Boosting macroscopic diffusion with local resetting

Area of Science:

• Physics
• Biophysics
• Statistical Mechanics

Background:

• Stochastic interactions are known to enhance self-diffusivity in biological systems, crucial for processes like navigation and tissue mechanics.
• The underlying physical mechanisms driving this nonequilibrium enhancement remain poorly understood.
• Understanding these mechanisms is key to controlling transport properties in cellular and bacterial systems.

Purpose of the Study:

• To introduce and analyze a model of stochastic resetting for understanding enhanced self-diffusivity.
• To derive analytic results for the self-diffusion coefficient under this resetting mechanism.
• To investigate how the arrangement of resetting sites affects diffusion enhancement.

Main Methods:

• Development of a theoretical model incorporating a local stochastic resetting mechanism.
• Analytical derivation of the self-diffusion coefficient.
• Mathematical analysis of the impact of resetting site regularity on diffusivity.

Main Results:

• The proposed stochastic resetting mechanism demonstrably enhances self-diffusivity.
• Analytic results explicitly show the enhancement of the diffusion coefficient.
• The enhancement of diffusivity is found to be optimized by regular arrays of resetting sites.

Conclusions:

• Stochastic resetting is a viable mechanism for enhancing self-diffusivity in diffusive systems.
• Regular arrangements of resetting sites offer an optimal strategy for maximizing diffusion.
• The findings provide conditions for optimizing macroscopic transport in systems with local binding interactions.