34,765 research outputs found
The inhomogeneous evolution of subgraphs and cycles in complex networks
Subgraphs and cycles are often used to characterize the local properties of
complex networks. Here we show that the subgraph structure of real networks is
highly time dependent: as the network grows, the density of some subgraphs
remains unchanged, while the density of others increase at a rate that is
determined by the network's degree distribution and clustering properties. This
inhomogeneous evolution process, supported by direct measurements on several
real networks, leads to systematic shifts in the overall subgraph spectrum and
to an inevitable overrepresentation of some subgraphs and cycles.Comment: 4 pages, 4 figures, submitted to Phys. Rev.
Comment on "Breakdown of the Internet under Intentional Attack"
We obtain the exact position of the percolation threshold in intentionally
damaged scale-free networks.Comment: 1 page, to appear in Phys. Rev. Let
Bose-Einstein condensation in complex networks
The evolution of many complex systems, including the world wide web, business
and citation networks is encoded in the dynamic web describing the interactions
between the system's constituents. Despite their irreversible and
non-equilibrium nature these networks follow Bose statistics and can undergo
Bose-Einstein condensation. Addressing the dynamical properties of these
non-equilibrium systems within the framework of equilibrium quantum gases
predicts that the 'first-mover-advantage', 'fit-get-rich' and
'winner-takes-all' phenomena observed in competitive systems are
thermodynamically distinct phases of the underlying evolving networks
Is organic farming a mitigation option? – A study on N2O emission from winter wheat
The objective of the study was to evaluate whether N2O emissions from cropping systems are affected by 1) organic versus conventional farming, 2) proportion of N2-fixing crops in the rotation and 3) use of catch crops
Giant strongly connected component of directed networks
We describe how to calculate the sizes of all giant connected components of a
directed graph, including the {\em strongly} connected one. Just to the class
of directed networks, in particular, belongs the World Wide Web. The results
are obtained for graphs with statistically uncorrelated vertices and an
arbitrary joint in,out-degree distribution . We show that if
does not factorize, the relative size of the giant strongly
connected component deviates from the product of the relative sizes of the
giant in- and out-components. The calculations of the relative sizes of all the
giant components are demonstrated using the simplest examples. We explain that
the giant strongly connected component may be less resilient to random damage
than the giant weakly connected one.Comment: 4 pages revtex, 4 figure
Search in weighted complex networks
We study trade-offs presented by local search algorithms in complex networks
which are heterogeneous in edge weights and node degree. We show that search
based on a network measure, local betweenness centrality (LBC), utilizes the
heterogeneity of both node degrees and edge weights to perform the best in
scale-free weighted networks. The search based on LBC is universal and performs
well in a large class of complex networks.Comment: 14 pages, 5 figures, 4 tables, minor changes, added a referenc
Designer Nets from Local Strategies
We propose a local strategy for constructing scale-free networks of arbitrary
degree distributions, based on the redirection method of Krapivsky and Redner
[Phys. Rev. E 63, 066123 (2001)]. Our method includes a set of external
parameters that can be tuned at will to match detailed behavior at small degree
k, in addition to the scale-free power-law tail signature at large k. The
choice of parameters determines other network characteristics, such as the
degree of clustering. The method is local in that addition of a new node
requires knowledge of only the immediate environs of the (randomly selected)
node to which it is attached. (Global strategies require information on finite
fractions of the growing net.
Majority-vote model on (3,4,6,4) and (3^4,6) Archimedean lattices
On Archimedean lattices, the Ising model exhibits spontaneous ordering. Two
examples of these lattices of the majority-vote model with noise are considered
and studied through extensive Monte Carlo simulations. The order/disorder phase
transition is observed in this system. The calculated values of the critical
noise parameter are q_c=0.091(2) and q_c=0.134(3) for (3,4,6,4) and (3^4,6)
Archimedean lattices, respectively. The critical exponents beta/nu, gamma/nu
and 1/nu for this model are 0.103(6), 1.596(54), 0.872(85) for (3,4,6,4) and
0.114(3), 1.632(35), 0.978(104) for (3^4,6) Archimedean lattices. These results
differs from the usual Ising model results and the majority-vote model on
so-far studied regular lattices or complex networks. The effective
dimensionality of the system [D_{eff}(3,4,6,4)=1.802(55) and
D_{eff}(3^4,6)=1.860(34)] for these networks are reasonably close to the
embedding dimension two.Comment: 6 pages, 7 figures in 12 eps files, RevTex
Effect of the accelerating growth of communications networks on their structure
Motivated by data on the evolution of the Internet and World Wide Web we
consider scenarios of self-organization of the nonlinearly growing networks
into free-scale structures. We find that the accelerating growth of the
networks establishes their structure. For the growing networks with
preferential linking and increasing density of links, two scenarios are
possible. In one of them, the value of the exponent of the
connectivity distribution is between 3/2 and 2. In the other, and
the distribution is necessarily non-stationary.Comment: 4 pages revtex, 3 figure
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