Agent Skills: PyZX Simplifier

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

circuit-designID: a5c-ai/babysitter/pyzx-simplifier

Install this agent skill to your local

pnpm dlx add-skill https://github.com/a5c-ai/babysitter/tree/HEAD/library/specializations/domains/science/quantum-computing/skills/pyzx-simplifier

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library/specializations/domains/science/quantum-computing/skills/pyzx-simplifier/SKILL.md

Skill Metadata

Name
pyzx-simplifier
Description
ZX-calculus based circuit simplification skill for advanced quantum circuit optimization

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