Cirq Quantum Computing with Python
技能 已验证 活跃Part of the AlterLab Academic Skills suite. 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.
To empower users to design, simulate, and run quantum circuits targeting Google Quantum AI hardware by leveraging the Cirq framework and its associated tools.
功能
- Circuit building with various qubit types and gates
- Exact and noisy quantum circuit simulation
- Parameter sweeps and analysis
- Circuit transformation and optimization
- Hardware integration with multiple providers
- Noise modeling and characterization
- Quantum experiment design and execution
- Support for advanced quantum algorithms (VQE, QAOA)
使用场景
- Targeting Google Quantum AI hardware for circuit execution
- Designing noise-aware quantum circuits
- Running quantum characterization experiments
- Simulating complex quantum circuits with various noise models
- Optimizing circuits for specific hardware backends
非目标
- Providing a graphical user interface for circuit design
- Abstracting away the low-level details of quantum computation
- Competing with general-purpose quantum programming languages
工作流
- Define quantum circuit using Cirq gates and operations.
- Optionally, add noise models or transformations.
- Simulate the circuit using Cirq simulators (state vector, density matrix, noisy).
- If targeting hardware, select qubits and optimize circuit for the device.
- Submit circuit to the chosen hardware provider (Google, IonQ, Azure, etc.).
- Analyze simulation or hardware results.
实践
- Circuit Design
- Simulation
- Hardware Execution
- Circuit Optimization
- Noise Modeling
- Experiments
先决条件
- Python 3.7+
- uv pip or pip package manager
- CIRQ and related packages (cirq-google, azure-quantum, etc. if using hardware integration)
Trust
- info:Issues AttentionThere are 2 open issues and 0 closed issues in the last 90 days, indicating low recent activity and response.
Execution
- info:Pinned dependenciesThe installation instructions use `uv pip install`, which typically handles dependency resolution but does not explicitly guarantee pinned dependencies via a lockfile in the provided source.
安装
npx skills add AlterLab-IEU/AlterLab-Academic-Skills通过 npx 运行 Vercel skills CLI(skills.sh)— 需要本地安装 Node.js,以及至少一个兼容 skills 的智能体(Claude Code、Cursor、Codex 等)。前提是仓库遵循 agentskills.io 格式。
质量评分
已验证类似扩展
Cirq
98Google 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.
Qiskit
99IBM quantum computing framework. Use when targeting IBM Quantum hardware, working with Qiskit Runtime for production workloads, or needing IBM optimization tools. Best for IBM hardware execution, quantum error mitigation, and enterprise quantum computing. For Google hardware use cirq; for gradient-based quantum ML use pennylane; for open quantum system simulations use qutip.
Qutip
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