Equivalent-circuit, scaling, random-walk simulation, and an experimental study of self-similar fractal electrodes and interfaces

1993 ◽  
Vol 48 (5) ◽  
pp. 3333-3344 ◽  
Author(s):  
B. Sapoval ◽  
R. Gutfraind ◽  
P. Meakin ◽  
M. Keddam ◽  
H. Takenouti
Keyword(s):  
Experimental Study ◽  
Random Walk ◽  
Equivalent Circuit ◽  
Self Similar ◽  
Random Walk Simulation

An Approach Toward Emulating Molecular Interaction with a Graph

2006 ◽  
Vol 59 (12) ◽  
pp. 869 ◽  
Author(s):  
Hideaki Suzuki
Keyword(s):  
Random Walk ◽  
Molecular Interaction ◽  
Hard Sphere ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Atomic Clusters ◽  
Experimental Results ◽  
Random Walk Simulation ◽  
Mathematical Graph ◽  
Three Dimensional Space

Network artificial chemistry (NAC) uses a mathematical graph to emulate molecular interaction in a solvent. To emulate molecules' movement in a three-dimensional space, rewiring rules for NAC graphs’ edges must be designed to enable the edges to imitate the relations between molecules or atomic clusters. Our research formulated the ‘network energy’ representing this constraint and rewired the NAC graph to minimize the required energy. Experimental results for the NAC rewiring are compared with a hard-sphere random walk simulation.

Random-walk simulation of the dielectric constant of a composite material

1990 ◽  
Vol 42 (8) ◽  
pp. 5342-5344 ◽  
Author(s):  
R. I. Cukier ◽  
S. Y. Sheu ◽  
J. Tobochnik
Keyword(s):  
Dielectric Constant ◽  
Composite Material ◽  
Random Walk ◽  
Random Walk Simulation

Random-walk simulation of diffusion-controlled processes among static traps

1989 ◽  
Vol 39 (16) ◽  
pp. 11833-11839 ◽  
Author(s):  
Sang Bub Lee ◽  
In Chan Kim ◽  
C. A. Miller ◽  
S. Torquato
Keyword(s):  
Random Walk ◽  
Controlled Processes ◽  
Diffusion Controlled ◽  
Random Walk Simulation

"MÜNCHHAUSEN TRICK" AND AMENABILITY OF SELF-SIMILAR GROUPS

2005 ◽  
Vol 15 (05n06) ◽  
pp. 907-937 ◽  
Author(s):  
VADIM A. KAIMANOVICH
Keyword(s):  
Random Walk ◽  
Probability Measure ◽  
Group Identity ◽  
Convex Combination ◽  
Similar Group ◽  
Grigorchuk Group ◽  
Intermediate Growth ◽  
Group A ◽  
Self Similar ◽  
Asymptotic Entropy

The structure of a self-similar group G naturally gives rise to a transformation which assigns to any probability measure μ on G and any vertex w in the action tree of the group a new probability measure μw. If the measure μ is self-similar in the sense that μw is a convex combination of μ and the δ-measure at the group identity, then the asymptotic entropy of the random walk (G, μ) vanishes; therefore, the random walk is Liouville and the group G is amenable. We construct self-similar measures on several classes of self-similar groups, including the Grigorchuk group of intermediate growth.

Multiple Random Walk Simulation: A Fast Method to Map Grade Uncertainty with Large Datasets

2016 ◽  
Vol 26 (2) ◽  
pp. 213-221 ◽  
Author(s):  
Rafael Moniz Caixeta ◽  
Diniz Tamantini Ribeiro ◽  
João Felipe Coimbra Leite Costa ◽  
Péricles Lopes Machado
Keyword(s):  
Random Walk ◽  
Large Datasets ◽  
Fast Method ◽  
Random Walk Simulation ◽  
Grade Uncertainty

A random walk simulation of flow injection analysis

1984 ◽  
Vol 165 ◽  
pp. 227-236 ◽  
Author(s):  
D. Betteridge ◽  
C.Z. Marczewski ◽  
A.P. Wade
Keyword(s):  
Random Walk ◽  
Flow Injection ◽  
Flow Injection Analysis ◽  
Random Walk Simulation
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