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@ARTICLE{Wennlf:616022,
      author       = {Wennlöf, Håkan and Dannheim, Dominik and Viera, Manuel
                      Del Rio and Dort, Katharina and Eckstein, Doris and King,
                      Finn and Gregor, Ingrid-Maria and Huth, Lennart and Lachnit,
                      Stephan and Mendes, Larissa and Rastorguev, Daniil and Daza,
                      Sara Ruiz and Schütze, Paul and Simancas, Adriana and
                      Snoeys, Walter and Spannagel, Simon and Stanitzki, Marcel
                      and Tomal, Alessandra and Velyka, Anastasiia and Vignola,
                      Gianpiero},
      title        = {{S}imulating {M}onolithic {A}ctive {P}ixel {S}ensors: {A}
                      {T}echnology-{I}ndependent {A}pproach {U}sing {G}eneric
                      {D}oping {P}rofiles},
      reportid     = {PUBDB-2024-06315, arXiv:2408.00027},
      year         = {2024},
      note         = {22 pages, 25 figures, submitted to Nuclear Instruments and
                      Methods in Physics Research, Section A},
      abstract     = {The optimisation of the sensitive region of CMOS sensors
                      with complex non-uniform electric fields requires precise
                      simulations, and this can be achieved by a combination of
                      electrostatic field simulations and Monte Carlo methods.
                      This paper presents the guiding principles of such
                      simulations, using a CMOS pixel sensor with a small
                      collection electrode and a high-resistivity epitaxial layer
                      as an example. The full simulation workflow is described,
                      along with possible pitfalls and how to avoid them. For
                      commercial CMOS processes, detailed doping profiles are
                      confidential, but the presented method provides an
                      optimisation tool that is sufficiently accurate to
                      investigate sensor behaviour and trade-offs of different
                      sensor designs without knowledge of proprietary information.
                      The workflow starts with detailed electric field finite
                      element method simulations in TCAD, using generic doping
                      profiles. Examples of the effect of varying different
                      parameters of the simulated sensor are shown, as well as the
                      creation of weighting fields, and transient pulse
                      simulations. The fields resulting from TCAD simulations can
                      be imported into the Allpix Squared Monte Carlo simulation
                      framework, which enables high-statistics simulations,
                      including modelling of stochastic fluctuations from the
                      underlying physics processes of particle interaction.
                      Example Monte Carlo simulation setups are presented and the
                      different parts of a simulation chain are described.
                      Simulation studies from small collection electrode CMOS
                      sensors are presented, and example results are shown for
                      both single sensors and multiple sensors in a test beam
                      telescope configuration. The studies shown are those
                      typically performed on sensor prototypes in test beam
                      campaigns, and a comparison is made to test beam data,
                      showing a maximum deviation of $4\%$ and demonstrating that
                      the approach is viable for generating realistic results.},
      cin          = {ATLAS},
      cid          = {I:(DE-H253)ATLAS-20120731},
      pnm          = {611 - Fundamental Particles and Forces (POF4-611) /
                      AIDAinnova - Advancement and Innovation for Detectors at
                      Accelerators (101004761)},
      pid          = {G:(DE-HGF)POF4-611 / G:(EU-Grant)101004761},
      experiment   = {EXP:(DE-H253)LHC-Exp-ATLAS-20150101},
      typ          = {PUB:(DE-HGF)25},
      eprint       = {2408.00027},
      howpublished = {arXiv:2408.00027},
      archivePrefix = {arXiv},
      SLACcitation = {$\%\%CITATION$ = $arXiv:2408.00027;\%\%$},
      doi          = {10.3204/PUBDB-2024-06315},
      url          = {https://bib-pubdb1.desy.de/record/616022},
}