Pyzx Simplifier

ZX-calculus based circuit simplification skill for advanced quantum circuit optimization

a5c-ai Updated 1.7k repo stars

File contents

PyZX Simplifier

Purpose

Provides expert guidance on ZX-calculus based circuit simplification, enabling powerful optimization through graphical quantum circuit representation.

Capabilities

  • ZX-diagram representation of circuits
  • Full simplification via ZX-calculus rules
  • T-count minimization
  • Clifford circuit extraction
  • Ancilla-free circuit optimization
  • Visualization of ZX-diagrams
  • Circuit-to-graph conversion
  • Equality verification

Usage Guidelines

  1. Conversion: Transform quantum circuits to ZX-diagrams for analysis
  2. Simplification: Apply ZX-calculus rewrite rules for optimization
  3. T-Minimization: Focus on T-gate reduction for fault-tolerant computing
  4. Extraction: Convert optimized ZX-diagrams back to circuits
  5. Visualization: Generate visual representations for understanding and debugging

Tools/Libraries

  • PyZX
  • ZX-calculus
  • NetworkX
  • Matplotlib

a5c-ai/babysitter/tree/main/library/specializations/domains/science/quantum-computing/skills/pyzx-simplifier commit bf8b9b071c

Frequently asked questions

npx skillmds@latest add a5c-ai/pyzx-simplifier