% 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”.

@ARTICLE{Teske:862060,
      author       = {Teske, Julian and Humpohl, Simon and Otten, Rene and
                      Bethke, Patrick and Cerfontaine, Pascal and Dedden, Jonas
                      and Ludwig, Arne and Wieck, Andreas D. and Bluhm, Hendrik},
      title        = {{A} machine learning approach for automated fine-tuning of
                      semiconductor spin qubits},
      journal      = {Applied physics letters},
      volume       = {114},
      number       = {13},
      issn         = {1077-3118},
      address      = {Melville, NY},
      publisher    = {American Inst. of Physics},
      reportid     = {FZJ-2019-02424},
      pages        = {133102 -},
      year         = {2019},
      abstract     = {While spin qubits based on gate-defined quantum dots have
                      demonstrated very favorable properties for quantum
                      computing, one remaining hurdle is the need to tune each of
                      them into a good operating regime by adjusting the voltages
                      applied to electrostatic gates. The automation of these
                      tuning procedures is a necessary requirement for the
                      operation of a quantum processor based on gate-defined
                      quantum dots, which is yet to be fully addressed. We present
                      an algorithm for the automated fine-tuning of quantum dots
                      and demonstrate its performance on a semiconductor
                      singlet-triplet qubit in GaAs. The algorithm employs a
                      Kalman filter based on Bayesian statistics to estimate the
                      gradients of the target parameters as a function of gate
                      voltages, thus learning the system response. The algorithm's
                      design is focused on the reduction of the number of required
                      measurements. We experimentally demonstrate the ability to
                      change the operation regime of the qubit within 3–5
                      iterations, corresponding to 10–15 min of lab-time.},
      cin          = {PGI-11},
      ddc          = {530},
      cid          = {I:(DE-Juel1)PGI-11-20170113},
      pnm          = {144 - Controlling Collective States (POF3-144)},
      pid          = {G:(DE-HGF)POF3-144},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000463657000023},
      doi          = {10.1063/1.5088412},
      url          = {https://juser.fz-juelich.de/record/862060},
}