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-20220508.tar.gz (117.8 kB view details)

Uploaded Source

Built Distribution

c3_toolset_nightly-20220508-py3-none-any.whl (112.3 kB view details)

Uploaded Python 3

File details

Details for the file c3-toolset-nightly-20220508.tar.gz.

File metadata

  • Download URL: c3-toolset-nightly-20220508.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-20220508.tar.gz
Algorithm Hash digest
SHA256 c38a44eddb7d1127e4f2384552f6365c0620441b28475f9ee2c65a7491ceca26
MD5 d488a812d74448f38af91cc83eb8c3ea
BLAKE2b-256 30fbe44a97475f06fdac902274ffa9738edc929e275eb7dc28b9698f030e029d

See more details on using hashes here.

File details

Details for the file c3_toolset_nightly-20220508-py3-none-any.whl.

File metadata

File hashes

Hashes for c3_toolset_nightly-20220508-py3-none-any.whl
Algorithm Hash digest
SHA256 0a56ee110d10b8fbb1f94db5372d26d622961d7d2badec49a025682ffde39be0
MD5 c8af01af6140e10de4eca18520946034
BLAKE2b-256 b46eb748ad7d4032d28fd538ceb5008a9f1e4c89231082d3c482f12a672a26e2

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