4 papers
FAlCon: A unified framework for algorithmic control of quantum dot devices
Tyler J. Kovach, Daniel Schug, Zach D. Merino +3
As spin-based quantum systems scale, their setup and control complexity increase sharply. In semiconductor quantum dot (QD) experiments, device-to-device variability, heterogeneous…
Bootstrapping, autonomous testing, and initialization system for Si/SiGe multi-quantum-dot devices
Tyler J. Kovach, Daniel Schug, M. A. Wolfe +7
Semiconductor quantum dot (QD) devices have become central to advancements in spin-based quantum computing. However, the increasing complexity of modern QD devices makes calibratio…
Benchmarking machine learning models for multi-class state recognition in double quantum dot data
Valeria DÃaz Moreno, Ryan P Khalili, Daniel Schug +2
Semiconductor quantum dots (QDs) are a leading platform for scalable quantum processors. However, scaling to large arrays requires reliable, automated tuning strategies for devices…
Automation of Quantum Dot Measurement Analysis via Explainable Machine Learning
Daniel Schug, Tyler J. Kovach, M. A. Wolfe +6
The rapid development of quantum dot (QD) devices for quantum computing has necessitated more efficient and automated methods for device characterization and tuning. This work demo…