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@ARTICLE{Fleitmann:909945,
      author       = {Fleitmann, Sarah and Hader, Fabian and Vogelbruch, Jan and
                      Humpohl, Simon and Hangleiter, Tobias and Meyer, Stefanie
                      and van Waasen, Stefan},
      title        = {{N}oise {R}eduction {M}ethods for {C}harge {S}tability
                      {D}iagrams of {D}ouble {Q}uantum {D}ots},
      journal      = {IEEE transactions on quantum engineering},
      volume       = {3},
      issn         = {2689-1808},
      address      = {New York, NY},
      publisher    = {IEEE},
      reportid     = {FZJ-2022-03539},
      pages        = {2689-1808},
      year         = {2022},
      abstract     = {Operating semiconductor quantum dots as quantum bits
                      requires isolating single electrons by adjusting gate
                      voltages. The transitions of electrons to and from the dots
                      appear as a honeycomb-like pattern in recorded charge
                      stability diagrams (CSDs). Thus, detecting the pattern is
                      essential to tune a double dot, but manual tuning is
                      seriously time-consuming. However, automation of this
                      process is difficult because the transitions’ contrast is
                      often low, and noise and background disorder potential
                      shifts disturb the CSDs. Therefore, the signal-to-noise
                      ratio needs to be increased to improve the detection of the
                      line pattern. For this purpose, we evaluate a representative
                      set of edge-preserving smoothing filters and compare them
                      both quantitatively and qualitatively by suitable metrics
                      and visual assessment. We generate artificial data to use
                      full-reference metrics for the evaluation procedure and to
                      optimize the filter parameters. Based on the results of this
                      article, the methods attain a moderate to good amount of
                      noise reduction and structure improvement dependent on the
                      different CSD qualities. In conclusion, we suggest
                      introducing the block-matching and three-dimensional
                      transform-domain filter into the automated tuning processing
                      pipeline. If the data are corrupted by significant amounts
                      of random telegraph noise, the bilateral filter and the
                      rolling guidance filter are also good choices.},
      cin          = {ZEA-2},
      ddc          = {621.3},
      cid          = {I:(DE-Juel1)ZEA-2-20090406},
      pnm          = {5223 - Quantum-Computer Control Systems and Cryoelectronics
                      (POF4-522)},
      pid          = {G:(DE-HGF)POF4-5223},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:001369115500050},
      doi          = {10.1109/TQE.2022.3165968},
      url          = {https://juser.fz-juelich.de/record/909945},
}