Paper Implementation Project #801: A Quantum Algorithm for Solving Linear Differential Equations: Theory and Experiment

[Barath-T]

A Quantum Algorithm for Linear Differential Equations: Theory and Experiment - Paper Implementation Project.
Closes #801

PR Description

Some notes

• Please make sure that you placed the files in an appropriate folder

• And that the files have indicative names.

• Please note that Classiq runs automatic code linting, which may minorly alter some files.

  • If you're familiar with pre-commit, you may run pre-commit install, and then at each commit, your files will be altered in a similar way

[review-notebook-app]

Check out this pull request on 

See visual diffs & provide feedback on Jupyter Notebooks.

---

Powered by ReviewNB

[Barath-T]

@NadavClassiq I've updated the PR according to the new guidelines provided.

[NadavClassiq]

Hello @Barath-T!

Thanks for the effort in implementing the paper using Classiq!
I will review the notebook in the next few days.

In the meantime, please see the draft for the updated contribution guidelines here

(a few additional files might be needed, but it only involved adding one line of code, it will be add to the main branch soon)

Thanks again!

I am looking forward to diving into your work! :)

[NadavClassiq]

Hi @Barath-T!

The .ipynb and .qmod files seem to be missing the timeout value in the tests/resources/timeouts.yaml file.
Please add a value following our contribution guidelines :)
Meanwhile, I'm starting to review the notebook.

Thanks!

[NadavClassiq]

@Barath-T
Another General comment. Try thinking of someone who didn't read the paper and trying to understand why and how it works. It will make the explanation clearer and more to the point.

Please let me know after accommodating the above notes, and I will re-overview the notebook for final comments :)

Thanks again for the efforts!

[NadavClassiq]

Hi @Barath-T,

I hope you are well!
How is it going with the update? Do you have any estimated time for adapting the notebook?
Also, whenever you are done, please rebase the branch on top of the main branch (upstream); that would solve the current conflict in the timeouts.

Best luck, and please let me know if we can do anything to support you.

[Barath-T]

Thanks @NadavClassiq , Its almost done and will push it in few hours.

[NadavClassiq]

Functionally this works, but you can speed it up with an ExecutionSession so you synthesize once and then just rebind t each run.

See the docs: https://docs.classiq.io/latest/user-guide/execution/ExecutionSession/?h=execution

And the QAOA MaxCut example (same concept): https://github.com/Classiq/classiq-library/blob/main/algorithms/qaoa/maxcut/qaoa_maxcut.ipynb

Also, you’re reusing i in both loops, which makes it hard to follow. After you integrate ExecutionSession, you can pull out the inner loop into its own cell and add a short Markdown explanation.

Seems redundant:

    results = job.result()
    results = job.result_value()

Reply via ReviewNB

[Barath-T]

Hi @NadavClassiq ,

Execution parameters can figure in restricted contexts only as rotation angles in gate-level functions and as the exponent value of the power operation.

As we are building unitary i don't think we can get it as parameter.

[NadavClassiq]

Hello @Barath-T!

Thanks for the updates, excellent work! We’re almost there. I have a few last notes and look forward to the final version.

Once it’s merged, we can discuss sharing this great project with the community :)

Also, this branch has a minor conflict in the timeout file, please rebase to resolve it. While you’re at it, please shorten the timeout now that the performance optimizations are in place (after adapting my new notes, it will improve performance).

Please also press "resolve" after completing each note, or ask questions if needed.