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Published on: February 16, 2024
Transport and its enhancement caused by coupling.
Jing-hui Li1, Qing-hu Chen, Xing-fei Zhou
1Faculty of Science, Ningbo University, Ningbo 315211, People's Republic of China.
Summary
We derived an exact formula for particle transport in coupled lattices with dichotomous noise. System asymmetry and coupling drive directional particle movement, even in symmetric systems.
Area of Science:
- Statistical Physics
- Condensed Matter Physics
- Nonlinear Dynamics
Background:
- Stochastic systems with periodic structures are crucial in various physical phenomena.
- Understanding particle transport in such systems is key to designing novel devices.
- Dichotomous noise is a common model for random fluctuations in physical and biological systems.
Purpose of the Study:
- To derive an exact analytical expression for the stationary probability current in a coupled lattice system driven by dichotomous noise.
- To identify the key factors influencing particle transport in these systems.
- To explore the role of spatial asymmetry, noise asymmetry, and inter-neighbor coupling.
Main Methods:
- Application of the Weiss mean-field approximation theory.
- Utilizing particles' transport theory for spatially periodic stochastic systems.
- Derivation of an exact analytical expression for the stationary probability current.
Main Results:
- Identified spatial asymmetry, noise asymmetry, and nearest-neighbor coupling as essential for stationary probability current.
- Demonstrated that coupling can induce directional particle transport, even under symmetric conditions.
- Showed that nearest-neighbor coupling can enhance particle transport in specific scenarios.
Conclusions:
- The study provides a theoretical framework for understanding particle transport in coupled stochastic lattice systems.
- The findings highlight the significant role of coupling in directing and enhancing particle movement.
- The results have potential applications in areas such as two-dimensional Josephson-junction arrays and protein motor clusters.
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