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PennyLane Quantum ML

A skill for building, differentiating and training quantum circuits with PennyLane across IBM, Google, Rigetti and IonQ backends.

Dev & CodingAdvanced33,0303,248AI score 8/10Last updated: Aug 9, 2026

What it does

Guides Claude in writing PennyLane 0.45 code: constructing quantum circuits, computing gradients automatically (parameter-shift, backprop, adjoint) and optimizing parameters. It covers variational algorithms (VQE, QAOA), quantum neural networks, hybrid models with PyTorch/JAX, and switching between simulators and real hardware (Qiskit/IBM, Braket, Cirq, Rigetti, IonQ). Deeper material lives in a references/ folder split by topic: circuits, QML, quantum chemistry, devices, optimization and advanced features.

Who it's for

  • Researchers and grad students working on variational quantum algorithms or QML
  • Computational chemists building molecular Hamiltonians, VQE runs and dissociation curves
  • Developers who want to benchmark the same circuit across multiple quantum backends

Examples

  1. "Write a VQE script for the H2 ground-state energy" → Hamiltonian construction, UCCSD ansatz and an Adam optimization loop
  2. "Build a 4-qubit variational classifier using AngleEmbedding" → QNN with StronglyEntanglingLayers plus a training loop
  3. "Move my simulator-tested circuit to an IBM backend and use parameter-shift gradients" → device swap and hardware-safe differentiation setup

· · · Install guide · · ·

Install in the Claude app (no terminal)
  1. Download the ZIP with the button below.
  2. In Claude, open Settings → Capabilities and turn on 'Code execution and file creation'. (one time)
  3. Go to Customize → Skills → + → 'Upload a skill' and upload the ZIP.
Download ZIP
Install in Claude Code

Let Claude do it — paste this into Claude Code

Install the skill I found on Claude Skill Mart.
Copy the skills/pennylane folder from the GitHub repo K-Dense-AI/scientific-agent-skills into my ~/.claude/skills/pennylane/.
When it's done, tell me in one line what this skill can do.

Install with a command instead

git clone https://github.com/K-Dense-AI/scientific-agent-skills.git && mkdir -p ~/.claude/skills && cp -r scientific-agent-skills/skills/pennylane ~/.claude/skills/

This is a third-party skill. Check the source repository before installing.

  1. Open a terminal and confirm Python 3.11+ and git are installed.
  2. Clone the repository: git clone https://github.com/K-Dense-AI/scientific-agent-skills.git
  3. Create the skills directory: mkdir -p ~/.claude/skills
  4. Copy the whole skill folder so the references/ docs come with it: cp -r scientific-agent-skills/skills/pennylane ~/.claude/skills/
  5. Install the library in your environment: uv pip install "pennylane==0.45.0", plus provider plugins such as pennylane-qiskit if you target hardware.
  6. Restart Claude Code and try a prompt like "use PennyLane to write a VQE example" to confirm the skill activates.