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pennylaneqldpc

Run PennyLane qLDPC tutorials covering LDPC basics, CSS construction, and Hypergraph Product validation.

30|2|Updated Apr 16, 2026
Search Tags:#css#simulation#pennylane#qldpc#hypergraph-product#tanner-graph
One-click install
npx skills add https://github.com/unitarylab/quantum-skills --skill pennylaneqldpc
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: pennylaneqldpc
Source: https://github.com/unitarylab/quantum-skills/tree/main/algorithms/quantum-error-correction
Command: npx skills add https://github.com/unitarylab/quantum-skills --skill pennylaneqldpc

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The skill helps learners understand and run a PennyLane-based qLDPC tutorial, guiding from classical LDPC basics to CSS and Hypergraph Product code construction.

Core Features & Use Cases

  • Demonstrates classical LDPC concepts (parity-check matrices, Tanner graphs) and CSS code construction.
  • Validates commutation for CSS stabilizers and constructs Hypergraph Product codes for educational demos.
  • Provides a runnable Python workflow (NumPy, NetworkX, Matplotlib, PennyLane) to visualize Tanner graphs, syndromes, and code dimensions.

Quick Start

Run the tutorial script to build and validate a small qLDPC code using Python with NumPy, NetworkX, Matplotlib, and PennyLane.

Frequently Asked Questions about pennylaneqldpc

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
What is a hypergraph product code in quantum LDPC construction?▼

A hypergraph product code is a CSS stabilizer code built by combining two classical LDPC parity-check matrices. This skill demonstrates the construction and validates commutation relations using small Python experiments with PennyLane.

How do I build and validate a qLDPC code using PennyLane?▼

You build and validate a qLDPC code by running the provided tutorial script, which constructs CSS stabilizers from LDPC matrices, checks commutation, and computes code dimensions using NumPy, NetworkX, and PennyLane.

Do I need a specific Python environment to run qLDPC tutorials with PennyLane?▼

You need Python 3.10 or higher with numpy, networkx, matplotlib, and pennylane installed. The runnable script at script/algorithm.py executes the full workflow from LDPC basics to hypergraph product validation.

How does a Tanner graph relate to LDPC parity-check matrices?▼

A Tanner graph represents the parity-check matrix of an LDPC code as a bipartite graph connecting variable and check nodes. This skill visualizes Tanner graphs and syndromes using NetworkX and Matplotlib for educational purposes.

Can I use this skill to learn CSS code construction from classical LDPC codes?▼

Yes, the skill guides you from classical LDPC concepts like parity-check matrices and Tanner graphs through CSS code construction, validating stabilizer commutation and demonstrating hypergraph product code assembly step by step.

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