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

qubits: [0]

- id: resonator spectroscopy high power
  priority: 0
  operation: resonator_spectroscopy
  parameters:
    freq_width: 10_000_000
    freq_step: 500_000
    amplitude: 0.4
    power_level: high
    nshots: 1024
    relaxation_time: 0

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-0.0.7.tar.gz (120.5 kB view details)

Uploaded Source

Built Distribution

qibocal-0.0.7-py3-none-any.whl (218.9 kB view details)

Uploaded Python 3

File details

Details for the file qibocal-0.0.7.tar.gz.

File metadata

  • Download URL: qibocal-0.0.7.tar.gz
  • Upload date:
  • Size: 120.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.8

File hashes

Hashes for qibocal-0.0.7.tar.gz
Algorithm Hash digest
SHA256 b88b66671797843258011bec008634860ead35dc66c83927368cc669b02fe34d
MD5 4b2653ab59f4c4eb4184ceaef8acc364
BLAKE2b-256 06df212e7ae046e1e8d05c10a3b3bd9130f9ca96d9bdf27a00ed429258c9ec04

See more details on using hashes here.

File details

Details for the file qibocal-0.0.7-py3-none-any.whl.

File metadata

  • Download URL: qibocal-0.0.7-py3-none-any.whl
  • Upload date:
  • Size: 218.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.8

File hashes

Hashes for qibocal-0.0.7-py3-none-any.whl
Algorithm Hash digest
SHA256 ec37ec5a508360ba9a45c89920e7d0a1e70acf5a96e427ce67849d5372688a7a
MD5 80588c6af53949bee5436df36fe598dc
BLAKE2b-256 2bfe0aa56e7f52d4cd5b849d46d7d37b0287a5ce1ca80aed973dc6189a26ea2d

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