pennylane
PennyLane
Hardware-agnostic quantum ML framework with automatic differentiation. Use when training quantum circuits via gradients, building hybrid quantum-classical models, or needing device portability across IBM/Google/Rigetti/IonQ. Best for variational algorithms (VQE, QAOA), quantum neural networks, and integration with PyTorch/JAX/TensorFlow. For hardware-specific optimizations use qiskit (IBM) or cirq (Google); for open quantum systems use qutip.
这页展示的是上游仓库条目，不代表已进入 SCI Skills 精选目录。
- 原始路径
- scientific-skills/pennylane
- 允许工具
- -
- 仓库版本
- 2.31.0
- 同步时间
- 2026年3月27日
条目说明
条目说明
PennyLane is a quantum computing library that enables training quantum computers like neural networks. It provides automatic differentiation of quantum circuits, device-independent programming, and seamless integration with classical machine learning frameworks.
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