
- Average time to close pull requests: 2 days
- Total issue authors: 8
- Total pull request authors: 7
- Average comments per issue: 6.37
- Average comments per pull request: 0.4
- Merged pull requests: 68
- Bot issues: 0
- Bot pull requests: 16
Past Year
- Issues: 2
- Pull requests: 14
- Average time to close issues: 36 minutes
- Average time to close pull requests: 1 day
- Issue authors: 2
- Pull request authors: 4
- Average comments per issue: 1.0
- Average comments per pull request: 0.21
- Merged pull requests: 10
- Bot issues: 0
- Bot pull requests: 2
Top Authors
Issue Authors
- GiggleLiu (13)
- ChenZhao44 (1)
- Roger-luo (1)
- slwu89 (1)
- fliingelephant (1)
- pengfzhou (1)
- JuliaTagBot (1)
- johnzl-777 (1)
Pull Request Authors
- GiggleLiu (65)
- github-actions[bot] (20)
- c-allergic (6)
- nzy1997 (2)
- pitmonticone (1)
- Fanerst (1)
- Wang-Shengtao (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- julia 22 total
- Total dependent packages: 1
- Total dependent repositories: 0
- Total versions: 32
juliahub.com: GenericTensorNetworks
Generic tensor networks for solution space properties.
- Homepage: https://queracomputing.github.io/GenericTensorNetworks.jl/dev/
- Documentation: https://docs.juliahub.com/General/GenericTensorNetworks/stable/
- License: Apache-2.0
-
Latest release: 4.1.0
published 8 months ago
Rankings
Dependencies
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- actions/checkout v2 composite
- codecov/codecov-action v1 composite
- fkirc/skip-duplicate-actions master composite
- julia-actions/julia-buildpkg v1 composite
- julia-actions/julia-processcoverage v1 composite
- julia-actions/julia-runtest v1 composite
- julia-actions/setup-julia v1 composite
- JuliaRegistries/TagBot v1 composite