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tensor-network-simulator

// Tensor network-based simulation skill for large circuit approximation

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updated:March 4, 2026
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SKILL.md Frontmatter
nametensor-network-simulator
descriptionTensor network-based simulation skill for large circuit approximation
allowed-toolsBash,Read,Write,Edit,Glob,Grep
metadata[object Object]

Tensor Network Simulator

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

  1. Structure Analysis: Identify circuit entanglement structure
  2. Method Selection: Choose MPS, PEPS, or general tensor network
  3. Bond Dimension: Set appropriate truncation threshold
  4. Contraction Ordering: Optimize contraction path for efficiency
  5. Error Monitoring: Track approximation errors through simulation

Tools/Libraries

  • TensorNetwork
  • quimb
  • ITensor
  • cuTensorNet (NVIDIA cuQuantum)
  • cotengra