https://github.com/rigetti/forest-benchmarking

A library for quantum characterization, verification, validation (QCVV), and benchmarking using pyQuil.
https://github.com/rigetti/forest-benchmarking

benchmarking forest qcvv quantum-computing tomography

Last synced: 5 days ago
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A library for quantum characterization, verification, validation (QCVV), and benchmarking using pyQuil.

• Host: GitHub
• URL: https://github.com/rigetti/forest-benchmarking
• Owner: rigetti
• License: apache-2.0
• Created: 2018-12-17T19:53:19.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2024-10-18T16:38:52.000Z (3 months ago)
• Last Synced: 2025-01-11T22:08:20.923Z (12 days ago)
• Topics: benchmarking, forest, qcvv, quantum-computing, tomography
• Language: Python
• Homepage:
• Size: 11.8 MB
• Stars: 54
• Watchers: 14
• Forks: 22
• Open Issues: 41
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • Contributing: .github/CONTRIBUTING.md
  • License: LICENSE
  • Code of conduct: .github/CODE_OF_CONDUCT.md
  • Codeowners: .github/CODEOWNERS

Awesome Lists containing this project

README

        
Forest Benchmarking: QCVV using PyQuil

======================================

[![pypi version](https://img.shields.io/pypi/v/forest-benchmarking)](https://pypi.org/project/forest-benchmarking/)

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3455847.svg)](https://doi.org/10.5281/zenodo.3455847)

[![slack workspace](https://img.shields.io/badge/slack-rigetti--forest-812f82.svg?)](https://join.slack.com/t/rigetti-forest/shared_invite/enQtNTUyNTE1ODg3MzE2LWExZWU5OTE4YTJhMmE2NGNjMThjOTM1MjlkYTA5ZmUxNTJlOTVmMWE0YjA3Y2M2YmQzNTZhNTBlMTYyODRjMzA)

A library for quantum characterization, verification, validation (QCVV), and benchmarking using [pyQuil](https://github.com/rigetti/pyquil).

Installation

------------

`forest-benchmarking` can be installed from source or via the Python package manager PyPI.

**Note**: NumPy and SciPy must be pre-installed for installation to be successful, due to cvxpy.

### Source

```bash

git clone https://github.com/rigetti/forest-benchmarking.git

cd forest-benchmarking/

pip install numpy scipy

pip install -e .

```

### PyPI

```bash

pip install numpy scipy

pip install forest-benchmarking

```

Library Philosophy

------------------

The core philosophy of `forest-benchmarking` is to separate:

* Experiment design and or generation

* Data collection

* Data analysis

* Data visualisation

We ask that code contributed to this repository respect this separation.

We also ask that an example of how to use your contributed code is placed

in the `/examples/` directory along with the standard documentation found in `/docs/`.

Testing

-------

The unit tests can be run locally using `pytest`, but beware that the test dependencies

must be installed beforehand using `pip install -r requirements.txt`.

Disclaimer

----------

This package is currently in alpha (v0.x), and therefore you should not expect that APIs

will necessarily be stable between releases. Code that depends on this package in its current

state is very likely to break when the package version changes, so we encourage you to pin

the version you use, and update it consciously when necessary.

Citation

--------

If you use Forest Benchmarking, please cite it via the [BibTeX file](forest-benchmarking.bib).