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Geometric Brownian information engine: Upper bound of the achievable work under feedback control
Syed Yunus Ali1, Rafna Rafeek1, Debasish Mondal1
1Department of Chemistry and Center for Molecular and Optical Sciences and Technologies, Indian Institute of Technology Tirupati, Yerpedu 517619, Andhra Pradesh, India.
The Journal of Chemical Physics
|January 9, 2022
Summary
This study introduces a Brownian information engine using feedback control for trapped particles. Researchers found that the system
Area of Science:
- Statistical mechanics
- Non-equilibrium thermodynamics
- Information theory
Background:
- Brownian motion is fundamental to understanding particle dynamics.
- Information engines harness information to perform work.
- Entropy and energy play crucial roles in physical systems.
Purpose of the Study:
- To design and analyze a geometric Brownian information engine.
- To investigate the impact of feedback control on extractable work.
- To explore the interplay between entropic and energetic contributions.
Main Methods:
- Utilizing overdamped Brownian particles in a 2D confinement with varying width.
- Implementing a feedback control protocol based on error-free position measurement.
- Calculating extractable work, total information, and unavailable information.
Main Results:
- Derived the exact analytical upper bound for extractable work as (53-2ln2)kBT.
- Demonstrated a work crossover from (53-2ln2)kBT to 12kBT by tuning entropic and energetic contributions.
- Observed higher information loss in entropy-dominated regimes, reducing achievable work.
Conclusions:
- The designed Brownian information engine effectively utilizes feedback control.
- System behavior transitions between entropy-dominated and energy-dominated regimes, affecting work output.
- Theoretical predictions align well with Langevin dynamics simulations.
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