Qiskit Experiments
Qiskit Experiments is a repository that builds tools for building, running, and analyzing experiments on noisy quantum computers using Qiskit.
To learn more about the package, you can see the most up-to-date documentation corresponding to the main branch of this repository or the documentation for the latest stable release.
Contribution Guidelines
If you'd like to contribute to Qiskit Experiments, please take a look at our contribution guidelines. This project adheres to Qiskit's code of conduct. By participating, you are expected to uphold this code.
We use GitHub issues for tracking requests and bugs. Please join the Qiskit Slack community and use the #experiments channel for discussion and simple questions. For questions that are more suited for a forum we use the Qiskit tag in Stack Exchange.
Authors and Citation
Qiskit Experiments is the work of many people who contribute to the project at different levels. If you use Qiskit Experiments, please cite our paper as per the included citation file.
License
Release files for qiskit-experiments 0.14.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| qiskit_experiments-0.14.2.tar.gz | 771.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| qiskit_experiments-0.14.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.4 MB
Release files / qiskit_experiments-0.14.2.tar.gz
| Download URL | qiskit_experiments-0.14.2.tar.gz |
|---|---|
| Size | 771.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
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Provenance
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Transparency logRelease files / qiskit_experiments-0.14.2-py3-none-any.whl
| Download URL | qiskit_experiments-0.14.2-py3-none-any.whl |
|---|---|
| Size | 651.4 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Aug 25, 2026.
Transparency log
