The MerLin Research Ecosystem around the world
MerLin is part of a growing ecosystem of researchers exploring photonic quantum machine learning.
Across different institutions and research groups, MerLin is used to prototype new quantum models, benchmark hybrid architectures, and investigate the capabilities of photonic quantum circuits for machine learning tasks.
The works highlighted on this page were developed independently by the research community using MerLin and Quandela platforms. They illustrate how a shared experimental framework can support open benchmarking, reproducibility, and peer validation of quantum machine learning results.
As new contributions emerge, this ecosystem continues to grow, providing a common foundation for collaborative exploration of photonic QML.
Community Highlights
Photonic Quantum-Accelerated Machine Learning
Second paper using the Boson-Sampling-based quantum reservoir architecture, with a focus on benchmarking and comparing the performance of the quantum reservoir to classical machine learning models on a variety of datasets.
Experimental multi-center validation of a radiomics-based photonic quantum precision medicine architecture for lesion-level prediction of anti-PD-1 response in non-small cell lung cancer
Preprint study using MerLin to test the external validity of radiomics-based photonic quantum architectures using an evidence-based, statistically significant reduced feature space
Get Listed
If you used MerLin in your research and would like your work listed here, feel free to contact us at merlin@quandela.com ! We would be happy to include your work in this growing ecosystem and share it with the community.