Inverted List Kinetic Monte Carlo with Rejection Applied to Directed Self-Assembly of Epitaxial Growth (Communications in Computational Physics, 2009)
We study the growth of epitaxial thin films on pre-patterned substrates thatinfluence the surface diffusion of subsequently deposited material using a kinetic MonteCarlo algorithm that combines the use of inverted lists with rejection. The resultingalgorithm is well adapted to systems with spatially heterogeneous hopping rates.To evaluate the algorithm's performance we compare it with an efficient, binary-treebased algorithm. A key finding is that the relative performance of the inverted listalgorithm improves with increasing system size.