Efficiency of one-dimensional active transport conditioned on motility

Area of Science:

• Statistical Mechanics
• Soft Matter Physics
• Theoretical Physics

Background:

• Stochastic processes exhibit altered properties when conditioned on observable values.
• Active matter systems involve self-propelled particles with inherent motility.
• Dynamical large deviations theory provides tools for analyzing effective processes.

Purpose of the Study:

• To investigate how conditioning interacting self-propelled particles on their motility affects their emergent interactions.
• To analyze the energy efficiency of these conditioned processes.
• To explore the nature of emergent interactions in active matter.

Main Methods:

• Applying the effective process formalism from dynamical large deviations theory.
• Analyzing two models: totally asymmetric exclusion process (TASEP) and run-and-tumble particles.
• Comparing two- and three-body interaction scenarios.

Main Results:

• Conditioning run-and-tumble particles induces alignment interactions and improves efficiency more than in TASEP.
• A diminishing return in efficiency is observed beyond a certain conditioning level.
• A screening effect in three-body systems suggests topological interactions.

Conclusions:

• Conditioning active matter particles on motility can lead to significant energy efficiency gains.
• Exploiting large fluctuations in mobility is key for substantial efficiency improvements.
• Emergent interactions can exhibit topological properties, especially in multi-particle systems.