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Efficiency of an autonomous, dynamic information engine operating on a single active particle.
1<a href="https://ror.org/0087djs12">Max Planck Institute for Dynamics and Self-Organization</a>, Göttingen 37073, Germany.
This study explores how information can be used to extract useful work from active fluctuations, potentially exceeding theoretical limits. It investigates an autonomous engine, analyzing measurement costs and efficiency through an auxiliary system.
Area of Science:
- Thermodynamics
- Information Theory
- Statistical Mechanics
Background:
- The Szilard engine highlights the link between information and thermodynamics.
- Landauer and Bennett resolved apparent paradoxes regarding the second law of thermodynamics concerning memory operations.
- Recent research explores active fluctuations and the potential to surpass Landauer's bound for work extraction.
Purpose of the Study:
- To investigate an autonomous dynamic information engine.
- To address the thermodynamic consistency of work extraction and measurement costs.
- To explore how information can be leveraged to perform useful work.
Main Methods:
- Extending the phase space to include an auxiliary system acting as a measurement device.
- Analyzing the nonreciprocal coupling between an active particle and the measurement device.
- Quantifying measurement costs via auxiliary entropy production.
Main Results:
- Demonstrated a feedback control loop driven by the measurement device.
- Quantified the thermodynamic cost associated with information measurement.
- Identified the crucial role of measurement precision in determining engine efficiency.
Conclusions:
- Autonomous information engines can extract useful work by utilizing active fluctuations.
- Thermodynamic consistency is maintained by accounting for measurement costs.
- Optimizing measurement precision is key to maximizing the efficiency of information engines.
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