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@INPROCEEDINGS{Cordes:911607,
      author       = {Cordes, Jakob and Tordeux, Antoine and Schadschneider,
                      Andreas and Rüdiger, Babara and Ugurcan, Baris},
      title        = {{N}oise-induced breakdown in linear self-driven particle
                      systems},
      school       = {Universität zu Köln},
      reportid     = {FZJ-2022-04866},
      year         = {2022},
      abstract     = {Self-driven particle systems can describe many
                      self-organized phenomena. Prominentexamples are oscillation,
                      wave, lane, or band formations, among other swarming
                      andcoordinated movements. Collective dynamics are
                      classically understood in the literature of active matter as
                      motility-induced phase separation using meta-stable
                      non-linear in-teraction models. Critical settings of the
                      parameters separate the disorder states from non-uniform
                      dynamics describing macroscopic patterns and structures. We
                      show in this contribution that noise effects can initiate
                      the spontaneous formation of waves insingle-file motions of
                      self-driven particles. In contrast to usual modeling
                      approaches, no non-linear interaction mechanisms or phase
                      transitions are necessary to coordinate the dynamics. The
                      stochastic effects initiate the self-organization in the
                      second order in a purely linear and ergodic framework. The
                      coupling of the noise to a discrete gradient in space yields
                      the emergence of stop-and-go waves, which we characterize
                      using speed and spacing auto-correlation functions. Varying
                      the characteristics of the noise allows for obtaining rich
                      dynamics ranging from coupled dynamics and stable
                      homogeneous dynamics to stop-and-go patterns with
                      deterministic oscillating features.},
      month         = {Aug},
      date          = {2022-08-22},
      organization  = {JMC 2022, Lyon (France), 22 Aug 2022 -
                       26 Aug 2022},
      subtyp        = {After Call},
      cin          = {IAS-7},
      cid          = {I:(DE-Juel1)IAS-7-20180321},
      pnm          = {5111 - Domain-Specific Simulation Data Life Cycle Labs
                      (SDLs) and Research Groups (POF4-511) / DFG project
                      446168800 - Multi-Agent-Modellierung der Dynamik von dichten
                      Fußgängermengen: Vorhersagen Verstehen (446168800)},
      pid          = {G:(DE-HGF)POF4-5111 / G:(GEPRIS)446168800},
      typ          = {PUB:(DE-HGF)24},
      url          = {https://juser.fz-juelich.de/record/911607},
}