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cirq

k-dense-ai/scie…t-skills

Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.

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安装命令

npx skills add https://github.com/k-dense-ai/scientific-agent-skills --skill cirq

SKILL.md

Cirq - Quantum Computing with Python

Cirq is Google Quantum AI's open-source framework for designing, simulating, and running quantum circuits on quantum computers and simulators.

When to Use This Skill

Use this skill when:

  • Building, simulating, or optimizing NISQ circuits in Python
  • Running jobs on Google Quantum AI processors (via cirq-google) or partner backends (IonQ, Azure Quantum, AQT, Pasqal)
  • Modeling noise, compiling to hardware gatesets, or designing characterization experiments
  • Using parameter sweeps, transformers, or the ReCirq experiment patterns

For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.

Installation

Examples target Cirq 1.7.0 on Python 3.11+. Keep Cirq vendor packages on the matching release; independently versioned integrations such as Azure Quantum need their own compatibility check.

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