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PennyLane Quantum ML

A skill that guides building, training, and deploying differentiable quantum circuits with PennyLane.

Data & AnalyticsAdvanced★ 33,030⑂ 3,248AI score 8/10Last updated: Aug 9, 2026

What it does

  • Gives pinned installation commands for PennyLane 0.45 and hardware plugins (IBM, Braket, Cirq, Rigetti, IonQ, Lightning, Catalyst).
  • Shows the canonical pattern for defining a QNode, applying gates and measurements, and running optimizer loops.
  • Covers common workflows: VQE for molecular ground states, QAOA, variational classifiers, and hybrid PyTorch/JAX models.
  • Lists 10 practical best practices (simulate first, parameter-shift on hardware, avoid barren plateaus, cache devices, profile with qml.specs()).
  • Points to topic-specific reference docs under references/ for circuits, QML, chemistry, devices, optimization, and advanced features.

Who it's for

  • Researchers and grad students working on quantum machine learning or variational algorithms.
  • Developers who need one codebase to run across multiple quantum hardware backends.
  • Anyone building quantum chemistry pipelines with VQE and molecular Hamiltonians.

Examples

  1. "Compute the H2 ground-state energy with a UCCSD VQE" → full script from Hamiltonian construction to the Adam optimization loop.
  2. "Build a 4-qubit angle-encoded variational classifier" → training code using AngleEmbedding and StronglyEntanglingLayers.
  3. "Move my validated circuit to IBM hardware" → switching to the qiskit.remote device and using parameter-shift gradients.

· · · Install guide · · ·

Try it now, no install

Paste this into Claude to use the skill without installing anything.

Read the instructions in this file and follow them to help me:
https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/HEAD/skills/pennylane/SKILL.md

What I want: (describe your task here)

If Claude can't open the link, open it yourself and paste the contents instead.

↓ If it works for you, download the ZIP below and install it. Then it runs on its own — no pasting each time.

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 /tmp/sas && mkdir -p ~/.claude/skills && cp -r /tmp/sas/skills/pennylane ~/.claude/skills/

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

  1. Open a terminal.
  2. Clone the repository: git clone https://github.com/K-Dense-AI/scientific-agent-skills.git
  3. Create the skills folder: mkdir -p ~/.claude/skills
  4. Copy the skill: cp -r scientific-agent-skills/skills/pennylane ~/.claude/skills/ (keep the references/ folder intact).
  5. In a Python 3.11+ environment run uv pip install "pennylane==0.45.0", plus any hardware plugin you need.
  6. Restart Claude Code and prompt something like "Write a VQE script with PennyLane" to trigger the skill.
View source on GitHub ↗License: MIT