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Utsab Khadka1, Viktor Holubec2,3, Haw Yang1

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This study introduces active microparticles that self-organize into complex structures using positional information. These nonequilibrium structures exhibit frustrated geometries, mimicking bound systems through information flow.

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Area of Science:

  • Complex systems
  • Active matter physics
  • Collective behavior

Background:

  • Self-organization generates order from local interactions across diverse scientific fields.
  • Collective animal behaviors emerge from self-organization, involving abstract interactions and feedback loops.
  • Examples include human crowds, bird flocks, and bacterial swarms.

Purpose of the Study:

  • To introduce novel interactions between active microparticles based on positional information.
  • To investigate the self-organization and emergent structures in a system driven by real-time feedback.
  • To analyze the characteristics of these nonequilibrium structures, particularly their geometries and dynamics.

Main Methods:

  • Developing active microparticles with propulsion directed by real-time positional feedback of other particles.
  • Confining particle interactions to two dimensions.
  • Observing and analyzing emergent structures and their dynamical properties.

Main Results:

  • Emergent structures formed through continuous information flow between microparticles.
  • Observation of frustrated geometries due to 2D confinement.
  • Dynamical degrees of freedom within structures resembling physically bound systems.

Conclusions:

  • Active microparticles can self-organize into complex, nonequilibrium structures using positional information.
  • These structures exhibit unique geometric and dynamic properties influenced by confinement and feedback.
  • The study provides insights into self-organization principles in active matter systems.