Clustering, intermittency and scaling for passive particles on fluctuating surfaces
Tapas Singha, Mustansir Barma

TL;DR
This paper develops a scaling framework to analyze clustering and intermittency of passive particles on fluctuating surfaces, combining simulations and analytical models to understand their steady state and approach dynamics.
Contribution
It introduces a comprehensive scaling approach to characterize particle clustering, intermittency, and aging on fluctuating surfaces, supported by analytical and numerical results.
Findings
Clustering exhibits multiscaling depending on driving surface.
Intermittency causes divergence of flatness in steady state.
Scaling laws describe the approach to steady state and aging behavior.
Abstract
We show that a scaling approach successfully characterizes clustering and intermittency in space and time, in systems of noninteracting particles driven by fluctuating surfaces. We study both the steady state and the approach to it, for passive particles sliding on one-dimensional Edwards-Wilkinson or Kardar-Parisi-Zhang surfaces, with particles moving either along or against the growth direction in the latter case. Extensive numerical simulations are supplemented by analytical results for a sticky slider model in which particles coalesce when they meet. Results for single particle displacement versus time show to what extent particle dynamics is slaved to the surface, while scaling properties of the probability distribution of the separation of two particles have important implications for replica symmetry breaking for a pair of trajectories. For the many-particle system, clustering in…
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