Python package for writing, manipulating, and running quantum circuits on quantum computers and simulators.

Features – Installation – Quick Start – Documentation – Integrations – Community – Citing Cirq – Contact

Features

Cirq provides useful abstractions for dealing with today’s noisy intermediate-scale quantum (NISQ) computers, where the details of quantum hardware are vital to achieving state-of-the-art results. Some of its features include:

• Flexible gate definitions and custom gates
• Parametrized circuits with symbolic variables
• Circuit transformation, compilation and optimization
• Hardware device modeling
• Noise modeling
• Multiple built-in quantum circuit simulators
• Integration with qsim for high-performance simulation
• Interoperability with NumPy and SciPy
• Cross-platform compatibility

Installation

Cirq supports Python version 3.10 and later, and can be used on Linux, MacOS, and Windows, as well as Google Colab. For complete installation instructions, please refer to the Install section of the Cirq documentation.

Quick Start – “Hello Qubit” Example

Here is a simple example to get you up and running with Cirq after you have installed it. Start a Python interpreter, and then type the following:

import cirq

# Pick a qubit.
qubit = cirq.GridQubit(0, 0)

# Create a circuit.
circuit = cirq.Circuit(
    cirq.X(qubit)**0.5,  # Square root of NOT.
    cirq.measure(qubit, key='m')  # Measurement.
)
print("Circuit:")
print(circuit)

# Simulate the circuit several times.
simulator = cirq.Simulator()
result = simulator.run(circuit, repetitions=20)
print("Results:")
print(result)

You should see the following output printed by Python:

Circuit:
(0, 0): ───X^0.5───M('m')───
Results:
m=11000111111011001000

Congratulations! You have run your first quantum simulation in Cirq. You can continue learning more by exploring the many Cirq tutorials described below.

Cirq Documentation

Documentation for Cirq is available in a variety of formats.

Tutorials

• Video tutorials on YouTube are an engaging way to learn Cirq.
• Jupyter notebook-based tutorials let you learn Cirq from your browser – no installation needed.
• Text-based tutorials are great when combined with a local installation of Cirq on your computer.

Reference Documentation

• Docs for the current stable release correspond to what you get with pip install cirq.
• Docs for the pre-release correspond to what you get with pip install cirq~=1.0.dev.

Examples

• The examples subdirectory of the Cirq GitHub repo has many programs illustrating the application of Cirq to everything from common textbook algorithms to more advanced methods.
• The Experiments page on the Cirq documentation site has yet more examples, from simple to advanced.

Change log

• The Cirq releases page on GitHub lists the changes in each release.

Integrations

Google Quantum AI has a suite of open-source software thats let you do more with Cirq. From high-performance simulators, to novel tools for expressing and analyzing fault-tolerant quantum algorithms, our software stack lets you develop quantum programs for a variety of applications.

Your interests	Software to explore
Large circuits and/or a lot of simulations?	qsim Stim
Quantum algorithms? Fault-tolerant quantum computing (FTQC)?	Qualtran
Quantum error correction (QEC)?	Stim
Chemistry and/or material science?	OpenFermion OpenFermion-Cirq
Quantum machine learning (QML)?	TensorFlow Quantum
Real experiments using Cirq?	ReCirq

Community

Cirq has benefited from open-source contributions by over 200 people and counting. We are dedicated to cultivating an open and inclusive community to build software for quantum computers, and have a code of conduct for our community.

Announcements

Stay on top of Cirq developments using the approach that best suits your needs:

• For releases and major announcements: sign up to the low-volume mailing list cirq-announce.
• For releases only:
  • Via GitHub notifications: configure GitHub repository notifications for the Cirq repo.
  • Via Atom/RSS from GitHub: subscribe to the GitHub Cirq releases Atom feed.
  • Via RSS from PyPI: subscribe to the PyPI Cirq releases RSS feed.

Cirq releases take place approximately every quarter.

Questions and Discussions

• Do you have questions about using Cirq? Post them to the Quantum Computing Stack Exchange and tag them with the cirq tag.
• Would you like to get more involved? Cirq Cynq is our biweekly virtual meeting of contributors to discuss everything from issues to ongoing efforts, as well as to ask questions. Join the cirq-dev Google Group to get an automatic meeting invitation.

Issues and Pull Requests

• Do you have a feature request or want to report a bug? Open an issue on GitHub to report it!
• Do you have a code contribution? Read our contribution guidelines, then open a pull request!

Citing Cirq

When publishing articles or otherwise writing about Cirq, please cite the Cirq version you use – it will help others reproduce your results. We use Zenodo to preserve releases. The following links let you download the bibliographic record for the latest stable release of Cirq in various popular formats:

        

For formatted citations and records in other formats, as well as records for all releases of Cirq past and present, visit the Cirq page on Zenodo.

Contact

For any questions or concerns not addressed here, please email [email protected].

Disclaimer

Cirq is not an official Google product. Copyright 2019 The Cirq Developers