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qiskit-advocate / qamp-spring-23

Qiskit advocate mentorship program (QAMP) Spring 23 cohort (April - July 2023)
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Power of data in quantum machine learning #18

Open ghellstern opened 1 year ago

ghellstern commented 1 year ago

Up to now it is not clear if quantum machine learning has an advantage compared to classical machine learning.

In paper https://www.nature.com/articles/s41467-021-22539-9 a suitable test has been proposed which checks if the data has certain geometrical properties.

Deliverable: Tutorial about the proposed method and implementation in Qiskit which allows to apply the method to different data sets.

orielkiss commented 1 year ago

FYI, this has been implemented here https://arxiv.org/abs/2206.15284.

ghellstern commented 1 year ago

Thank you for the hint! However, as far as I see, they use PennyLane and not Qiskit ...

gunchamalik commented 1 year ago

@ghellstern Please let me know the skills required for this project.

orielkiss commented 1 year ago

The authors also allow the use of different backends such as pennylane, qiskit or cirq. What i mean is that this is already implemented https://quask.readthedocs.io/en/latest/index.html so this may save you some time :)

ghellstern commented 1 year ago

@ghellstern Please let me know the skills required for this project.

It's necessary to understand the theoretical approach of the paper, to use Qiskit to implement it and the skill to present it in a pedagogical way. Maybe the project results in a paper; therefore scientific writing would be great.

zinaefchary commented 1 year ago

I have a background in QML and would be definitely interested in the project :)

grossiM commented 1 year ago

Maybe it is an interesting project but it is already implemented in https://quask.readthedocs.io/en/latest/index.html

EACMichiels commented 1 year ago

@ghellstern Dear Gerard, I have had too much workload to join from the start. But I would be eager to see the results of this work and potentially review the work done and provide feedback. Let me know if I still can help please. Eric_Michiels@be.ibm.com. +32 475 252130.