%0 Conference Paper
%A Hader, Fabian
%A Fuchs, Fabian
%A Fleitmann, Sarah
%A Havemann, Karin
%A Scherer, Benedikt
%A Vogelbruch, Jan-Friedrich
%A Humpohl, Simon
%A Hangleiter, Tobias
%A Huckemann, Till
%A Geck, Lotte
%A van Waasen, Stefan
%T Towards Scalable Robust Charge Transition Detection for Quantum Dot Devices
%M FZJ-2025-04195
%D 2025
%X Reliable detection of charge transitions in charge stability diagrams (CSDs) is a key requirement for the full automation of quantum dot device control. Performing this task directly at the cryogenic stage reduces data transfer and supports scalability. To provide the large labeled datasets required for developing and evaluating detection methods, we introduced SimCATS [1], a simulator that generates realistic CSDs including sensor responses and distortions. We optimize both traditional and machine-learning-based detection methods using simulated data and benchmark them on simulated and experimental measurements from GaAs and SiGe qubit devices. We also investigate the potential of model compression and find its performance closely tied to task complexity, which can be alleviated by sensor dot compensation. In fact, we find that sensor compensation allows machine-learning approaches to be reduced in size by up to two orders of magnitude while maintaining, or even improving, detection quality. Together with high-quality measurements, this enables robust and scalable (ray-based) charge transition detection. Finally, we estimate the cryogenic power budget for applying this approach to large-scale systems with up to one million qubits. <br>[1] F. Hader et al., "Simulation of Charge Stability Diagrams for Automated Tuning Solutions (SimCATS)", IEEE Transactions on Quantum Engineering, DOI: 10.1109/TQE.2024.3445967 (2024).
%B Advances in Automation of Quantum Dot Devices Control
%C 5 Oct 2025 - 5 Oct 2025, Los Angeles (USA)
Y2 5 Oct 2025 - 5 Oct 2025
M2 Los Angeles, USA
%F PUB:(DE-HGF)6
%9 Conference Presentation
%R 10.34734/FZJ-2025-04195
%U https://juser.fz-juelich.de/record/1047274