🗃️ Add component "PyTeNet" from Issue #159

[github-actions]

Closes #159. This PR was automatically generated.

---

Summary:

title: PyTeNet
languages:
  - Python
links:
  docs: https://pytenet.readthedocs.io
  github: https://github.com/cmendl/pytenet
  releases: https://pypi.org/project/pytenet/
maintainers:
  - TUM-QC
---

**PyTeNet** is a didactic Python implementation of quantum tensor network operations and simulations within the matrix product state framework.

Features include matrix product state and operator classes, constructing common Hamiltonians as MPOs, converting arbitrary operator chains to MPOs, TDVP time evolution, DMRG algorithm, and built-in support for additive quantum numbers.

[github-actions]

PR Preview Action v1.8.1
🚀 View preview at https://Munich-Quantum-Software-Stack.github.io/Component-Catalog/pr-preview/pr-160/
Built to branch gh-pages at 2026-08-13 08:23 UTC. Preview will be ready when the GitHub Pages deployment is complete.

[DRovara]

Thank you for adding the component, @cmendl. I'm sorry for the delay, but I finally managed to look at the PR. I just have one minor comment that would need fixing - probably the same thing applies to your other PR too. Thanks a lot!

[DRovara]

We typically only have single-paragraph summaries of a couple of lines, so it would likely be best to also apply that here for consistency reasons. One potential suggestion (but feel free to write up your own if you also want to include the features in more detail):

Suggested change

	**PyTeNet** is a didactic Python implementation of quantum tensor network operations and simulations
	within the matrix product state framework.
	Features include matrix product state and operator classes, constructing common Hamiltonians as
	MPOs, converting arbitrary operator chains to MPOs, TDVP time evolution, DMRG algorithm, and
	built-in support for additive quantum numbers.
	A didactic Python implementation of quantum tensor network operations and simulations
	within the matrix product state framework.

[cmendl]

Thanks! Here is a suggestion for a single-paragraph summary:

A didactic Python implementation of quantum tensor network operations and simulations within the matrix product state framework. It features conversion of arbitrary operator chains to MPOs, the DMRG algorithm, and TDVP time evolution.

[DRovara]

Great, thanks a lot! I've updated the PR and I'm letting the preview build right now. If it looks good, I'll merge it in. (Same goes for the other PR)