A random rule model of surface growth

• A modified version of the etching model is presented.
• Stochasticity is introduced in the rule instead of in the site selection.
• The changes in dynamics make the model more suitable for exponents determination.
• The proposed model is computationally more efficient than the original one.

Stochastic models of surface growth are usually based on randomly choosing a substrate site to perform iterative steps, as in the etching model, Mello et al. (2001) [5]. In this paper I modify the etching model to perform sequential, instead of random, substrate scan. The randomicity is introduced not in the site selection but in the choice of the rule to be followed in each site. The change positively affects the study of dynamic and asymptotic properties, by reducing the finite size effect and the short-time anomaly and by increasing the saturation time. It also has computational benefits: better use of the cache memory and the possibility of parallel implementation.