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-20221220.tar.gz (126.0 kB view details)

Uploaded Source

Built Distribution

c3_toolset_nightly-20221220-py3-none-any.whl (116.6 kB view details)

Uploaded Python 3

File details

Details for the file c3-toolset-nightly-20221220.tar.gz.

File metadata

  • Download URL: c3-toolset-nightly-20221220.tar.gz
  • Upload date:
  • Size: 126.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.16

File hashes

Hashes for c3-toolset-nightly-20221220.tar.gz
Algorithm Hash digest
SHA256 d4c4852138f87c73d0894d2023fa7f969bd64ef4b5f665f21bb0610e092c2d5a
MD5 36ecddd65e6ffcf7643c745c12d8780b
BLAKE2b-256 19c034add08b2fec16e6ee78f3828d0d085bcb361de90202235f783af3b82017

See more details on using hashes here.

File details

Details for the file c3_toolset_nightly-20221220-py3-none-any.whl.

File metadata

File hashes

Hashes for c3_toolset_nightly-20221220-py3-none-any.whl
Algorithm Hash digest
SHA256 36499147b84b388784dc91ef63757e1d608b7b2ef5e8792a3a2e2517965e01d1
MD5 208498eb441d65bd7399f169ddd4b272
BLAKE2b-256 c5c060cd1d756de0719e2e673801a67b7411c443df2c457f98ff17ae918a8627

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