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@ARTICLE{Hader:1005435,
      author       = {Hader, Fabian and Vogelbruch, Jan and Humpohl, Simon and
                      Hangleiter, Tobias and Eguzo, Chimezie and Heinen, Stefan
                      and Meyer, Stefanie and van Waasen, Stefan},
      title        = {{O}n {N}oise-{S}ensitive {A}utomatic {T}uning of
                      {G}ate-{D}efined {S}ensor {D}ots},
      journal      = {IEEE transactions on quantum engineering},
      volume       = {4},
      issn         = {2689-1808},
      address      = {New York, NY},
      publisher    = {IEEE},
      reportid     = {FZJ-2023-01472},
      pages        = {5500218},
      year         = {2023},
      abstract     = {In gate-defined quantum dot systems, the conductance change
                      of electrostatically coupled sensor dots allows the
                      observation of the quantum dots' charge and spin states.
                      Therefore, the sensor dots must be optimally sensitive to
                      changes in its electrostatic environment. A series of
                      conductance measurements varying the two sensor-dot-forming
                      barrier gate voltages serve to tune the dot into a
                      corresponding operating regime. In this paper, we analyze
                      the noise characteristics of the measured data and define a
                      criterion to identify continuous regions with a sufficient
                      signal-gradient-to-noise ratio. Hence, accurate noise
                      estimation is required when identifying the optimal
                      operating regime. Therefore, we evaluate several existing
                      noise estimators, modify them for 1D data, optimize their
                      parameters, and analyze their quality based on simulated
                      data. The estimator of Chen et al. [1] turns out to be best
                      suited for our application concerning minimally scattering
                      results. Furthermore, using this estimator in an algorithm
                      for flank-of-interest classification in measured data shows
                      the relevance and applicability of our approach.},
      cin          = {ZEA-2 / PGI-11},
      ddc          = {621.3},
      cid          = {I:(DE-Juel1)ZEA-2-20090406 / I:(DE-Juel1)PGI-11-20170113},
      pnm          = {5223 - Quantum-Computer Control Systems and Cryoelectronics
                      (POF4-522) / 5221 - Advanced Solid-State Qubits and Qubit
                      Systems (POF4-522)},
      pid          = {G:(DE-HGF)POF4-5223 / G:(DE-HGF)POF4-5221},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:001363356900001},
      doi          = {10.1109/TQE.2023.3255743},
      url          = {https://juser.fz-juelich.de/record/1005435},
}