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-20220515.tar.gz (117.8 kB view details)

Uploaded Source

Built Distribution

c3_toolset_nightly-20220515-py3-none-any.whl (112.3 kB view details)

Uploaded Python 3

File details

Details for the file c3-toolset-nightly-20220515.tar.gz.

File metadata

  • Download URL: c3-toolset-nightly-20220515.tar.gz
  • Upload date:
  • Size: 117.8 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-20220515.tar.gz
Algorithm Hash digest
SHA256 8577f102ffbf6f743248a74c932ec4616b6d43cfa9b76a3eda285ed2ba249f6f
MD5 d3517cb7e5369fd39009e119a3abc6cd
BLAKE2b-256 50bbd3589913a20dd0aba80a424e4749ca577220082d9323eed931ee45e0c4fd

See more details on using hashes here.

File details

Details for the file c3_toolset_nightly-20220515-py3-none-any.whl.

File metadata

File hashes

Hashes for c3_toolset_nightly-20220515-py3-none-any.whl
Algorithm Hash digest
SHA256 d9dc8d325e5956c30861ae644e74d6dff81dfe504ba4459742924ad44d4dcac1
MD5 dfbf3b726bad77414d233e8eb5597fad
BLAKE2b-256 f51721adbcfd3db980b8ca07669906005b44903c62c9a8cdc34b3ea451a5bd79

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