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Emergence of Memory in Equilibrium versus Nonequilibrium Systems
Xizhu Zhao1,2, David Hartich1, Aljaž Godec1
1Mathematical bioPhysics Group, Max Planck Institute for Multidisciplinary Sciences, Am Faßberg 11, 37077 Göttingen.
Physical Review Letters
|April 19, 2024
Summary
Memory effects in complex systems depend on how observable and hidden dynamics interact. Equilibrium systems show memory when timescales overlap, while driven systems exhibit maximal memory with timescale separation, aiding mechanism diagnostics.
Area of Science:
- Statistical Mechanics
- Complex Systems Dynamics
- Information Theory
Background:
- Experiments often simplify high-dimensional systems to low-dimensional observables, causing loss of information about hidden microscopic details.
- Correlations between observable states and hidden degrees of freedom are known to cause memory effects, but their emergence conditions are unclear.
Purpose of the Study:
- To investigate the emergence of memory effects in minimal stationary systems.
- To differentiate memory emergence in cooperative (equilibrium) versus driven (non-equilibrium) scenarios.
Main Methods:
- Analysis of minimal stationary systems with coupled observed and hidden degrees of freedom.
- Comparison of memory emergence under different coupling mechanisms: cooperative evolution (equilibrium) and hidden non-equilibrium current (driven).
Main Results:
- In equilibrium systems, strongest memory effects arise when the timescales of hidden and observed dynamics overlap.
- In driven systems, maximal memory emerges under a clear separation of timescales between hidden and observed dynamics.
Conclusions:
- Memory emergence mechanisms differ fundamentally between equilibrium and driven systems.
- These differences can potentially serve as a diagnostic tool to identify underlying hidden transport mechanisms.
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