Implement Date-reuploading classifier in Qiskit Machine Learning

[a-matsuo]

Description

Data re-uploading is a recently proposed idea of quantum neural network, which uses a quantum circuit with a series of data re-uploading and processing layers. Unlike the conventional quantum circuit of quantum neural network, it has multiple layers of re-uploading input data. In this project, we will implement the data re-uploading quantum neural network in Qiskit Machine Learning. The goal of this project is to write code and create a pull request.

Data-reuploading classifier tutorial.

Figure from Pérez-Salinas et al. (2019)

Deliverables

Code and a Pull Request

Mentors details

• Mentor 1
  • Name: Atsushi Matsuo
  • GitHub ID: a-matsuo
  • What they do: Qiskit Application core developer

Number of mentees

1

Type of mentees

• Mentee 1
  • Required:
  • Experience in coding Python
  • Nice to have:
  • Knowledge in quantum machine learning

[adekusar-drl]

Oh wow, you were faster than me! I did have the same paper on my mind!

[a-matsuo]

hehehe 😉

[ShivaniRajput11]

I am interested to be a part of this project .

I have understanding and experience in Quantum machine learning .I am also proficient in Python and have experience working with Qiskit.

I am eager to learn and am open to feedback and guidance.This project would be a good opportunity for me to further develop my skills and gain experience in quantum machine learning.

I look forward to the opportunity to work with you on this project.Thank you

[a-matsuo]

Hi @ShivaniRajput11, Great to hear that you're interested in being a part of this project! Your experience and skills in Quantum machine learning and proficiency in Python and Qiskit make you an ideal candidate for this project.

We are excited to have you on board for this project and look forward to working together. In the meantime, I recommend that you familiarize yourself with the project's goals and requirements by reviewing some helpful resources. You can start by going through the Data-reuploading classifier tutorial, and the Qiskit Machine Learning tutorials (1, 2).

Additionally, I recommend that you take a look at the two_layer_qnn.py file, which should provide a good basis for understanding how the Data-reuploading neural network class will look like. This will allow you to hit the ground running once we had the kick-off meeting.

If you have any questions or concerns, please don't hesitate to reach out in the Qiskit workspace in Slack or Github.

[ericardomuten]

Hi! @a-matsuo

I'm interested in the project. I had previously implemented the data reuploading classifier in Qiskit but only as a Jupyter Notebook (not a Python module). I also have implemented it as an open-source package but using Tensorflow Quantum. I have a quite deep understanding of the topic as it was my undergraduate thesis topic.

It would be interesting to try implementing this as a new Python module for Qiskit Machine Learning. I look forward to hearing back from you, thanks a lot!

[ShivaniRajput11]

@a-matsuo , Thank You for considering. Looking forward to working on this project together.

[a-matsuo]

Hi @ericardomuten , thank you for your interest in this project. While we appreciate your enthusiasm, we have already have @ShivaniRajput11 as our mentee for this project. However, we encourage collaboration among advocates. Would you guys, @ShivaniRajput11 and @ericardomuten, be interested in collaborating on this project? We believe that working together would be a great way for both of you to learn and grow. Let us know your thoughts on this.

[ericardomuten]

Hi @a-matsuo

Yeah, I think that would be ideal. Working together might make the code finish faster. I have reached out to Shivani on Slack. Thanks!

[ericardomuten]

Dear @GemmaDawson, do you mind also assigning me to this issue? The three of us talked about the project and we have started to work together on it. Thanks!

[ShivaniRajput11]

Slide Deck Checkpoint1: QAMP_Project Implement Date-reuploading classifier in Qiskit Machine Learning3.pdf

[ShivaniRajput11]

Slide Deck Checkpoint2: QAMP_Project'23 #3 CHECKPOINT-2.pdf