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-20220721.tar.gz (119.1 kB view details)

Uploaded Source

Built Distribution

c3_toolset_nightly-20220721-py3-none-any.whl (111.9 kB view details)

Uploaded Python 3

File details

Details for the file c3-toolset-nightly-20220721.tar.gz.

File metadata

  • Download URL: c3-toolset-nightly-20220721.tar.gz
  • Upload date:
  • Size: 119.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.13

File hashes

Hashes for c3-toolset-nightly-20220721.tar.gz
Algorithm Hash digest
SHA256 79cdf968ad1c58bed266b63aa2d99cd9a4069dc939281a731b56d87bb2acd26e
MD5 c59481e133b668e952bacb337dadfadb
BLAKE2b-256 845842d403c0ed34c7fa7142175b3e0501ea0b2aae607eccc44a63b898e661e4

See more details on using hashes here.

File details

Details for the file c3_toolset_nightly-20220721-py3-none-any.whl.

File metadata

File hashes

Hashes for c3_toolset_nightly-20220721-py3-none-any.whl
Algorithm Hash digest
SHA256 262b8fb5e302c983d58e889c05caac15708f80cc86724e653d6b1a6b4b0df760
MD5 e01636670323f1b9ac53cbf491a483ce
BLAKE2b-256 ab0cf0cb03fbd6948b5ed73b86161d8dc424d9f5bbe84df6f6c2f62e09b0df75

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