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

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.