Skip to main content

Qibo's quantum calibration, characterization and validation module.

Project description

Qibocal

codecov PyPI - Version PyPI - Python Version

Qibocal provides Quantum Characterization Validation and Verification protocols using Qibo and Qibolab.

Qibocal key features:

  • Automatization of calibration protocols.

  • Declarative inputs using runcard.

  • Generation of a report.

Documentation

docs

Qibocal documentation is available here.

Installation

The package can be installed by source:

git clone https://github.com/qiboteam/qibocal.git
cd qibocal
pip install .

Developer instructions

For development make sure to install the package using poetry and to install the pre-commit hooks:

git clone https://github.com/qiboteam/qibocal.git
cd qibocal
poetry install
pre-commit install

Minimal working example

This section shows the steps to perform a resonator spectroscopy with Qibocal.

Write a runcard

A runcard contains all the essential information to run a specific task. For our purposes, we can use the following:

platform: tii1q

targets: [0]

- id: resonator spectroscopy high power
  operation: resonator_spectroscopy
  parameters:
    freq_width: 10_000_000
    freq_step: 500_000
    amplitude: 0.4
    power_level: high
    nshots: 1024
    relaxation_time: 5_000

How to run protocols

To run the protocols specified in the runcard, Qibocal uses the qq auto command

qq auto <runcard> -o <output_folder>

if <output_folder> is specified, the results will be saved in it, otherwise qq will automatically create a default folder containing the current date and the username.

Uploading reports to server

In order to upload the report to a centralized server, send to the server administrators your public ssh key (from the machine(s) you are planning to upload the report) and then use the qq upload <output_folder> command. This program will upload your report to the server and generate an unique URL.

Contributing

Contributions, issues and feature requests are welcome! Feel free to check GitHub issues

Citation policy

arXiv DOI

If you use the package please refer to the documentation for citation instructions

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

qibocal-0.0.9.tar.gz (126.2 kB view details)

Uploaded Source

Built Distribution

qibocal-0.0.9-py3-none-any.whl (226.4 kB view details)

Uploaded Python 3

File details

Details for the file qibocal-0.0.9.tar.gz.

File metadata

  • Download URL: qibocal-0.0.9.tar.gz
  • Upload date:
  • Size: 126.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.12.3

File hashes

Hashes for qibocal-0.0.9.tar.gz
Algorithm Hash digest
SHA256 13ba5a4b96aeb86fea5386454e2355b3209a07deeae9374e8ab6293bc1631417
MD5 2e6c5c7d46452d4642cdb8340f79788d
BLAKE2b-256 ed25668eb7ab91567ffcede8900a744435cdd3c037711c89774bd62bfbed2b19

See more details on using hashes here.

File details

Details for the file qibocal-0.0.9-py3-none-any.whl.

File metadata

  • Download URL: qibocal-0.0.9-py3-none-any.whl
  • Upload date:
  • Size: 226.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.12.3

File hashes

Hashes for qibocal-0.0.9-py3-none-any.whl
Algorithm Hash digest
SHA256 cbedf9ba3395917acd6e1105544ed8610cac689e5c6036f106e76d2acff0d79f
MD5 99f8f4cb3b97092b347e7ce71e159405
BLAKE2b-256 7d38817cfe930d8f7a2bbe4421759ab4ad3409e52763553716dea3319e9fef93

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