Skip to main content

Toolset for control, calibration and characterization of physical systems

Project description

C3 - An integrated tool-set for Control, Calibration and Characterization

codecov Language grade: Python Build and Test Documentation Status Code style: black PyPI version fury.io PyPI license PyPI pyversions Binder

The C3 package is intended to close the loop between open-loop control optimization, control pulse calibration, and model-matching based on calibration data.

Installation

pip install c3-toolset

If you want to try out the bleeding edge (possibly buggy) version under development:

pip install c3-toolset-nightly

There is no official support for c3-toolset on Apple Silicon devices, but you can check the CONTRIBUTING.md for instructions on setting up an experimental version.

Usage

C3 provides a simple Python API through which it may integrate with virtually any experimental setup. Contact us at c3@q-optimize.org.

The paper introducing C3 as a concept can be found on the arxiv.

Documentation is available here on RTD.

Examples are available in the examples/ directory and can also be run online using the launch|binder badge above.

If you wish to contribute, please check out the issues tab and also the CONTRIBUTING.md for useful resources.

The source code is available on Github at https://github.com/q-optimize/c3.

Citation

If you use c3-toolset in your research, please cite it as below:

@article{Wittler2021,
   title={Integrated Tool Set for Control, Calibration, and Characterization of Quantum Devices Applied to Superconducting Qubits},
   volume={15},
   DOI={10.1103/physrevapplied.15.034080},
   number={3},
   journal={Physical Review Applied},
   author={Wittler, Nicolas and Roy, Federico and Pack, Kevin and Werninghaus, Max and Saha Roy, Anurag and Egger, Daniel J. and Filipp, Stefan and Wilhelm, Frank K. and Machnes, Shai},
   year={2021},
   month={Mar}
}

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

c3-toolset-nightly-20220421.tar.gz (117.2 kB view details)

Uploaded Source

Built Distribution

c3_toolset_nightly-20220421-py3-none-any.whl (111.4 kB view details)

Uploaded Python 3

File details

Details for the file c3-toolset-nightly-20220421.tar.gz.

File metadata

  • Download URL: c3-toolset-nightly-20220421.tar.gz
  • Upload date:
  • Size: 117.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.9.12

File hashes

Hashes for c3-toolset-nightly-20220421.tar.gz
Algorithm Hash digest
SHA256 1f0b615c7065d3f45f7a6c9e649f891ec7d07b08b919f7bf00cd0596fddf841f
MD5 fa415b0a7b6695879123b066a4e87622
BLAKE2b-256 6b63424fd6036c91e0fa1ca41428e6bd728d3d3e9356006e85add0942f1c29a2

See more details on using hashes here.

File details

Details for the file c3_toolset_nightly-20220421-py3-none-any.whl.

File metadata

File hashes

Hashes for c3_toolset_nightly-20220421-py3-none-any.whl
Algorithm Hash digest
SHA256 be5587f0a64a3cc7651e14f7e7a28061b6ceff0c4f596094a302194d3a6a86b3
MD5 c97e24a9dd4e2587241059bb1dc13c0e
BLAKE2b-256 99137cfb436493eb1e73c31352945d9c0760de8eb9bc5348feeb02b3aa304269

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page