1,779 research outputs found
Inhomogeneous percolation models for spreading phenomena in random graphs
Percolation theory has been largely used in the study of structural
properties of complex networks such as the robustness, with remarkable results.
Nevertheless, a purely topological description is not sufficient for a correct
characterization of networks behaviour in relation with physical flows and
spreading phenomena taking place on them. The functionality of real networks
also depends on the ability of the nodes and the edges in bearing and handling
loads of flows, energy, information and other physical quantities. We propose
to study these properties introducing a process of inhomogeneous percolation,
in which both the nodes and the edges spread out the flows with a given
probability.
Generating functions approach is exploited in order to get a generalization
of the Molloy-Reed Criterion for inhomogeneous joint site bond percolation in
correlated random graphs. A series of simple assumptions allows the analysis of
more realistic situations, for which a number of new results are presented. In
particular, for the site percolation with inhomogeneous edge transmission, we
obtain the explicit expressions of the percolation threshold for many
interesting cases, that are analyzed by means of simple examples and numerical
simulations. Some possible applications are debated.Comment: 28 pages, 11 figure
Hierarchical models of rigidity percolation
We introduce models of generic rigidity percolation in two dimensions on
hierarchical networks, and solve them exactly by means of a renormalization
transformation. We then study how the possibility for the network to self
organize in order to avoid stressed bonds may change the phase diagram. In
contrast to what happens on random graphs and in some recent numerical studies
at zero temperature, we do not find a true intermediate phase separating the
usual rigid and floppy ones.Comment: 20 pages, 8 figures. Figures improved, references added, small
modifications. Accepted in Phys. Rev.
Optimal Path and Minimal Spanning Trees in Random Weighted Networks
We review results on the scaling of the optimal path length in random
networks with weighted links or nodes. In strong disorder we find that the
length of the optimal path increases dramatically compared to the known small
world result for the minimum distance. For Erd\H{o}s-R\'enyi (ER) and scale
free networks (SF), with parameter (), we find that the
small-world nature is destroyed. We also find numerically that for weak
disorder the length of the optimal path scales logaritmically with the size of
the networks studied. We also review the transition between the strong and weak
disorder regimes in the scaling properties of the length of the optimal path
for ER and SF networks and for a general distribution of weights, and suggest
that for any distribution of weigths, the distribution of optimal path lengths
has a universal form which is controlled by the scaling parameter
where plays the role of the disorder strength, and
is the length of the optimal path in strong disorder. The
relation for is derived analytically and supported by numerical
simulations. We then study the minimum spanning tree (MST) and show that it is
composed of percolation clusters, which we regard as "super-nodes", connected
by a scale-free tree. We furthermore show that the MST can be partitioned into
two distinct components. One component the {\it superhighways}, for which the
nodes with high centrality dominate, corresponds to the largest cluster at the
percolation threshold which is a subset of the MST. In the other component,
{\it roads}, low centrality nodes dominate. We demonstrate the significance
identifying the superhighways by showing that one can improve significantly the
global transport by improving a very small fraction of the network.Comment: review, accepted at IJB
Numerical evaluation of the upper critical dimension of percolation in scale-free networks
We propose a numerical method to evaluate the upper critical dimension
of random percolation clusters in Erd\H{o}s-R\'{e}nyi networks and in
scale-free networks with degree distribution ,
where is the degree of a node and is the broadness of the degree
distribution. Our results report the theoretical prediction, for scale-free networks with and
for Erd\H{o}s-R\'{e}nyi networks and scale-free networks with .
When the removal of nodes is not random but targeted on removing the highest
degree nodes we obtain for all . Our method also yields
a better numerical evaluation of the critical percolation threshold, , for
scale-free networks. Our results suggest that the finite size effects increases
when approaches 3 from above.Comment: 10 pages, 5 figure
On the freezing of variables in random constraint satisfaction problems
The set of solutions of random constraint satisfaction problems (zero energy
groundstates of mean-field diluted spin glasses) undergoes several structural
phase transitions as the amount of constraints is increased. This set first
breaks down into a large number of well separated clusters. At the freezing
transition, which is in general distinct from the clustering one, some
variables (spins) take the same value in all solutions of a given cluster. In
this paper we study the critical behavior around the freezing transition, which
appears in the unfrozen phase as the divergence of the sizes of the
rearrangements induced in response to the modification of a variable. The
formalism is developed on generic constraint satisfaction problems and applied
in particular to the random satisfiability of boolean formulas and to the
coloring of random graphs. The computation is first performed in random tree
ensembles, for which we underline a connection with percolation models and with
the reconstruction problem of information theory. The validity of these results
for the original random ensembles is then discussed in the framework of the
cavity method.Comment: 32 pages, 7 figure
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