Fluctuation-dominated phase ordering in the one dimensional Truncated Inverse Distance Square Ising (TIDSI) model

TL;DR

This paper investigates fluctuation-dominated phase ordering in the one-dimensional TIDSI model, combining analytical cluster representation and Monte Carlo simulations to explore critical behavior, correlation growth, and aging dynamics.

Contribution

It introduces the TIDSI-CL cluster representation, analyzes the narrow range of the interaction ratio c, and studies coarsening and aging phenomena in the model.

Findings

Analytical results agree with Monte Carlo simulations within the allowed c range.

Correlation length diverges near the critical point, indicating a broad near-critical region.

Aging behavior exhibits two scaling regimes with distinct exponents.

Abstract

Many physical systems, including some examples of active matter, granular assemblies, and biological systems, show fluctuation-dominated phase ordering (FDPO), where macroscopic fluctuations coexist with long-range order. Most of these systems are out of equilibrium. By contrast, a recent work has analytically demonstrated that an equilibrium one-dimensional Truncated Inverse Distance Square Ising (TIDSI) model shows FDPO. The analytical results rely on a cluster representation of the model that we term TIDSI-CL and are governed by the ratio, $c$, of the long-range interaction strength to the critical temperature. We show that the allowed range of $c$ is very narrow in the TIDSI model while it is unbounded in TIDSI-CL. We perform Monte-Carlo simulations for the TIDSI model and show consistency with the analytical results in the allowed range of $c$. The correlation length grows strongly on approaching the critical point, leading to a broad near-critical region. Within this region, $\alpha$, which is the cusp exponent of the power-law decay of the scaled correlation function at criticality, changes to $\alpha^\text{eff}$. We also investigate the coarsening dynamics of the model: the correlation function, domain size distribution, and aging behavior are consistent with the equilibrium properties upon replacing the system size, $L$, with the coarsening length, $\mathcal{L}(t)$. The mean largest cluster size shows logarithmic corrections due to finite $L$ and waiting time, $t_w$. The aging autocorrelation function exhibits two different scaling forms, characterized by exponents $\beta$ and $\gamma$, at short and long times compared to $t_w$, where $\beta=\alpha/2$.