How to Learn Dynamics Incoherently

[DSGuala]

Title:

Learning quantum dynamics incoherently: Variational learning using classical shadows

Summary:

This demo describes how to use a parameterized quantum circuit and classical shadow measurements to reproduce an unknown quantum process.

Relevant references:

https://arxiv.org/abs/2303.12834

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If you are writing a demonstration, please answer these questions to facilitate the marketing process.

• GOALS — Why are we working on this now?

  • Promote PennyLane datasets
  • Promote the Learning Dynamics Incoherently dataset
  • Highlight and encourage dataset contributions from external contributors
  • Show PennyLane implementation of a paper

• AUDIENCE — Who is this for?

  QML researchers

• KEYWORDS — What words should be included in the marketing post?

• Which of the following types of documentation is most similar to your file? (more details here)

• [ ] Tutorial

• [ ] Demo

• [x] How-to

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Deployment Info:

• Pull Request ID: 1156
• Deployment SHA: f279cdb92f1bafbb20701943faeadd8e666a28e6 (The Deployment SHA refers to the latest commit hash the docs were built from)

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[Qottmann]

Hey @DSGuala please make sure the demo renders when tagging for review. I tried fixing it locally by providing the missing argument but then encounter other errors. The older deploy does not seem to show this new demo but only "Create an Ising Hamiltonian with random weights"

[DSGuala]

Good work @DSGuala 💪

The how-to demo gives a concise recipe for reproducing the main results from the quoted paper, that's great 👍

I left some question regarding some things that strike me as odd and where I am not sure if those were your choices or just reproducing the paper. I think in either case we should rephrase some things to make that more clear to the reader.

The demo currently misses a convincing code part that shows that the learned circuit approximates well the target circuit. I am not sure that is the case actually given the little improvement in the cost value 🤔

There were a lot of avoidable ReST vs markdown rendering issues. Please make sure to do a self-review of the rendered version to avoid that in the future 👍

Thanks for the review! Super useful comments.

Sorry for the poor review experience :disappointed: I'm aware that this demo still needs a lot of work. Unfortunately, I haven't been able to dedicate as much focus-time as I wanted to it. But I will be addressing all the review comments as soon as possible and do some troubleshooting to make sure the output clearly demonstrates that the circuit is learned.

[Qottmann]

I noticed that the paper's title and focus also is on the limitations of these procedures. Is that something we want to mention / discuss in this how-to as well?

[Qottmann]

There were merge conflicts with master which prevented building of the latest version. I made some local changes but that might mess with your poetry config. You can just reset hard to your last commit (c77df90) and then fix poetry with a new lock from your environment.

Please make sure to review the last commit in the deployment (and make sure there is a deployment in the first place) when requesting re-review 👍