6,862 research outputs found
Acoustic telemetry survey of the dusky grouper (Epinephelus marginatus) in the Marine Reserve of Cerbère-Banyuls: implications on the colonization of the no protected areas
Ising spin glass models versus Ising models: an effective mapping at high temperature II. Applications to graphs and networks
By applying a recently proposed mapping, we derive exactly the upper phase
boundary of several Ising spin glass models defined over static graphs and
random graphs, generalizing some known results and providing new ones.Comment: 11 pages, 1 Postscript figur
Diffusion-annihilation processes in complex networks
We present a detailed analytical study of the
diffusion-annihilation process in complex networks. By means of microscopic
arguments, we derive a set of rate equations for the density of particles
in vertices of a given degree, valid for any generic degree distribution, and
which we solve for uncorrelated networks. For homogeneous networks (with
bounded fluctuations), we recover the standard mean-field solution, i.e. a
particle density decreasing as the inverse of time. For heterogeneous
(scale-free networks) in the infinite network size limit, we obtain instead a
density decreasing as a power-law, with an exponent depending on the degree
distribution. We also analyze the role of finite size effects, showing that any
finite scale-free network leads to the mean-field behavior, with a prefactor
depending on the network size. We check our analytical predictions with
extensive numerical simulations on homogeneous networks with Poisson degree
distribution and scale-free networks with different degree exponents.Comment: 9 pages, 5 EPS figure
Diffusion-annihilation processes in complex networks
We present a detailed analytical study of the
diffusion-annihilation process in complex networks. By means of microscopic
arguments, we derive a set of rate equations for the density of particles
in vertices of a given degree, valid for any generic degree distribution, and
which we solve for uncorrelated networks. For homogeneous networks (with
bounded fluctuations), we recover the standard mean-field solution, i.e. a
particle density decreasing as the inverse of time. For heterogeneous
(scale-free networks) in the infinite network size limit, we obtain instead a
density decreasing as a power-law, with an exponent depending on the degree
distribution. We also analyze the role of finite size effects, showing that any
finite scale-free network leads to the mean-field behavior, with a prefactor
depending on the network size. We check our analytical predictions with
extensive numerical simulations on homogeneous networks with Poisson degree
distribution and scale-free networks with different degree exponents.Comment: 9 pages, 5 EPS figure
Structure of shells in complex networks
In a network, we define shell as the set of nodes at distance
with respect to a given node and define as the fraction of nodes
outside shell . In a transport process, information or disease usually
diffuses from a random node and reach nodes shell after shell. Thus,
understanding the shell structure is crucial for the study of the transport
property of networks. For a randomly connected network with given degree
distribution, we derive analytically the degree distribution and average degree
of the nodes residing outside shell as a function of . Further,
we find that follows an iterative functional form
, where is expressed in terms of the generating
function of the original degree distribution of the network. Our results can
explain the power-law distribution of the number of nodes found in
shells with larger than the network diameter , which is the average
distance between all pairs of nodes. For real world networks the theoretical
prediction of deviates from the empirical . We introduce a
network correlation function to
characterize the correlations in the network, where is the
empirical value and is the theoretical prediction.
indicates perfect agreement between empirical results and theory. We apply
to several model and real world networks. We find that the networks
fall into two distinct classes: (i) a class of {\it poorly-connected} networks
with , which have larger average distances compared with randomly
connected networks with the same degree distributions; and (ii) a class of {\it
well-connected} networks with
Nonlocal evolution of weighted scale-free networks
We introduce the notion of globally updating evolution for a class of
weighted networks, in which the weight of a link is characterized by the amount
of data packet transport flowing through it. By noting that the packet
transport over the network is determined nonlocally, this approach can explain
the generic nonlinear scaling between the strength and the degree of a node. We
demonstrate by a simple model that the strength-driven evolution scheme
recently introduced can be generalized to a nonlinear preferential attachment
rule, generating the power-law behaviors in degree and in strength
simultaneously.Comment: 4 pages, 4 figures, final version published in PR
Reverse engineering of linking preferences from network restructuring
We provide a method to deduce the preferences governing the restructuring
dynamics of a network from the observed rewiring of the edges. Our approach is
applicable for systems in which the preferences can be formulated in terms of a
single-vertex energy function with f(k) being the contribution of a node of
degree k to the total energy, and the dynamics obeys the detailed balance. The
method is first tested by Monte-Carlo simulations of restructuring graphs with
known energies, then it is used to study variations of real network systems
ranging from the co-authorship network of scientific publications to the asset
graphs of the New York Stock Exchange. The empirical energies obtained from the
restructuring can be described by a universal function f(k) -k ln(k), which is
consistent with and justifies the validity of the preferential attachment rule
proposed for growing networks.Comment: 7 pages, 6 figures, submitted to PR
Model of correlated sequential adsorption of colloidal particles
We present results of a new model of sequential adsorption in which the
adsorbing particles are correlated with the particles attached to the
substrate. The strength of the correlations is measured by a tunable parameter
. The model interpolates between free ballistic adsorption in the limit
and a strongly correlated phase, appearing for
and characterized by the emergence of highly ordered structures. The phenomenon
is manifested through the analysis of several magnitudes, as the jamming limit
and the particle-particle correlation function. The effect of correlations in
one dimension manifests in the increased tendency to particle chaining in the
substrate. In two dimensions the correlations induce a percolation transition,
in which a spanning cluster of connected particles appears at a certain
critical value . Our study could be applicable to more general
situations in which the coupling between correlations and disorder is relevant,
as for example, in the presence of strong interparticle interactions.Comment: 6 pages, 8 EPS figures. Phys. Rev. E (in press
Halting viruses in scale-free networks
The vanishing epidemic threshold for viruses spreading on scale-free networks
indicate that traditional methods, aiming to decrease a virus' spreading rate
cannot succeed in eradicating an epidemic. We demonstrate that policies that
discriminate between the nodes, curing mostly the highly connected nodes, can
restore a finite epidemic threshold and potentially eradicate a virus. We find
that the more biased a policy is towards the hubs, the more chance it has to
bring the epidemic threshold above the virus' spreading rate. Furthermore, such
biased policies are more cost effective, requiring less cures to eradicate the
virus
Glassy behavior of electrons near metal-insulator transitions
The emergence of glassy behavior of electrons is investigated for systems
close to the disorder and/or interaction-driven metal-insulator transitions.
Our results indicate that Anderson localization effects strongly stabilize such
glassy behavior, while Mott localization tends to suppress it. We predict the
emergence of an intermediate metallic glassy phase separating the insulator
from the normal metal. This effect is expected to be most pronounced for
sufficiently disordered systems, in agreement with recent experimental
observations.Comment: Final version as published in Physical Review Letter
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