Model discovery for studies of surface morphological modifications based on Kuramoto-Sivashinsky dynamics

A wide range of observations in studies of surfaces exposed to ion beams can be explained and analyzed successfully by continuum models of the Kuramoto-Sivashinsky type. Despite certain progress in the theoretical understanding of the model parameters on the basis of atomistic models, much of the applications are based on phenomenological determination of several unknown quantities. In this work a numerical tool is discussed and investigated, which allows us to determine model coefficients and complex model structures from experimental findings. The method resembles known approaches in machine learning and data-driven reconstruction techniques. To keep the discussion on a fundamental level, numerical simulations are conducted by employing a scaled test model. The reconstruction technique is demonstrated for this model system and shows a high accuracy in recovering input parameters for situations without beam noise. As an application to an unknown system to be explored, the algorithm is then applied to a system with lognormal distributed ion bombardment. The impact of the beam fluctuations in the proposed model are discussed. Perspectives of the numerical algorithm for an analysis of experimental data are addressed.