Displaying similar documents to “Lack of Gromov-hyperbolicity in small-world networks”

Non-hyperbolicity in random regular graphs and their traffic characteristics

Gabriel Tucci (2013)

Open Mathematics

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In this paper we prove that random d-regular graphs with d ≥ 3 have traffic congestion of the order O(n logd−13 n) where n is the number of nodes and geodesic routing is used. We also show that these graphs are not asymptotically δ-hyperbolic for any non-negative δ almost surely as n → ∞.

Gromov hyperbolicity of planar graphs

Alicia Cantón, Ana Granados, Domingo Pestana, José Rodríguez (2013)

Open Mathematics

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We prove that under appropriate assumptions adding or removing an infinite amount of edges to a given planar graph preserves its non-hyperbolicity, a result which is shown to be false in general. In particular, we make a conjecture that every tessellation graph of ℝ2 with convex tiles is non-hyperbolic; it is shown that in order to prove this conjecture it suffices to consider tessellation graphs of ℝ2 such that every tile is a triangle and a partial answer to this question is given....

Segmentation in personal networks

Tom A. B. Snijders, Marinus Spreen (1997)

Mathématiques et Sciences Humaines

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A concept and several measures for segmentation of personal networks are proposed. It is argued that the implications of segmentation of personal networks are, in a sense, the opposite of those of segmentation of entire networks. The measures are illustrated by the example of the trust network in a civil service departement. For the case where relations in the personal network are observed by a sample rather than completely, estimators for the segmentation measures are given. ...

Gromov hyperbolic cubic graphs

Domingo Pestana, José Rodríguez, José Sigarreta, María Villeta (2012)

Open Mathematics

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If X is a geodesic metric space and x 1; x 2; x 3 ∈ X, a geodesic triangle T = {x 1; x 2; x 3} is the union of the three geodesics [x 1 x 2], [x 2 x 3] and [x 3 x 1] in X. The space X is δ-hyperbolic (in the Gromov sense) if any side of T is contained in a δ-neighborhood of the union of the two other sides, for every geodesic triangle T in X. We denote by δ(X) the sharp hyperbolicity constant of X, i.e., δ(X) = inf {δ ≥ 0: X is δ-hyperbolic}. We obtain information about the hyperbolicity...

Using R to Build and Assess Network Models in Biology

G. Hartvigsen (2011)

Mathematical Modelling of Natural Phenomena

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In this paper we build and analyze networks using the statistical and programming environment R and the igraph package. We investigate random, small-world, and scale-free networks and test a standard problem of connectivity on a random graph. We then develop a method to study how vaccination can alter the structure of a disease transmission network. We also discuss a variety of other uses for networks in biology.