pennylane - Quantum machine learning library with auto-differentiation.
PennyLane enables building, differentiating, and optimizing hybrid quantum-classical models across simulators and quantum hardware backends.
Tags
Updated: 2026-09-20Capabilities
Typical Inputs
Typical Outputs
What this skill does
- Construct quantum circuits
- Train hybrid quantum models
- Simulate quantum chemistry
- Execute on devices
- Optimize circuit parameters
Inputs
- Circuit parameters
- Quantum device configurations
- Classical datasets
- Molecular geometries
Outputs
- Expectation values
- Optimized parameters
- Molecular ground state energies
- Measurement samples
Requirements
- Python 3.11 or newer
- PennyLane package
- Hardware provider plugins