quantumlib/Cirq

Health v2 · maintenance only

Adoption not part of the score

5053 stars · 1262 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Cirq is a Python framework from Google Quantum AI for writing, manipulating, optimizing, and simulating quantum circuits, with a focus on NISQ (noisy intermediate-scale quantum) hardware. It includes built-in simulators, noise and device modeling, circuit compilation, and integration with the high-performance qsim simulator.

Use cases

• build and simulate quantum circuits in python
• simulate noisy NISQ quantum circuits
• compile and optimize quantum circuits for real hardware
• model quantum device hardware constraints and noise
• run quantum algorithms on simulators before executing on quantum computers
• learn quantum computing with a python sdk

When to choose

• you need fine-grained control over qubit placement and hardware-aware circuit design
• you target Google quantum hardware or want hardware-level noise modeling
• you need high-performance circuit simulation via qsim integration

When to avoid

• you want a higher-level abstraction-focused framework like Qiskit's ecosystem breadth
• you need fault-tolerant quantum error correction tooling rather than NISQ circuits
• your project is not Python-based

Facets

framework · maturity stable

simulation sdk machine-learning quantum-computing simulation programming-languages python windows cross-platform quantum-circuits nisq quantum-simulation quantum-programming google-quantum-ai qsim algorithms linux macos

Member repositories

For agents

markdown · JSON · MCP: product_card(name="quantumlib/Cirq")