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 scientific concept can be found in Wittler2021. Software and implementation details are described in SahaRoy2022.

Documentation is available here on RTD.

Examples

The following notebooks are available in the examples/ directory and can also be run online using the launch|binder badge above:

Contributing

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-20220921.tar.gz (126.1 kB view details)

Uploaded Source

Built Distribution

c3_toolset_nightly-20220921-py3-none-any.whl (116.6 kB view details)

Uploaded Python 3

File details

Details for the file c3-toolset-nightly-20220921.tar.gz.

File metadata

  • Download URL: c3-toolset-nightly-20220921.tar.gz
  • Upload date:
  • Size: 126.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.14

File hashes

Hashes for c3-toolset-nightly-20220921.tar.gz
Algorithm Hash digest
SHA256 14c4303f321c2ef66850d6f6ae95d9df11b39c629d831535aa4c96cc49cff1f4
MD5 98d698c114e9347eb059b1b2b8b29a8c
BLAKE2b-256 741e0e382ac9cf22bb168b2e42db35d118b94c05d573d31c6d7395daa3a62dd2

See more details on using hashes here.

File details

Details for the file c3_toolset_nightly-20220921-py3-none-any.whl.

File metadata

File hashes

Hashes for c3_toolset_nightly-20220921-py3-none-any.whl
Algorithm Hash digest
SHA256 1b3bcf045da64c979f57081f47c65fcd29d3be1621413e40bda6c5c00262ef6f
MD5 aaba27338fcd964aca097e97f5b97f4d
BLAKE2b-256 de341e54f14d716dc6eb659cd305a2df9f6079f967070cec00614e00f7173869

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