Inverted List Kinetic Monte Carlo with Rejection Applied to Directed Self-Assembly of Epitaxial Growth

We study the growth of epitaxial thin films on pre-patterned substrates that influence the surface diffusion of subsequently deposited material using a kinetic Monte Carlo algorithm that combines the use of inverted lists with rejection. The resulting algorithm is well adapted to systems with spatially heterogeneous hopping rates. To evaluate the algorithm's performance we compare it with an efficient, binary-tree based algorithm. A key finding is that the relative performance of the inverted list algorithm improves with increasing system size.