Tensor network-based simulation skill for large circuit approximation
--- name: tensor-network-simulator-67492921c71f description: Tensor network-based simulation skill for large circuit approximation allowed-tools: - Bash - Read - Write - Edit - Glob - Grep metadata: specialization: quantum-computing domain: science category: simulation phase: 6 graph: domains: [domain:quantum-computing] specializations: [specialization:quantum-computing] skillAreas: [skill-area:physics-simulation, skill-area:mathematical-reasoning, skill-area:dynamic-programming] workflows: [workflow:experiment-design] roles: [role:computational-scientist, role:research-scientist] --- # 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--- name: tensor-network-simulator-67492921c71f description: Tensor network-based simulation skill for large circuit approximation allowed-tools: - Bash - Read - Write - Edit - Glob - Grep metadata: specialization: quantum-computing domain: science category: simulation phase: 6 graph: domains: [domain:quantum-computing] specializations: [specialization:quantum-computing] skillAreas: [skill-area:physics-simulation, skill-area:mathematical-reasoning, skill-area:dynamic-programming] workflows: [workflow:experiment-design] roles: [role:computational-scientist, role:research-scientist] --- # 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
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.