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This study analyzes large deviations in driven diffusion models, revealing fluctuation regimes through an effective Markov process. The findings offer insights into nonequilibrium systems and current fluctuations.

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Area of Science:

  • Statistical Mechanics
  • Nonequilibrium Physics
  • Stochastic Processes

Background:

  • Driven diffusion on a circle models complex nonequilibrium systems.
  • Understanding current fluctuations is key to characterizing system dynamics.

Purpose of the Study:

  • To analyze large deviations of time-integrated current in driven diffusion.
  • To explain observed fluctuation regimes using an effective Markov process.
  • To derive bounds for the current large deviation function.

Main Methods:

  • Fourier-Bloch decomposition of the tilted generator.
  • Construction of an effective (driven) Markov process.
  • Analysis of fluctuation regimes and low-noise limits.

Main Results:

  • Obtained large deviation functions for current fluctuations.
  • Developed an effective Markov process explaining fluctuation regimes.
  • Derived an upper bound for the current large deviation function.

Conclusions:

  • The effective Markov process provides physical insight into fluctuation regimes.
  • Comparison with entropic bounds and study of low-noise limits advance understanding of large deviations in nonequilibrium systems.