An effective algorithm for simulating diffusion-driven aggregation Original Research Article

In many fields of physics and chemistry growth phenomena driven by mutual particle collisions (coagulation) are of great interest. In this paper an effective N-particle-method for simulating the coagulation due to Brownian motion at very low number densities is presented. Under such conditions the mean particle distance exceeds the typical aggregate diameter by orders of magnitude and a collision will be a very rare event. We derive a criterion which allows an efficient detection of candidates for imminent collisions. The N-particle method is based on an adaptive time step scheme respecting for the individual dynamical states of the aggregates. The numerical cost of the algorithm scales with the particle number approximately as NlogN. In order to minimize the influence of the decreasing number of particles within the simulation box a new rescaling method is used throughout the aggregation process.