quimb-tensor-network
QuTiP/quimb tensor network skill for quantum many-body simulations and entanglement analysis
Profile →npx skills add a5c-ai/babysitter --skill quimb-tensor-network --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Quimb Tensor Network ## 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 1. **State Representation**: Use MPS for one-dimensional systems 2. **Ground States**: Run DMRG for ground state calculations 3. **Time Evolution**: Use TEBD for dynamics 4. **Entanglement**: Calculate entanglement entropy and spectra 5. **Open Systems**: Model dissipative quantum systems ## Tools/Libraries - quimb - QuTiP - ITensor
- Purpose
- Capabilities
- Usage Guidelines
- Tools/Libraries
What does the quimb-tensor-network skill do?
QuTiP/quimb tensor network skill for quantum many-body simulations and entanglement analysis
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill quimb-tensor-network --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.