This repository contains implementations and resources for reproducing key quantum machine learning papers, with a focus on photonic and optical quantum computing.
It is part of the main MerLin project: https://github.com/merlinquantum/merlin and complements the online documentation available at:
https://merlinquantum.ai/research/reproduced_papers.html
Each paper reproduction is designed to be accessible, well-documented, and easy to extend. Contributions are welcome!
We encourage contributions of new quantum ML paper reproductions. Please follow the guidelines below:
paper_reproduction/
├── README.md # Paper overview and results
├── implementation.py # Core implementation
├── notebook.ipynb # Interactive exploration of key concepts
├── data/ # Datasets and preprocessing
├── results/ # Figures and analysis
└── tests/ # Validation tests
- Propose the paper in our GitHub Discussions
- Implement using the repository tools, following the structure above
- Validate results against the original paper
- Document in Jupyter notebook format
- Submit a pull request with the complete reproduction folder
- High-impact quantum ML papers (>50 citations preferred)
- Photonic/optical quantum computing focus
- Implementable with current repository features
- Clear experimental validation
Contributors are recognized in:
- Paper reproduction documentation
- MerLin project contributors list
- Academic citations in MerLin publications
This repository uses Ruff for consistent code formatting and linting across all paper implementations.
Check code style:
ruff check .Format code:
ruff format .Install pre-commit hooks (recommended):
pip install pre-commit
pre-commit install- Code style rules are defined in
pyproject.toml - GitHub Actions automatically check all PRs and pushes
- Pre-commit hooks run ruff automatically before commits