Optimal work extraction and mutual information in a generalized Szilárd engine.
Juyong Song1, Susanne Still2, Rafael Díaz Hernández Rojas3
1Samsung Research, Samsung Electronics Co., Ltd., Seoul, 06765, Korea.
Physical Review. E
|June 17, 2021
Summary
Researchers explored thermodynamic bounds for information processing using Szilárd's engine. They found optimal work extraction depends on particle number and partition configuration, revealing a critical point for symmetric versus asymmetric partitioning.
Area of Science:
- Thermodynamics
- Information Theory
- Statistical Mechanics
Background:
- Szilárd's engine (1929) established fundamental links between thermodynamics and information processing.
- The original model considered a single particle in a two-partition box.
Purpose of the Study:
- To calculate maximal average work extracted from a system with N particles and q partitions.
- To determine how work extraction relates to information about particle distribution.
Main Methods:
- Extended Szilárd's engine model to N particles and q partitions.
- Analyzed work extraction limited by pressure equalization.
- Quantified work via mutual information between particle position and partition counts.
Main Results:
- Average extracted work is proportional to mutual information.
- Identified a critical particle number N*(q) determining optimal partition symmetry.
- Optimal partitioning is symmetric for N < N*(q) and asymmetric for N > N*(q).
Conclusions:
- The study provides a generalized framework for Szilárd's engine.
- Optimal work extraction depends on a balance between information and system configuration.
- Asymptotic analysis for large N reveals further insights into thermodynamic limits.
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