# Faceted patterns and anomalous surface roughening driven by long-term correlated noise

## TL;DR

This paper studies how long-term correlated noise affects surface growth in the KPZ model, revealing the emergence of faceted patterns and anomalous roughening not explained by traditional theories.

## Contribution

It demonstrates that long-term correlated noise induces faceted surface patterns and anomalous roughening in KPZ growth, challenging existing theoretical frameworks.

## Key findings

- Faceted patterns dominate surface morphology with increased noise correlation.
- Anomalous kinetic roughening occurs due to long-term noise correlations.
- Conventional renormalization group methods do not capture these phenomena.

## Abstract

We investigate Kardar-Parisi-Zhang (KPZ) surface growth in the presence of long-term correlated noise. By means of extensive numerical simulations of models in the KPZ universality class we find that, as the noise correlator range increases, the surface develops a pattern of macroscopic facets that completely dominate the dynamics and induce anomalous kinetic roughening. This novel phenomenon is not described by the conventional dynamic renormalisation group calculations and can explain the singular behavior observed in the analytical treatment of this problem in the seminal paper of Medina {\it et al} [Phys. Rev. A {\bf 39}, 3053 (1989)].