Dynamics of Fluctuation Dominated Phase Ordering: Hard-core Passive Sliders on a Fluctuating Surface

TL;DR

This paper investigates the dynamics of particles on a fluctuating surface, revealing long-range order, clustering behavior, and complex aging phenomena through simulations and analytical methods.

Contribution

It introduces a detailed analysis of fluctuation-driven phase ordering in a one-dimensional particle-surface system, combining numerical simulations with analytical calculations.

Findings

Long-range order exists despite fluctuations.

Auto-correlation decays with a cusp, indicating non-trivial scaling.

System meanders between ordered states without losing order.

Abstract

We study the dynamics of a system of hard-core particles sliding downwards on a one dimensional fluctuating interface, which in a special case can be mapped to the problem of a passive scalar advected by a Burgers fluid. Driven by the surface fluctuations, the particles show a tendency to cluster, but the hard-core interaction prevents collapse. We use numerical simulations to measure the auto-correlation function in steady state and in the aging regime, and space-time correlation functions in steady state. We have also calculated these quantities analytically in a related surface model. The steady state auto-correlation is a scaling function of t/L^z, where L is the system size and z the dynamic exponent. Starting from a finite intercept, the scaling function decays with a cusp, in the small argument limit. The finite value of the intercept indicates the existence of long range order in the system. The space-time correlation, which is a function of r/L and t/L^z, is non-monotonic in t for fixed r. The aging auto-correlation is a scaling function of t_1 and t_2 where t_1 is the waiting time and t_2 the time difference. This scaling function decays as a power law for t_2 \gg t_1; for t_1 \gg t_2, it decays with a cusp as in steady state. To reconcile the occurrence of strong fluctuations in the steady state with the fact of an ordered state, we measured the distribution function of the length of the largest cluster. This shows that fluctuations never destroy ordering, but rather the system meanders from one ordered configuration to another on a relatively rapid time scale.