Individual skill
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.
skills/pennylane/SKILL.md
Source commit 2d2065fb4520fa3f3f2bcf61cff26ec8b7eba4b5
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Network or broad shell
- Last checked
- Nov 10, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 56,837
- Repository last updated
- Nov 9, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- ai-scientist Repository topic
- bioinformatics Repository topic
- chemoinformatics Repository topic
- claude Repository topic
- claude-skills Repository topic
- claudecode Repository topic
- clinical-research Repository topic
- computational-biology Repository topic
- data-analysis Repository topic
- drug-discovery Repository topic
- education Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
SKILL.mdcore · 7,218 bytesSKILL.mdcore · 7,218 bytesSKILL.mdcore · 7,218 bytesSKILL.mdcore · 7,218 bytesSKILL.mdcore · 7,218 bytesreferences/advanced_features.mddoc · 7,874 bytesreferences/devices_backends.mddoc · 9,093 bytesreferences/getting_started.mddoc · 4,048 bytesreferences/optimization.mddoc · 6,860 bytesreferences/quantum_chemistry.mddoc · 7,645 bytesreferences/quantum_circuits.mddoc · 5,064 bytesreferences/quantum_ml.mddoc · 6,647 bytes
Read excerpt
# PennyLane
## When to use
Use PennyLane to optimize parameterized circuits, build hybrid quantum-classical
models, estimate molecular energies, or compare a validated circuit across devices.
This skill targets stable PennyLane 0.45.1. The local examples use small synthetic
systems; successful optimization does not establish quantum advantage, molecular
accuracy, or hardware fidelity.
## Installation
Create a dedicated environment; provider plugins and compiler dependencies should
be resolved separately from unrelated scientific packages: