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Fluctuation theorems from Bayesian retrodiction.

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Bayesian retrodiction naturally defines the reverse process in statistical mechanics for both classical and quantum systems. This approach unifies and broadens fluctuation theorems, enhancing our understanding of irreversibility.

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Area of Science:

  • Statistical Mechanics
  • Quantum Mechanics
  • Bayesian Inference

Background:

  • Quantitative studies of irreversibility often grapple with defining the reverse process, especially in quantum systems.
  • Existing fluctuation theorems like Jarzynski's equality and Crooks' theorem have faced definitional challenges for reverse processes.

Purpose of the Study:

  • To demonstrate that Bayesian retrodiction provides a natural and unified framework for defining the reverse process in statistical mechanics.
  • To show the consistency of established fluctuation theorems with retrodictive arguments.
  • To generalize fluctuation relations by constructing the reverse process using logical inference.

Main Methods:

  • Applying Bayesian retrodiction to define reverse channels in classical and quantum theories.
  • Reinterpreting and validating paradigmatic results (Jarzynski's equality, Crooks' theorem, Tasaki's theorem) through a retrodictive lens.
  • Justifying corrections for non-equilibrium and open quantum systems as consequences of Bayesian retrodiction.

Main Results:

  • The reverse channel in statistical mechanics, both classical and quantum, arises naturally from Bayesian retrodiction.
  • Key fluctuation theorems are shown to be consistent with this retrodictive framework.
  • Corrections for non-equilibrium and open quantum systems are explained as remnants of Bayesian retrodiction.

Conclusions:

  • Bayesian retrodiction offers a unified and logically consistent method for defining reverse processes in statistical mechanics.
  • This approach broadens the scope and applicability of fluctuation relations.
  • The findings provide a more robust theoretical foundation for studying irreversibility in physical systems.