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-20220403.tar.gz (116.4 kB view details)

Uploaded Source

Built Distribution

c3_toolset_nightly-20220403-py3-none-any.whl (111.1 kB view details)

Uploaded Python 3

File details

Details for the file c3-toolset-nightly-20220403.tar.gz.

File metadata

  • Download URL: c3-toolset-nightly-20220403.tar.gz
  • Upload date:
  • Size: 116.4 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-20220403.tar.gz
Algorithm Hash digest
SHA256 ec10f0fd692554d217acc319657efce041a3072dec31d2ea7524ee565894019e
MD5 2362ab78cedbcc11623fb3f8ef70afd3
BLAKE2b-256 55fa0f6fc134c3e60853cfb664f753dce7b8b85230511fef0484f26332652e29

See more details on using hashes here.

File details

Details for the file c3_toolset_nightly-20220403-py3-none-any.whl.

File metadata

File hashes

Hashes for c3_toolset_nightly-20220403-py3-none-any.whl
Algorithm Hash digest
SHA256 bc83f444cfaf4a40eb56d42517357762b04a15ce2679ff4eba68eb659c5fad28
MD5 3ea5f54a1bf7f1d556a4f0a0d0f4b497
BLAKE2b-256 acbccee241b4bece5e6bd17813b7445f47d6f5171b0aca0881b2f5ccd5f3482d

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