Fluctuation-dominated phase ordering driven by stochastically evolving surfaces: depth models and sliding particles

Area of Science:

• Statistical Physics
• Condensed Matter Physics
• Surface Science

Background:

• Investigating phase ordering phenomena in complex systems is crucial for understanding emergent behaviors.
• Fluctuating surfaces and particle dynamics present challenges due to their inherent randomness and scale-dependent properties.
• Conventional models often fail to capture the nuances of systems with large-scale fluctuations.

Purpose of the Study:

• To explore unconventional phase ordering in coarse-grained models of fluctuating surfaces.
• To analyze the behavior of hard-core particles sliding on these surfaces under gravity.
• To characterize the deviations from conventional phase ordering and Porod law in specific universality classes.

Main Methods:

• Coarse-grained depth models for Edwards-Wilkinson (EW), Kardar-Parisi-Zhang (KPZ), and noisy surface-diffusion (NSD) universality classes.
• Numerical and exact analytical techniques to study coarsening processes and steady states.
• Analysis of particle cluster size distributions, spatial correlation functions, and density-density correlations.

Main Results:

• Systems exhibit ordering with large-scale fluctuations, deviating from conventional states.
• For EW and KPZ surfaces, order parameter distributions are broad, and correlation functions show cusps (alpha=1/2), differing from Porod law.
• Surface fluctuations induce large-scale particle clustering, with coarsening length scaling as t^(1/z).

Conclusions:

• Fluctuating surfaces exhibit unique phase ordering characterized by broad distributions and cusped correlation functions.
• Particle dynamics on these surfaces lead to significant clustering driven by surface fluctuations.
• The findings challenge conventional coarsening theories and highlight the importance of scale-dependent phenomena in statistical physics.