Monte Carlo study of linear diffusion-limited aggregation

1986 ◽  
Vol 19 (3) ◽  
pp. L131-L135 ◽  
Author(s):  
J -M Debierre ◽  
L Turban
1986 ◽  
Vol 55 (8) ◽  
pp. 2479-2482 ◽  
Author(s):  
Yoshinori Hayakawa ◽  
Hiroshi Kondo ◽  
Mitsugu Matsushita

Author(s):  
Tong Gao ◽  
Ziwei Qian ◽  
Hongbo Chen ◽  
Reza Shahbazian-Yassar ◽  
Issei Nakamura

We have developed a lattice Monte Carlo (MC) simulation based on the diffusion-limited aggregation model that accounts for the effect of the physical properties of small ions such as inorganic...


1996 ◽  
Vol 464 ◽  
Author(s):  
Andrew Yen ◽  
Raoul Kopelman

ABSTRACTThe diffusion-limited annihilation reactions A+A→products and A+B→products havebeen subject to theoretical, numerical, and experimental study over the past decade. “Anomalous” behaviors have been reported for both reactions, but with different upper critical dimensions (d=2 and d=4 respectively). The critical dimensions and the scaling of the exponents for the generalized reaction nA+mB→products depends on n and m. We present Monte Carlo simulations for two different types of third-order reactions, A+A+A→0 and A+2B→0, on both one and two dimensional lattices. Our numerical results show that for the two-dimensional case the behavior of the reaction follows mean-field theory while in one dimension the result is“anomalous”. Our numerical results are in good agreement with theory based on microscopic arguments and scaling analysis.


Methodology ◽  
2013 ◽  
Vol 9 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Holger Steinmetz

Although the use of structural equation modeling has increased during the last decades, the typical procedure to investigate mean differences across groups is still to create an observed composite score from several indicators and to compare the composite’s mean across the groups. Whereas the structural equation modeling literature has emphasized that a comparison of latent means presupposes equal factor loadings and indicator intercepts for most of the indicators (i.e., partial invariance), it is still unknown if partial invariance is sufficient when relying on observed composites. This Monte-Carlo study investigated whether one or two unequal factor loadings and indicator intercepts in a composite can lead to wrong conclusions regarding latent mean differences. Results show that unequal indicator intercepts substantially affect the composite mean difference and the probability of a significant composite difference. In contrast, unequal factor loadings demonstrate only small effects. It is concluded that analyses of composite differences are only warranted in conditions of full measurement invariance, and the author recommends the analyses of latent mean differences with structural equation modeling instead.


2011 ◽  
Author(s):  
Patrick J. Rosopa ◽  
Amber N. Schroeder ◽  
Jessica Doll

1993 ◽  
Vol 3 (9) ◽  
pp. 1719-1728
Author(s):  
P. Dollfus ◽  
P. Hesto ◽  
S. Galdin ◽  
C. Brisset

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