Conditional Entropic Approach to Nonequilibrium Complex Systems with Weak Fluctuation Correlation

Area of Science:

• Non-equilibrium thermodynamics
• Statistical mechanics
• Complex systems analysis

Background:

• Understanding the behavior of complex systems far from equilibrium is challenging.
• Spatiotemporal fluctuations in these systems often exhibit weak correlations over large time scales.
• Characterizing these fluctuations is crucial for modeling dynamic processes.

Purpose of the Study:

• To develop a conditional entropic approach for analyzing non-equilibrium complex systems.
• To investigate the role of weak correlations in fluctuation distributions.
• To provide a framework for understanding diffusion phenomena in biological contexts.

Main Methods:

• Application of conditional entropy principles.
• Analysis of fluctuation distributions in systems with weak correlations.
• Modeling of diffusion processes using the developed entropic approach.

Main Results:

• Identified that weak correlations in spatiotemporal fluctuations maximize conditional entropy.
• Demonstrated the approach's efficacy in explaining protein diffusion within bacteria.
• Showcased potential applications in modeling membraneless organelles and cellular components.

Conclusions:

• The conditional entropic approach offers a novel perspective on non-equilibrium systems.
• Weak correlations play a key role in maximizing entropy and governing diffusion.
• The framework is applicable to diverse biological diffusion phenomena.