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Active Brownian particles with spin dynamics in fluctuating environments exhibit patterned order. Competition between interactions and active noise drives phase transitions and microphase separation, creating diverse structures like lamellar and hexagonal patterns.

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Area of Science:

  • Soft-matter science
  • Statistical physics
  • Active matter systems

Background:

  • Systems of independent active particles in fluctuating environments are crucial in soft-matter science.
  • Understanding the collective behavior and emergent properties of such systems is a key challenge.

Purpose of the Study:

  • To investigate the role of activity-driven spin dynamics in generating patterned order in a minimal model of Brownian particles.
  • To explore how competition between mediated interactions and active noise influences system behavior.

Main Methods:

  • Utilized a minimal model of noninteracting spin-carrying Brownian particles in a Gaussian field.
  • Employed Monte Carlo simulations combined with analytical methods based on dynamical density functional approaches.

Main Results:

  • Demonstrated that activity-driven spin dynamics leads to patterned order.
  • Observed diverse behaviors including phase transitions and microphase separation, ranging from lamellar to hexagonal ordering of opposite magnetization clusters.
  • Identified both stationary and dynamic regimes, including the formation and growth of magnetization lumps.

Conclusions:

  • The interplay of mediated interactions and active noise is sufficient to generate complex multibody interactions and diverse emergent behaviors.
  • The model successfully captures phenomena like phase transitions and microphase separation driven by particle activity and spin dynamics.