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@INPROCEEDINGS{Hader:1047274,
      author       = {Hader, Fabian and Fuchs, Fabian and Fleitmann, Sarah and
                      Havemann, Karin and Scherer, Benedikt and Vogelbruch,
                      Jan-Friedrich and Humpohl, Simon and Hangleiter, Tobias and
                      Huckemann, Till and Geck, Lotte and van Waasen, Stefan},
      title        = {{T}owards {S}calable {R}obust {C}harge {T}ransition
                      {D}etection for {Q}uantum {D}ot {D}evices},
      reportid     = {FZJ-2025-04195},
      year         = {2025},
      abstract     = {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).},
      month         = {Oct},
      date          = {2025-10-05},
      organization  = {Advances in Automation of Quantum Dot
                       Devices Control, Los Angeles (USA), 5
                       Oct 2025 - 5 Oct 2025},
      subtyp        = {After Call},
      cin          = {PGI-4},
      cid          = {I:(DE-Juel1)PGI-4-20110106},
      pnm          = {5223 - Quantum-Computer Control Systems and Cryoelectronics
                      (POF4-522)},
      pid          = {G:(DE-HGF)POF4-5223},
      typ          = {PUB:(DE-HGF)6},
      url          = {https://juser.fz-juelich.de/record/1047274},
}