qnetvo

Simulate and optimize quantum communication networks using quantum computers.

https://github.com/chitambarlab/qnetvo

Science Score: 64.0%

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
  • DOI references
    Found 6 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
  • Committers with academic emails
    2 of 6 committers (33.3%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (14.1%) to scientific vocabulary

Keywords

quantum-computing quantum-network-simulator quantum-networks quantum-noise variational-optimization variational-quantum-circuits
Last synced: 6 months ago · JSON representation ·

Repository

Simulate and optimize quantum communication networks using quantum computers.

Basic Info
Statistics
  • Stars: 17
  • Watchers: 5
  • Forks: 7
  • Open Issues: 0
  • Releases: 12
Topics
quantum-computing quantum-network-simulator quantum-networks quantum-noise variational-optimization variational-quantum-circuits
Created almost 5 years ago · Last pushed over 1 year ago
Metadata Files
Readme License Citation

README.md

qNetVO: Quantum Network Variational Optimizer

Simulate and optimize quantum communication networks using quantum computers.

LatestTest StatusCode style: blackPyPI versionDOI

Features

QNetVO simulates quantum communication networks on differentiable quantum cicuits. The cicuit parameters are optimized with respect to a cost function using automatic differentiation and gradient descent. QNetVO is powered by PennyLane, an open-source framework for cross-platform quantum machine learning.

Simulating Quantum Communication Networks:

  • Construct complex quantum network ansatzes from generic quantum circuit compenents.
  • Simulate the quantum network on a quantum computer or classical simulator.

Optimizing Quantum Communication Networks:

  • Use our library of network-oriented cost functions or create your own.
  • Gradient descent methods for tuning quantum network ansatz settings to minimize the cost.

Quick Start

Install qNetVO:

$ pip install qnetvo

Install PennyLane:

$ pip install pennylane==0.37

Import packages:

import pennylane as qml import qnetvo as qnet

Note

For optimal use, qNetVO should be used with PennyLane. QNetVO is currently compatible with PennyLane v0.37.

Contributing

We welcome outside contributions to qNetVO. Please see the Contributing page for details and a development guide.

How to Cite

DOI

See CITATION.bib for a BibTex reference to qNetVO.

License

QNetVO is free and open-source. The software is released under the Apache License, Version 2.0. See LICENSE for details and NOTICE for copyright information.

Acknowledgments

We thank Xanadu, the UIUC Physics Department, and the Quantum Information Science and Engineering Network (QISE-Net) for their support of qNetVO. Work funded by NSF award DMR-1747426.

Owner

  • Name: Chitambar Lab Group
  • Login: ChitambarLab
  • Kind: organization
  • Location: United States of America

Citation (CITATION.bib)

@misc{qNetVO,
	author  = {Brian Doolittle and Tom Bromley},
	title   = {qNetVO: the Quantum Network Variational Optimizer},
	howpublished =  {\url{https://github.com/ChitambarLab/qNetVO}},
	url     = {https://github.com/ChitambarLab/qNetVO},
	version = {v0.4.3},
	year    = {2022},
	month   = {March},
	doi     = {10.5281/zenodo.6345834},
}

GitHub Events

Total
  • Watch event: 8
  • Fork event: 1
Last Year
  • Watch event: 8
  • Fork event: 1

Committers

Last synced: almost 3 years ago

All Time
  • Total Commits: 432
  • Total Committers: 6
  • Avg Commits per committer: 72.0
  • Development Distribution Score (DDS): 0.023
Top Committers
Name Email Commits
Brian Doolittle b****e@g****m 422
trbromley b****2@g****m 3
Danny Chen d****n@m****v 3
Nathan Killoran c****y@u****m 2
Tom Bromley 4****y@u****m 1
Danny Chen d****n@m****v 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 8 months ago

All Time
  • Total issues: 0
  • Total pull requests: 55
  • Average time to close issues: N/A
  • Average time to close pull requests: 18 days
  • Total issue authors: 0
  • Total pull request authors: 5
  • Average comments per issue: 0
  • Average comments per pull request: 0.64
  • Merged pull requests: 53
  • 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: 5 days
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 4.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
Pull Request Authors
  • bdoolittle (51)
  • m-bhatia (2)
  • trbromley (2)
  • co9olguy (1)
  • dannychen0830 (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 31 last-month
  • Total dependent packages: 1
  • Total dependent repositories: 1
  • Total versions: 12
  • Total maintainers: 1
pypi.org: qnetvo

The Quantum Network Variational Optimizer

  • Versions: 12
  • Dependent Packages: 1
  • Dependent Repositories: 1
  • Downloads: 31 Last month
Rankings
Dependent packages count: 4.8%
Forks count: 14.2%
Average: 17.7%
Stargazers count: 18.5%
Dependent repos count: 21.6%
Downloads: 29.5%
Maintainers (1)
Last synced: 6 months ago

Dependencies

docs/requirements.txt pypi
  • Pygments >=2.7.4
  • furo *
  • m2r2 ==0.3.2
  • pennylane *
  • sphinx >=3.0
  • sphinxcontrib-email ==0.3.5
requirements.txt pypi
  • dask *
  • pennylane ==0.22
  • pennylane-qiskit ==0.20
  • qiskit ==0.34
  • tensorflow >=2.0,<3.0
  • tensornetwork >=0.3,<0.4
.github/workflows/build_documentation.yml actions
  • actions/checkout v1 composite
  • ad-m/github-push-action master composite
  • ammaraskar/sphinx-action master composite
.github/workflows/check_documentation.yml actions
  • actions/checkout v1 composite
  • ammaraskar/sphinx-action master composite
.github/workflows/formatting_check.yml actions
  • actions/checkout v2 composite
  • actions/setup-python v2 composite
  • styfle/cancel-workflow-action 0.4.1 composite
.github/workflows/run_tests.yml actions
  • actions/checkout v2 composite
  • actions/setup-python v2 composite
  • styfle/cancel-workflow-action 0.4.1 composite
environment.yml pypi
  • furo *
  • m2r2 ==0.3
  • sphinxcontrib-email ==0.3.5
pyproject.toml pypi