2008
DOI: 10.1590/s0103-97332008000100016
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Strategies for optimize off-lattice aggregate simulations

Abstract: We review some computer algorithms for the simulation of off-lattice clusters grown from a seed, with emphasis on the diffusion-limited aggregation, ballistic aggregation and Eden models. Only those methods which can be immediately extended to distinct off-lattice aggregation processes are discussed. The computer efficiencies of the distinct algorithms are compared.

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Cited by 17 publications
(13 citation statements)
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“…In the case of overlap, simulation proceeds to the next step. The time is increased by ∆t = 1/N , where N is the number of particles of the cluster at time t. Optimization strategies described in reference [32] were used to speed up the simulation. A cluster of diameter 8000 takes typically 8 min of simulation in a CPU Intel Xeon 3.2 GHz, whereas if no optimization is used the same simulation takes several hours of computation.…”
Section: Isotropic Radial Growthmentioning
confidence: 99%
“…In the case of overlap, simulation proceeds to the next step. The time is increased by ∆t = 1/N , where N is the number of particles of the cluster at time t. Optimization strategies described in reference [32] were used to speed up the simulation. A cluster of diameter 8000 takes typically 8 min of simulation in a CPU Intel Xeon 3.2 GHz, whereas if no optimization is used the same simulation takes several hours of computation.…”
Section: Isotropic Radial Growthmentioning
confidence: 99%
“…The previously introduced variables r l and r k must be as large as possible, but computational limitations restrict their values. For the DLA simulations, ∆ can be a few particle diameters [27]. However, for the BA limit, ∆ cannot be small due to distortions caused by shadow instabilities [28,29].…”
Section: Modelmentioning
confidence: 99%
“…Cluster growth optimizations were implemented using steps of size 16a in the large empty regions nearby the cluster and three step sizes (16a, 100a and 200a) were used far from the cluster. More details about long step and off-lattice optimizations are available elsewhere [27].…”
Section: Modelmentioning
confidence: 99%
“…If the growth starts with a single particle, the model yields asymptotically spherical clusters with a self-affine surface exhibiting the scaling exponents of the KPZ universality class [21]. We simulated off-lattice clusters in twodimensions with the usual algorithm [21,22]: a particle in the active (growing) zone 1 is selected at random and a new particle is added in a random position chosen in the empty neighbourhood of the selected particle. The procedure is repeated while the cluster does not reach N particles.…”
mentioning
confidence: 99%