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Area of Science:

  • Statistical Physics
  • Soft Matter Physics

Background:

  • Controlling stochastic systems is crucial for applications in biology and materials science.
  • Most research focuses on equilibrium systems, leaving out-of-equilibrium dynamics less understood.
  • Active Brownian particles (ABPs) model self-propelled entities like bacteria.

Purpose of the Study:

  • To develop control protocols for a 2D active Brownian particle system in a harmonic potential.
  • To transition the system from a passive-like steady state to an active-like steady state.
  • To explore control strategies for genuinely out-of-equilibrium systems.

Main Methods:

  • Investigated a 2D active Brownian particle model within a harmonic potential.
  • Analyzed control protocols by adjusting potential stiffness and particle activity.
  • Derived exact analytical results for the system dynamics.

Main Results:

  • Identified specific driving parameter protocols to achieve the desired state transition.
  • Demonstrated the feasibility of controlling out-of-equilibrium ABPs.
  • Obtained analytical solutions for this prototypical self-propelled particle model.

Conclusions:

  • Developed novel control techniques applicable to a broader range of out-of-equilibrium systems.
  • The findings advance the understanding and control of active matter.
  • This work bridges statistical physics and complex system control.