pennylane
Builds and differentiates PennyLane quantum circuits, hybrid PyTorch or JAX models, molecular VQE and QAOA workflows. Use for variational quantum algorithms, quantum machine learning, simulator validation, and moving validated circuits to provider plugins. For hardware-specific compilation use qiskit or cirq; for open-system dynamics use qutip.
- Version
- 2.0
- License
- Apache-2.0 license
- Compatibility
- Requires Python 3.11+ and PennyLane 0.45.1 with NumPy 2+. Optional PyTorch, JAX or provider plugins need separate compatible environments. Local simulation needs no credentials; hardware requires provider credentials and network access.
Pinned to revision 68105dd992f1, so it is the text this page describes rather than whatever the author pushed since.
Pre-approved tools experimental
Experimental field. Support varies between clients, so this list is what the author declared, not what your client will enforce.
- Read
- Bash
- Python
Files
- skills/pennylane/SKILL.md
- skills/pennylane/SKILL_CN.md
- skills/pennylane/references/advanced_features.md
- skills/pennylane/references/devices_backends.md
- skills/pennylane/references/getting_started.md
- skills/pennylane/references/optimization.md
- skills/pennylane/references/quantum_chemistry.md
- skills/pennylane/references/quantum_circuits.md
- skills/pennylane/references/quantum_ml.md
Every link opens the file at its source, pinned to the revision this page describes.