quantumlib/Cirq

Python framework for creating, editing, and running Noisy Intermediate-Scale Quantum (NISQ) circuits.

What it solves

Cirq is a Python package designed to write, manipulate, and run quantum circuits on both quantum computers and simulators. It specifically addresses the challenges of Noisy Intermediate-Scale Quantum (NISQ) computers, where hardware-specific details are critical for achieving high-performance results.

How it works

Cirq provides a set of abstractions for defining quantum gates and circuits. Users can create flexible gate definitions, use symbolic variables for parameterized circuits, and apply transformations, compilation, and optimization to their circuits. The library includes built-in simulators and integrates with qsim for high-performance simulation, while maintaining interoperability with NumPy and SciPy.

Who it’s for

Quantum developers, researchers, and scientists who need to build and test quantum programs, model hardware noise, and run simulations or real experiments on quantum hardware.

Highlights

  • Hardware-Centric Design: Focused on NISQ devices, providing tools for hardware device and noise modeling.
  • Flexible Circuitry: Supports custom gates and parameterized circuits with symbolic variables.
  • C-platform Compatibility: Cross-platform support for Linux, MacOS, and Windows.
  • Extensive Ecosystem: Integrates with other Google Quantum AI tools like TensorFlow Quantum for QML, Stim for error correction, and OpenFermion for chemistry.

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