% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@TECHREPORT{Scherer:1009243,
      author       = {Scherer, Benedikt},
      title        = {{E}valuation of {L}ine {D}etection {M}ethods for the
                      {A}nalysis of {C}harge {S}tability {D}iagrams},
      volume       = {4441},
      number       = {4441},
      address      = {Jülich},
      publisher    = {Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag},
      reportid     = {FZJ-2023-02705, 4441},
      series       = {Berichte des Forschungszentrums Jülich},
      pages        = {IX, 64},
      year         = {2023},
      abstract     = {The various approaches for the implementation of qubits are
                      objects of ongoing research. One approach uses the spin
                      states of electrons that are confined in double quantum
                      dots. For the calibration of such a qubit, charge stability
                      diagrams (CSDs) are measured and analyzed. They constitute
                      the changes in dependence on the voltages of two electrodes
                      and, thus, can be represented as grayscale images. The
                      voltages at which electrons tunnel in or out of the quantum
                      dots correspond to line structures in the CSD images.
                      Therefore, the automatic detection of lines in CSD images
                      plays an important role in the qubit calibration process.
                      Various line detection methods are explored in this thesis.
                      Since edge detection is a substep employed by several line
                      detectors, a selection of edge detection methods is explored
                      as well. Additionally, postprocessing methods for the
                      validation, grouping, and merging of lines and the
                      segmentation of infinite lines into finite line segments are
                      investigated. This thesis focuses on traditional approaches
                      as opposed to approaches based on machine learning. Two
                      methods are proposed for the automatic evaluation of the
                      detection results. Both methods function by comparing the
                      detections against a manually labeled ground truth data set.
                      The first method evaluates edge maps by comparing the
                      individual edge pixels with the pixels corresponding to the
                      ground truth lines. The second method benchmarks the
                      detected lines against the ground truth lines. Using these
                      evaluation methods, the free parameters of the edge
                      detectors, line detectors, and postprocessing methods are
                      optimized. The detection results of the methods are
                      evaluated and compared for four data setsof varying quality.
                      Additionally, the implications of the detection quality for
                      the analysis of CSDs are explained.},
      cin          = {ZEA-2},
      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)3 / PUB:(DE-HGF)29},
      doi          = {10.34734/FZJ-2023-02705},
      url          = {https://juser.fz-juelich.de/record/1009243},
}