8,908 research outputs found
Epidemic dynamics in finite size scale-free networks
Many real networks present a bounded scale-free behavior with a connectivity
cut-off due to physical constraints or a finite network size. We study epidemic
dynamics in bounded scale-free networks with soft and hard connectivity
cut-offs. The finite size effects introduced by the cut-off induce an epidemic
threshold that approaches zero at increasing sizes. The induced epidemic
threshold is very small even at a relatively small cut-off, showing that the
neglection of connectivity fluctuations in bounded scale-free networks leads to
a strong over-estimation of the epidemic threshold. We provide the expression
for the infection prevalence and discuss its finite size corrections. The
present work shows that the highly heterogeneous nature of scale-free networks
does not allow the use of homogeneous approximations even for systems of a
relatively small number of nodes.Comment: 4 pages, 2 eps figure
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
EUV and X-ray spectroheliograph study
The results of a program directed toward the definition of an EUV and X-ray spectroheliograph which has significant performance and operational improvements over the OSO-7 instrument are documented. The program investigated methods of implementing selected changes and incorporated the results of the study into a set of drawings which defines the new instrument. The EUV detector performance degradation observed during the OSO-7 mission was investigated and the most probable cause of the degradation identified
Fluctuation-driven dynamics of the Internet topology
We study the dynamics of the Internet topology based on the empirical data on
the level of the autonomous systems. It is found that the fluctuations
occurring in the stochastic process of connecting and disconnecting edges are
important features of the Internet dynamics. The network's overall growth can
be described approximately by a single characteristic degree growth rate
and the fluctuation strength , together with the vertex growth rate . A
stochastic model which incorporate these values and an adaptation rule newly
introduced reproduces several features of the real Internet topology such as
the correlations between the degrees of different vertices.Comment: Final version appeared in Phys. Rev. Let
Percolation in Hierarchical Scale-Free Nets
We study the percolation phase transition in hierarchical scale-free nets.
Depending on the method of construction, the nets can be fractal or small-world
(the diameter grows either algebraically or logarithmically with the net size),
assortative or disassortative (a measure of the tendency of like-degree nodes
to be connected to one another), or possess various degrees of clustering. The
percolation phase transition can be analyzed exactly in all these cases, due to
the self-similar structure of the hierarchical nets. We find different types of
criticality, illustrating the crucial effect of other structural properties
besides the scale-free degree distribution of the nets.Comment: 9 Pages, 11 figures. References added and minor corrections to
manuscript. In pres
Jamming during the discharge of granular matter from a silo
In this work we present an experimental study of the jamming that stops the
free flow of grains from a silo discharging by gravity. When the outlet size is
not much bigger than the beads, granular material jams the outlet of the
container due to the formation of an arch. Statistical data from the number of
grains fallen between consecutive jams are presented. The information that they
provide can help to understand the jamming phenomenon. As the ratio between the
size of the orifice and the size of the beads is increased, the probability
that an arch blocks the outlet decreases. We show here that there is a power
law divergence of the mean avalanche size for a finite critical radius. Beyond
this critical radius no jamming can occur and the flow is never stopped. The
dependence of the arch formation on the shape and the material of the grains
has been explored. It has been found that the material properties of the grains
do not affect the arch formation probability. On the contrary, the shape of the
grains deeply influences it. A simple model to interpret the results is also
discussed.Comment: Submitted to Phys. Rev.
Computational complexity arising from degree correlations in networks
We apply a Bethe-Peierls approach to statistical-mechanics models defined on
random networks of arbitrary degree distribution and arbitrary correlations
between the degrees of neighboring vertices. Using the NP-hard optimization
problem of finding minimal vertex covers on these graphs, we show that such
correlations may lead to a qualitatively different solution structure as
compared to uncorrelated networks. This results in a higher complexity of the
network in a computational sense: Simple heuristic algorithms fail to find a
minimal vertex cover in the highly correlated case, whereas uncorrelated
networks seem to be simple from the point of view of combinatorial
optimization.Comment: 4 pages, 1 figure, accepted in Phys. Rev.
Topology and correlations in structured scale-free networks
We study a recently introduced class of scale-free networks showing a high
clustering coefficient and non-trivial connectivity correlations. We find that
the connectivity probability distribution strongly depends on the fine details
of the model. We solve exactly the case of low average connectivity, providing
also exact expressions for the clustering and degree correlation functions. The
model also exhibits a lack of small world properties in the whole parameters
range. We discuss the physical properties of these networks in the light of the
present detailed analysis.Comment: 10 pages, 9 figure
Weighted evolving networks: coupling topology and weights dynamics
We propose a model for the growth of weighted networks that couples the
establishment of new edges and vertices and the weights' dynamical evolution.
The model is based on a simple weight-driven dynamics and generates networks
exhibiting the statistical properties observed in several real-world systems.
In particular, the model yields a non-trivial time evolution of vertices'
properties and scale-free behavior for the weight, strength and degree
distributions.Comment: 4 pages, 4 figure
Statistical Agent Based Modelization of the Phenomenon of Drug Abuse
We introduce a statistical agent based model to describe the phenomenon of
drug abuse and its dynamical evolution at the individual and global level. The
agents are heterogeneous with respect to their intrinsic inclination to drugs,
to their budget attitude and social environment. The various levels of drug use
were inspired by the professional description of the phenomenon and this
permits a direct comparison with all available data. We show that certain
elements have a great importance to start the use of drugs, for example the
rare events in the personal experiences which permit to overcame the barrier of
drug use occasionally. The analysis of how the system reacts to perturbations
is very important to understand its key elements and it provides strategies for
effective policy making. The present model represents the first step of a
realistic description of this phenomenon and can be easily generalized in
various directions.Comment: 12 pages, 5 figure
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