Welcome to LLY-DML WIKI

LLY-DML is part of the LILY Project and focuses on optimization parameter-based quantum circuits. It enhances the efficiency of quantum algorithms by fine-tuning parameters of quantum gates. DML stands for Differentiable Machine Learning, emphasizing the use of gradient-based optimization techniques to improve the performance of quantum circuits.

LLY-DML is available on the LILY QML platform, making it accessible for researchers and developers.

For inquiries or further information, please contact: [email protected].

This wiki is structured as follows:

• Code Documentation
• Theoretical Background of DML
• Application Cases of DML
• Research Topics

Contributors

Leading

Role	Name	Links
Project Lead	Leon Kaiser	ORCID, GitHub
Inquiries and Management	Raul Nieli	Email
Supporting Contributors	Eileen Kühn	GitHub, KIT Profile
Supporting Contributors	Max Kühn	GitHub

Other Contributors

Contributor	Role	Contribution
Clausia	Support in Development	General development support
MrGilli	Support in Quplexity DML Version	Quplexity DML Development
Supercabb	Support in Code Development	Codebase contributions
Userlenn	Support in Code Development	Codebase contributions