This gives Claude the ability to write, simulate, and optimize quantum circuits using Google's Cirq framework. You'd reach for it when targeting Google Quantum AI hardware like Sycamore or Weber, when you need fine-grained noise modeling, or when running characterization experiments like randomized benchmarking. It covers the full stack from basic circuit construction through parameterized gates, noisy simulation, hardware compilation, and variational algorithms. The skill includes integration patterns for Google Quantum Engine, IonQ, Azure Quantum, and other providers. If you're working with IBM hardware you want qiskit instead, and if you need automatic differentiation for quantum ML, pennylane is the better fit.
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- last updated
- Aug 21, 2026
Install
$ npx -y skills add k-dense-ai/scientific-agent-skills --skill cirq --agent claude-codeInstalls into .claude/skills of the current project.
Files
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.
uv pip install "cirq-core==1.7.0"
# Optional OpenQASM import dependency
uv pip install ply
For hardware integration (pin matching versions for reproducibility):
# Google Quantum Engine (requires approved GCP project access)
uv pip install "cirq-google==1.7.0"
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- Repository
- github.com/k-dense-ai/scientific-agent-skills
- Categories
- AI & Agent Building, Data Science & ML, Design & UI/UX, Game Development
- First seen
- Jun 3, 2026
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