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@ARTICLE{Crippa:479822,
      author       = {Crippa, Arianna and Funcke, Lena and Hartung, Tobias and
                      Heinemann, Beate and Jansen, Karl and Kropf, Annabel and
                      Kuehn, Stefan and Meloni, Federico and Spataro, David and
                      Tueysuez, Cenk and Yap, Yee Chinn},
      title        = {{T}rack reconstruction at the {LUXE} experiment using
                      quantum algorithms},
      reportid     = {PUBDB-2022-03238, DESY-22-113. arXiv:2210.13021.
                      PROC-CTD2022-32. MIT-CTP/5476},
      pages        = {7},
      year         = {2022},
      note         = {7 pages, 6 figures, Proceedings of the Connecting The Dots
                      workshop 2022 (CTD2022)},
      abstract     = {LUXE (Laser Und XFEL Experiment) is a proposed experiment
                      at DESY which will study Quantum Electrodynamics (QED) in
                      the strong-field regime, where QED becomes non-perturbative.
                      The measurement of the rate of electron-positron pair
                      creation, an essential ingredient to study this regime, is
                      enabled by the use of a silicon tracking detector. Precision
                      tracking of positrons traversing the four layers of the
                      tracking detector becomes very challenging at high laser
                      intensities due to the high rates, which can be
                      computationally expensive for classical computers. In this
                      work, an update of our previous studies of the potential of
                      quantum computers to reconstruct positron tracks is
                      presented. The reconstruction problem is formulated in terms
                      of a Quadratic Unconstrained Binary Optimisation (QUBO), and
                      solved using simulated quantum computers and a hybrid
                      quantum-classical algorithm, namely Variational Quantum
                      Eigensolver (VQE). Different ansatz circuits and optimisers
                      are studied. The results are discussed and compared with
                      classical track reconstruction algorithms using Graph Neural
                      Network and Combinatorial Kalman Filter.},
      month         = {May},
      date          = {2022-05-31},
      organization  = {Connecting the Dots Workshop, New
                       Jersey (USA), 31 May 2022 - 2 Jun 2022},
      keywords     = {computer, quantum (INSPIRE) / laser, yield (INSPIRE) /
                      quantum electrodynamics (INSPIRE) / positron (INSPIRE) /
                      track data analysis (INSPIRE) / tracking detector (INSPIRE)
                      / strong field (INSPIRE) / binary (INSPIRE) / proposed
                      experiment (INSPIRE) / hybrid (INSPIRE) / quantum algorithm
                      (INSPIRE) / pixel (INSPIRE) / silicon (INSPIRE) / tracks
                      (INSPIRE) / nonperturbative (INSPIRE) / electron positron
                      (INSPIRE) / neural network (INSPIRE) / variational quantum
                      eigensolver (INSPIRE)},
      cin          = {FTX / ZEU-NIC},
      cid          = {I:(DE-H253)FTX-20210408 / I:(DE-H253)ZEU-NIC-20120731},
      pnm          = {622 - Detector Technologies and Systems (POF4-622)},
      pid          = {G:(DE-HGF)POF4-622},
      experiment   = {EXP:(DE-H253)LUXE-20220501},
      typ          = {PUB:(DE-HGF)25},
      eprint       = {2210.13021},
      howpublished = {arXiv:2210.13021},
      archivePrefix = {arXiv},
      SLACcitation = {$\%\%CITATION$ = $arXiv:2210.13021;\%\%$},
      doi          = {10.3204/PUBDB-2022-03238},
      url          = {https://bib-pubdb1.desy.de/record/479822},
}