kwant-quantum-transport
Kwant quantum transport skill for mesoscopic physics, scattering matrix calculations, and nanostructure modeling
Profile →npx skills add a5c-ai/babysitter --skill kwant-quantum-transport --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.
# Kwant Quantum Transport ## Purpose Provides expert guidance on Kwant quantum transport calculations for mesoscopic systems, including scattering matrix computations and nanostructure modeling. ## Capabilities - System builder for arbitrary geometries - Scattering matrix computation - Landauer-Buttiker formalism - Tight-binding Hamiltonian construction - Band structure visualization - Parallel transport calculations ## Usage Guidelines 1. **System Definition**: Build systems with leads and scattering regions 2. **Hamiltonians**: Define tight-binding Hamiltonians 3. **Scattering**: Compute scattering matrices and conductance 4. **Band Structure**: Calculate and visualize band structures 5. **Parallelization**: Use parallel computing for large systems ## Tools/Libraries - Kwant - NumPy - SciPy
- Purpose
- Capabilities
- Usage Guidelines
- Tools/Libraries
What does the kwant-quantum-transport skill do?
Kwant quantum transport skill for mesoscopic physics, scattering matrix calculations, and nanostructure modeling
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill kwant-quantum-transport --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.