QML-for-Conspicuity-Detection-in-Production

Womanium Quantum+AI 2024 Projects

Please review the participation guidelines here before starting the project.

Do NOT delete/ edit the format of this read.me file.

Include all necessary information only as per the given format.

Project Information:

Team Size:

• Maximum team size = 2
• While individual participation is also welcome, we highly recommend team participation :)

Eligibility:

• All nationalities, genders, and age groups are welcome to participate in the projects.
• All team participants must be enrolled in Womanium Quantum+AI 2024.
• Everyone is eligible to participate in this project and win Womanium grants.
• All successful project submissions earn the Womanium Project Certificate.
• Best participants win Womanium QSL fellowships with Fraunhofer ITWM. Please review the eligibility criteria for QSL fellowships in the project description below.

Project Description:

• Click here to view the project description.
• YouTube recording of the project description - link

Project Submission:

All information in this section will be considered for project submission and judging.

Ensure your repository is public and submitted by August 9, 2024, 23:59pm US ET.

Ensure your repository does not contain any personal or team tokens/access information to access backends. Ensure your repository does not contain any third-party intellectual property (logos, company names, copied literature, or code). Any resources used must be open source or appropriately referenced.

Team Information:

Team Member 1:

• Full Name: La Wun Nannda
• Womanium Program Enrollment ID (see Welcome Email, format- WQ24-xxxxxxxxxxxxxxx): WQ24-G58ujBYY1tLxtO3

Team Member 2:

• Full Name: Chit Zin Win
• Womanium Program Enrollment ID (see Welcome Email, format- WQ24-xxxxxxxxxxxxxxx): WQ24-VDCiq5LYVoOJjeJ

Project Solution:

With limited internet access and time, we finished three of the five project deliverables:

1. We finish the codebook sections “Introduction to Quantum Computing”, “Single-Qubit Gates” and “Circuits with Many Qubits” from the PennyLane Codebook. The repository contains the corresponding notebooks for this task. They are named with an initial of Pennylane I... .ipynb.
2. We implement and present the usual steps of the tutorial Variational Classifier with our own words. The notebook file is named Task 2. Variational_Classifier.ipynb. Necessary data is in the directory variational_classifier/data.
3. We implement and present our steps in a notebook and comment on the important steps for the tutorial Quanvolutional Neural Networks. The notebook file is named Task 3. Quanvolutional_Neural_Networks.ipynb and the directory quanvolution contains quantum pre-processed data.

In this project, we, Myanmar Youths, reproduce the PennyLane tutorials the way we understand. In future, we hope to spread the quantum knowledge and the PennyLane library among quantum-computing enthusiasts from Myanmar. To achieve our goal, we consider to-

• create notebooks from existing tutorials,
• add our understandings to the documentation,
• translate them into the Burmese language.

However, we did not achieve our goal in time as our translation process is not finished. But this process will be continued after the project submission. All necessary code files and any additional information required to judge our project solution are included in the repository.

Project Presentation Deck:

Upload/ Link a 3min. presentation deck here.

See project presentation guidelines here