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Active particles in moving traps: Minimum work protocols and information efficiency of work extraction.

Janik Schüttler1, Rosalba Garcia-Millan1,2,3, Michael E Cates1

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We found optimal control strategies for active particles in harmonic traps. Feedback control reduces work costs, and finite persistence time minimizes work, leading to an active information engine.

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Area of Science:

  • Physics
  • Statistical Mechanics
  • Active Matter Physics

Background:

  • Controlling particle movement in harmonic traps is a fundamental problem.
  • Active particles, which consume energy to move, introduce new complexities.
  • Understanding optimal control for active matter is crucial for nanotechnology and biophysics.

Purpose of the Study:

  • To establish general principles for thermodynamically optimal control of active matter.
  • To compare work costs and fluctuations for different active particle models (Gaussian vs. non-Gaussian).
  • To investigate the role of feedback control and measurement uncertainty.

Main Methods:

  • Theoretical calculations of optimal control protocols.
  • Analysis of work variance and information efficiency.
  • Simulations of Active Ornstein-Uhlenbeck and run-and-tumble particles.
  • Development of an active information engine model.

Main Results:

  • Open-loop protocols are similar to passive particles but have higher work fluctuations.
  • Closed-loop (feedback) control reduces average work with minimal measurement error.
  • Finite persistence time is key to achieving minimum work.
  • The proposed active information engine shows higher efficiency with run-and-tumble particles.

Conclusions:

  • General principles for active matter control are established.
  • Feedback control offers significant advantages in reducing work costs.
  • Active information engines can harness self-propulsion for work extraction.