Quimb Tensor Network

SkillDev tools

QuTiP/quimb tensor network skill for quantum many-body simulations and entanglement analysis

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.

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 Quimb Tensor Network skill

What this skill tells your AI

The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/science/physics/skills/quimb-tensor-network/SKILL.md and read by ahel’s review.

Purpose

Provides expert guidance on tensor network simulations for quantum many-body systems, including MPS, DMRG, and entanglement analysis.

Capabilities

MPS and DMRG calculations
TEBD time evolution
Entanglement entropy computation
Quantum master equation solving
Open quantum systems dynamics
GPU-accelerated contractions

Usage Guidelines

State Representation: Use MPS for one-dimensional systems
Ground States: Run DMRG for ground state calculations
Time Evolution: Use TEBD for dynamics
Entanglement: Calculate entanglement entropy and spectra
Open Systems: Model dissipative quantum systems

Tools/Libraries

quimb
QuTiP
ITensor

Signals

GitHub stars: 2k
Forks: 112
Last commit: Sep 2026

Advanced

Item type: skill
Key: quimb-tensor-network
Source: github.com/a5c-ai/babysitter

github.com/a5c-ai/babysitter