Nonequilibrium statistical physics beyond the ideal heat bath approximation.

Area of Science:

• Statistical Physics
• Physical Chemistry
• Biophysics

Background:

• Many nonequilibrium statistical physics (NESP) models rely on a near-equilibrium approximation, assuming ideal equilibrium baths for fluctuations.
• This assumption, common in Fokker-Planck, Langevin, and diffusion models, fails when systems are far from equilibrium.

Purpose of the Study:

• To develop a more principled approach for NESP by deriving rate fluctuations from underlying dynamics.
• To introduce corrections for NESP processes in realistic, imperfect environments, especially for systems far from equilibrium.

Main Methods:

• Utilized the maximum caliber principle as the foundational framework.
• Derived corrections to NESP models based on a more realistic environmental interaction.

Main Results:

• Developed a method to correct NESP models that are limited by near-equilibrium approximations.
• Showed that environmental factors beyond temperature, such as speed and size, are critical for characterizing fluctuations in systems far from equilibrium.

Conclusions:

• The study provides a more accurate framework for NESP by moving beyond the ideal bath approximation.
• The findings are particularly relevant for understanding and modeling complex systems driven far from thermodynamic equilibrium.