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Boosting macroscopic diffusion with local resetting

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arxiv 2401.12772 v1 pith:R6BPE77W submitted 2024-01-23 cond-mat.soft cond-mat.stat-mechphysics.bio-ph

classification cond-mat.softcond-mat.stat-mechphysics.bio-ph
keywords interactionslocalresettingagentmacroscopicmechanismpropertiesresults
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Stochastic interactions generically enhance self-diffusivity in living and biological systems, e.g. optimizing navigation strategies and controlling material properties of cellular tissues and bacterial aggregates. Despite this, the physical mechanisms underlying this nonequilibrium behavior are poorly understood. Here, we introduce a model of interactions between an agent and its environment in the form of a local stochastic resetting mechanism, in which the agent's position is set to the nearest of a predetermined array of sites with a fixed rate. We derive analytic results for the self-diffusion coefficient, showing explicitly that this mechanism enhances diffusivity. Strikingly, we show analytically that this enhancement is optimized by regular arrays of resetting sites. Altogether, our results ultimately provide the conditions for the optimization of the macroscopic transport properties of diffusive systems with local random binding interactions.

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Nested Stochastic Resetting: Nonequilibrium Steady-states and Exact Correlations

    cond-mat.stat-mech 2025-02 conditional novelty 7.0 of 10

    A chain of Brownian particles with one-way stochastic resetting has exactly solvable steady-state distributions and two-point correlations.

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