Tensor Network Simulator
SkillDev toolsTensor network-based simulation skill for large circuit approximation
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Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Tensor Network Simulator skill
What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/science/quantum-computing/skills/tensor-network-simulator/SKILL.md and read by ahel’s review.
Purpose
Provides expert guidance on tensor network-based quantum circuit simulation for approximate evaluation of circuits beyond state vector limits.
Capabilities
- MPS (Matrix Product State) simulation
- PEPS simulation for 2D circuits
- Contraction path optimization
- Truncation error control
- GPU-accelerated contraction
- Circuit cutting support
- Entanglement-limited approximation
- Memory-time tradeoff tuning
Usage Guidelines
- Structure Analysis: Identify circuit entanglement structure
- Method Selection: Choose MPS, PEPS, or general tensor network
- Bond Dimension: Set appropriate truncation threshold
- Contraction Ordering: Optimize contraction path for efficiency
- Error Monitoring: Track approximation errors through simulation
Tools/Libraries
- TensorNetwork
- quimb
- ITensor
- cuTensorNet (NVIDIA cuQuantum)
- cotengra
Signals
- GitHub stars
- 2k
- Forks
- 112
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
tensor-network-simulator- Source
- github.com/a5c-ai/babysitter