scholarly journals Maximal Clusters in Non-Critical Percolation and Related Models

2006 ◽  
Vol 122 (4) ◽  
pp. 671-703 ◽  
Author(s):  
Remco van Der Hofstad ◽  
Frank Redig
Keyword(s):  
Critical Percolation ◽  
Maximal Clusters

Estimates of critical percolation probabilities for a set of two-dimensional lattices

1972 ◽  
Vol 71 (1) ◽  
pp. 97-106 ◽  
Author(s):  
D. G. Neal
Keyword(s):  
Monte Carlo ◽  
Two Dimensions ◽  
Two Dimensional ◽  
Critical Percolation ◽  
Site Percolation

AbstractThis paper describes new detailed Monte Carlo investigations into bond and site percolation problems on the set of eleven regular and semi-regular (Archimedean) lattices in two dimensions.

scholarly journals A PERCOLATION MODEL OF DIAGENESIS

2002 ◽  
Vol 13 (03) ◽  
pp. 319-331 ◽  
Author(s):  
S. S. MANNA ◽  
T. DATTA ◽  
R. KARMAKAR ◽  
S. TARAFDAR
Keyword(s):  
Numerical Simulation ◽  
Critical Behavior ◽  
Sedimentary Rocks ◽  
Two Dimensions ◽  
Percolation Model ◽  
Type Model ◽  
Stable Configuration ◽  
Critical Percolation ◽  
Restructuring Process ◽  
Simulation Results

The restructuring process of diagenesis in the sedimentary rocks is studied using a percolation type model. The cementation and dissolution processes are modeled by the culling of occupied sites in rarefied and growth of vacant sites in dense environments. Starting from sub-critical states of ordinary percolation the system evolves under the diagenetic rules to critical percolation configurations. Our numerical simulation results in two dimensions indicate that the stable configuration has the same critical behavior as the ordinary percolation.

scholarly journals Decomposable Convexities in Graphs and Hypergraphs

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Francesco M. Malvestuto
Keyword(s):  
Convex Hull ◽  
Convex Sets ◽  
Nonempty Subset ◽  
Convex Set ◽  
Convex Geometry ◽  
Convexity Space ◽  
Vertex Set ◽  
Convex Geometries ◽  
Acyclic Hypergraph ◽  
Maximal Clusters

Given a connected hypergraph with vertex set V, a convexity space on is a subset of the powerset of V that contains ∅, V, and the singletons; furthermore, is closed under intersection and every set in is connected in . The members of are called convex sets. The convex hull of a subset X of V is the smallest convex set containing X. By a cluster of we mean any nonempty subset of V in which every two vertices are separated by no convex set. We say that a convexity space on is decomposable if it satisfies the following three axioms: (i) the maximal clusters of form an acyclic hypergraph, (ii) every maximal cluster of is a convex set, and (iii) for every nonempty vertex set X, a vertex does not belong to the convex hull of X if and only if it is separated from X by a convex cluster. We prove that a decomposable convexity space on is fully specified by the maximal clusters of in that (1) there is a closed formula which expresses the convex hull of a set in terms of certain convex clusters of and (2) is a convex geometry if and only if the subspaces of induced by maximal clusters of are all convex geometries. Finally, we prove the decomposability of some known convexities in graphs and hypergraphs taken from the literature (such as “monophonic” and “canonical” convexities in hypergraphs and “all-paths” convexity in graphs).

scholarly journals Loewner driving functions for off-critical percolation clusters

2009 ◽  
Vol 80 (5) ◽  
Author(s):  
Yoichiro Kondo ◽  
Namiko Mitarai ◽  
Hiizu Nakanishi
Keyword(s):  
Critical Percolation ◽  
Percolation Clusters

Lower bounds for the critical probability in percolation models with oriented bonds

1980 ◽  
Vol 17 (04) ◽  
pp. 979-986 ◽  
Author(s):  
Lawrence Gray ◽  
John C. Wierman ◽  
R. T. Smythe
Keyword(s):  
Lower Bounds ◽  
Oriented Percolation ◽  
Critical Probability ◽  
Critical Percolation ◽  
Simple Method

In completely or partially oriented percolation models, a conceptually simple method, using barriers to enclose all open paths from the origin, improves the best previous lower bounds for the critical percolation probabilities.

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