[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

---

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

[CatalinaAlbornoz]

Awesome @DennisWayo !

I'll forward your submission to our team for them to review.

Unfortunately we cannot add images to the cards. However, you could add it to the top of the readme so that it's highly visible when people visit your repo.

We'll get back to you soon with next steps!

[DennisWayo]

Dear @CatalinaAlbornoz,

Thank you very much for the update, I truly appreciate it. I look forward to the review and the next steps.

I will also add a figure to the repository to make it more visible.

[drdren]

Hi @DennisWayo , thanks for providing a community demo! I took a quick look and it seems good to me. However, I will review it in more detail next week. If things go well, then we will add a card to our community demo page and advertise it. Are you fine with us tagging your Twitter and/or LinkedIn handles in our advertising?

Thanks, @CatalinaAlbornoz, for bringing this to my attention.

[DennisWayo]

Dear @drdren

Thanks for reaching out. I don't mind at all; whether LinkedIn or X, I am fine with it.

[drdren]

Hello @DennisWayo, I examined your demo and it looks great! You might want to add a requirements.txt or a brief note that the user only needs to install pennylane to run the code. Also, you could consider using the symbol for alpha in notebook 2, rather than spelling out alpha.

Otherwise, could you distinguish GKP error correction from 'ordinary' error correction in the abstract?

[DennisWayo]

Dear @drdren,

Thank you for the review. I have now updated the repo for your kind reference.

Abstract
This five-part demo series introduces GKP-based quantum error correction in photonic systems from a software perspective using PennyLane. Unlike ordinary qubit-level error correction, where syndrome extraction and recovery act directly on qubits, the GKP framing starts from bosonic oscillator noise and studies how correction appears at the logical-circuit layer as reduced effective logical noise. The series progresses from single-qubit logical coherence under effective noise to channel comparisons, multi-qubit Bell/GHZ behavior, and an interactive playground.

[drdren]

Hi @DennisWayo! Thanks for that! I have made a card for your demo, which you can check out in our community demos section: https://pennylane.ai/qml/demos_community. I will organise the promotion of your demo through LinkedIn, X/Twitter, Discord, and Slack with your LinkedIn and X/Twitter handles tagged.

I am aiming to have those marketed by next week (week of the 20th of April); I will let you know the date soon! Feel free to share those marketing links when they come through.

Thanks again for your wonderful community demo!

cc: @CatalinaAlbornoz

[DennisWayo]

Oh mine! Thank you so much, @drdren, I really appreciate the support.

And thank you @CatalinaAlbornoz for your guidance and mentorship throughout this process.

It’s exciting to see the demo now live on the community page. I look forward to sharing the promotion when it goes out. Thanks again to the PennyLane team!🔥

[CatalinaAlbornoz]

Congrats to you on this demo @DennisWayo ! 🥳

And kudos to @drdren for leading the review and publication process! 🙌

[drdren]

Hi @DennisWayo, we are set to market your demo this Wednesday, the 22nd of April 2026. Keep an eye out on PennyLane's LinkedIn, X (Twitter), Discord, and Slack!