[Tutorial] GKP-based quantum error correction in photonic systems

[DennisWayo]

Summary:
This PR adds a new PennyLane demo at demonstrations_v2/tutorial_gkp_qec_photonic_s01/ with:

• demo.py (single bundled tutorial script preserving the S01–S05 narrative flow)
• metadata.json (authors, categories, references, related content, preview image placeholders)

The demo presents GKP error correction from a software-layer perspective in PennyLane and walks through:

• S01: logical coherence decay under effective depolarizing noise
• S02: correction modeled as suppression of effective logical noise
• S03: comparison across logical noise channels
• S04: multi-qubit Bell/GHZ correlation decay
• S05: interactive-style playground for parameter exploration

Relevant references:

• Gottesman, Kitaev, Preskill (2000), arXiv:quant-ph/0008040
• Menicucci (2014), Phys. Rev. Lett. 112, 120504
• Mirrahimi et al. (2014), New J. Phys. 16, 045014
• Banić et al. (2025), Phys. Rev. A 112, 052425
• Bergholm et al. (2018), arXiv:1811.04968

Possible Drawbacks:

• Uses an effective-noise abstraction and does not include full CV/non-Gaussian GKP state simulation.
• Preview thumbnails are placeholders and may be updated during review.

Related GitHub Issues: N/A

• GOALS — Why are we working on this now?
  Provide an accessible, software-focused introduction to GKP error correction in photonic systems for PennyLane users.

• AUDIENCE — Who is this for?
  Quantum software learners, photonic-QEC beginners, and developers who want intuition for logical noise modeling in PennyLane.

• KEYWORDS — What words should be included in the marketing post?
  GKP, bosonic codes, photonic quantum computing, quantum error correction, logical noise, PennyLane.

• Which of the following types of documentation is most similar to your file?

• Tutorial
• Demo
• How-to

AI tool use disclosure
ChatGPT model support was used only for language editing and writing clarity checks. Experimental design, implementation, tuning, verification, and all technical conclusions are the author's own work and responsibility. All notebook content was reviewed by the author before submission. Any opinions, findings, conclusions, or recommendations expressed in this demo are those of the author(s) and do not necessarily reflect the views of PennyLane.

[github-actions]

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Deployed at: 2026-03-12 12:00:20 UTC

[CatalinaAlbornoz]

Hi @DennisWayo,

Thanks for your submission! The first part of the demo captures some interesting details and the graphs really help to get a picture of what's happening.

Because this is structured as a five-part series, it’s a bit of a departure from the standard PennyLane demo format. However, I noticed in your repo that you’ve already split the code into several notebooks, this actually makes it a perfect candidate for a community demo!

This route allows us to host a card on our community demos page that links directly to your repository, giving you full ownership of the series while we provide the platform and marketing via our social media channels.

If you’re up for that, please share the information below and we can get the process started!

Note: We’re looking for a human-written title and abstract to ensure the demo's unique voice shines through on our page.

---

General information

Name
Your full name (or username).

Affiliation (optional)
Your affiliation, if applicable; e.g. University, research institute, company.

Twitter (optional)
Your Twitter username, if interested; helps us advertise your demo while linking directly back to you.

LinkedIn (optional)
Your LinkedIn handle, if interested; helps us advertise your demo while linking directly back to you.

---

Demo information

Title
The title of your demo.

Abstract
A short abstract describing you demo. Try to keep it to 1-3 sentences that makes clear the goal and outcome of the demo.

Relevant links
Add a link to your demo (as a GitHub repository, Jupyter notebook, Python script, etc.) as well as links to any papers/resources used.

[DennisWayo]

Dear @catalina,

Thanks a lot for the feedback and for the community demo suggestion. I’d be happy to proceed with that route.

---

General information

Name
Dennis Wayo

Affiliation
College of Computing, Georgia Institute of Technology, Atlanta, GA 30332, USA

Twitter
https://x.com/DennisWayogh

LinkedIn
https://www.linkedin.com/in/dennis-wayo-765a38b1/

---

Demo information

Title
BosonicFlow-GKP: A five-part practical series on GKP quantum error correction in photonic systems

Abstract
This five-part demo series introduces GKP-based quantum error correction in photonic systems from a software perspective using PennyLane. It progresses from single-qubit logical coherence under effective noise to channel comparisons, multi-qubit Bell/GHZ behavior, and an interactive playground. The outcome is practical intuition for how error correction appears as reduced effective logical noise at the logical-circuit layer.

Relevant links

• Main repository: https://github.com/DennisWayo/bosonicflow-gkp
• Demo notebooks (S01-S05): https://github.com/DennisWayo/bosonicflow-gkp/tree/gkp-qec-demo/demos
• Main notebook (S01): https://github.com/DennisWayo/bosonicflow-gkp/blob/gkp-qec-demo/demos/gkp_qec_demo_01.ipynb
• Reference paper (GKP): https://arxiv.org/abs/quant-ph/0008040
• PennyLane paper: https://arxiv.org/abs/1811.04968

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If possible, could we also include one representative figure from the series on the community demo card/page?