Pinning-depinning transitions in two classes of discrete elastic-string models in (2+1)-dimensions

TL;DR

This study investigates pinning-depinning phase transitions in two classes of discrete elastic-string models in (2+1) dimensions, estimating critical exponents and analyzing surface morphologies, revealing they do not belong to existing universality classes.

Contribution

The paper provides extensive numerical analysis of pinning-depinning transitions in (2+1)-D discrete elastic-string models with quenched disorder, identifying their unique universality class.

Findings

Critical exponents satisfy scaling relations.

Models do not belong to known universality classes.

Surface morphologies relate to scaling and correlation length.

Abstract

The pinning-depinning phase transitions of interfaces for two classes of discrete elastic-string models are investigated numerically. In the (1+1)-dimensions, we revisit these two elastic-string models with slight modification to growth rule, and compare the estimated values with the previous numerical and experimental results. For the (2+1)-dimensional case, we perform extensive simulations on pinning-depinning transitions in these { discrete models with quenched disorder}. For full comparisons in the physically relevant spatial dimensions, we also perform numerically two distinct universality classes, including the quenched Edwards-Wilkinson (QEW), and the quenched Kardar-Parisi-Zhang (QKPZ) equations with and without external driving forces. The critical exponents of these {systems in the presence of quenched disorder} are numerically estimated. Our results show that the critical exponents satisfy scaling relations well, and these two discrete elastic-string models do not fall into the existing universality classes. In order to visually comparisons of these {discrete systems with quenched disorder} in the (2+1)-dimensional cases, we present surface morphologies with various external driving forces during the saturated time regimes. The relationships between surface morphologies, scaling exponents and correlation length are also revealed.