This workshop, co-hosted with the University of California Los Angeles (UCLA) will convene stakeholders from industry, academia, and the government interested in the research and development of semiconductor quantum computing technologies. Topics to be discussed include opportunities for research and development of tuning, characterization, and control methods for semiconductor quantum dot devices, the need for facilitating interaction and collaboration between the stakeholders to build a large open-access database of experimental and simulated data for benchmarking new machine learning algorithms, determining key performance metrics for the various aspects of the tuning, characterizing, and controlling of quantum dot devices, and identifying barriers to near-term and future applications of the auto-tuning methods. Furthermore, this workshop will provide a discussion place to consider methods of collaboration in a neutral setting and future roadmap development for methods for tuning large-scale devices.

Who Should Attend

Stakeholders from industry, academia, and government who are engaged in research on all aspects of automating semiconductor-based quantum computing technologies, including but not limited to:

• Availability and sharing of experimental datasets
• Frontiers of automation
• Simulation of quantum dot systems
• Closing the loop through digital twins
• Pushing to the edge: automation in hardware

For more information about AQD: Advances in Automation of Quantum Dot Devices Control, please visit https://qdcontrol.github.io/

Created August 19, 2025, Updated August 25, 2025