Kinetic Monte Carlo algorithm study of physical vapor deposition thin film growth

A new kinetic Monte Carlo algorithm was provided to simulate thin film growing of physical vapor deposition. Red-black tree was used to select jump path and update system jump rate, the efficiencies of red-black tree search, linear tree search and binary tree search were compared, and the time complexity and space complexity were analyzed synthetically. The results show that red-black tree search is better than linear search and binary tree search in kinetic Monte Carlo simulation, whose efficiency is the highest, and red-black tree is adapted to be used in kinetic Monte Carlo simulation of large system with plenty of atoms like thin film prepared by physical vapor deposition.