109 research outputs found
Annealed and Mean-Field formulations of Disease Dynamics on Static and Adaptive Networks
We use the annealed formulation of complex networks to study the dynamical
behavior of disease spreading on both static and adaptive networked systems.
This unifying approach relies on the annealed adjacency matrix, representing
one network ensemble, and allows to solve the dynamical evolution of the whole
network ensemble all at once. Our results accurately reproduce those obtained
by extensive numerical simulations showing a large improvement with respect to
the usual heterogeneous mean-field formulation. Moreover, by means of the
annealed formulation we derive a new heterogeneous mean-field formulation that
correctly reproduces the epidemic dynamics.Comment: 5 pages, 3 Figures. Final version published in Physical Review E
(Rapid Comm.
Immunization of Real Complex Communication Networks
Most communication networks are complex. In this paper, we address one of the
fundamental problems we are facing nowadays, namely, how we can efficiently
protect these networks. To this end, we study an immunization strategy and
found that it works as good as targeted immunization, but using only local
information about the network topology. Our findings are supported with
numerical simulations of the Susceptible-Infected-Removed (SIR) model on top of
real communication networks, where immune nodes are previously identified by a
covering algorithm. The results provide useful hints in the way to design and
deploying a digital immune system.Comment: 6 pages. To appear in the European Physical Journal B (2006
An integrative approach for modeling and simulation of Heterocyst pattern formation in Cyanobacteria strands
A comprehensive approach to cellular differentiation in cyanobacteria is
developed. To this aim, the process of heterocyst cell formation is studied
under a systems biology point of view. By relying on statistical physics
techniques, we translate the essential ingredients and mechanisms of the
genetic circuit into a set of differential equations that describes the
continuous time evolution of combined nitrogen, PatS, HetR and NtcA
concentrations. The detailed analysis of these equations gives insight into the
single cell dynamics. On the other hand, the inclusion of diffusion and noisy
conditions allows simulating the formation of heterocysts patterns in
cyanobacteria strains. The time evolution of relevant component concentrations
are calculated allowing for a comparison with experiments. Finally, we discuss
the validity and the possible improvements of the model.Comment: 20 pages (including the supporting information), 8 figure
Communicability reveals a transition to coordinated behavior in multiplex networks
We analyse the flow of information in multiplex networks by means of the communicability function. First, we generalize this measure from its definition from simple graphs to multiplex networks. Then, we study its relevance for the analysis of real-world systems by studying a social multiplex where information flows using formal/informal channels and an air transportation system where the layers represent different air companies. Accordingly, the communicability, which is essential for the good performance of these complex systems, emerges at a systemic operation point in the multiplex where the performance of the layers operates in a coordinated way very differently from the state represented by a collection of unconnected networks
Maximal-entropy random walks in complex networks with limited information
J.G.-G. was supported by MICINN through the Ramon y Cajal program and by grants FIS2008-01240 and MTM2009-13848
Nonintegrable Schrodinger Discrete Breathers
In an extensive numerical investigation of nonintegrable translational motion
of discrete breathers in nonlinear Schrodinger lattices, we have used a
regularized Newton algorithm to continue these solutions from the limit of the
integrable Ablowitz-Ladik lattice. These solutions are shown to be a
superposition of a localized moving core and an excited extended state
(background) to which the localized moving pulse is spatially asymptotic. The
background is a linear combination of small amplitude nonlinear resonant plane
waves and it plays an essential role in the energy balance governing the
translational motion of the localized core. Perturbative collective variable
theory predictions are critically analyzed in the light of the numerical
results.Comment: 42 pages, 28 figures. to be published in CHAOS (December 2004
Fear induced explosive transitions in the dynamics of corruption
In this article, we analyze a compartmental model aimed at mimicking the role of imitation and delation of corruption in social systems. In particular, the model relies on a compartmental dynamics in which individuals can transit between three states: honesty, corruption, and ostracism. We model the transitions from honesty to corruption and from corruption to ostracism as pairwise interactions. In particular, honest agents imitate corrupt peers while corrupt individuals pass to ostracism due to the delation of honest acquaintances. Under this framework, we explore the effects of introducing social intimidation in the delation of corrupt people. To this aim, we model the probability that an honest delates a corrupt agent as a decreasing function of the number of corrupt agents, thus mimicking the fear of honest individuals to reprisals by those corrupt ones. When this mechanism is absent or weak, the phase diagram of the model shows three equilibria [(i) full honesty, (ii) full corruption, and (iii) a mixed state] that are connected via smooth transitions. However, when social intimidation is strong, the transitions connecting these states turn explosive leading to a bistable phase in which a stable full corruption phase coexists with either mixed or full honesty stable equilibria. To shed light on the generality of these transitions, we analyze the model in different network substrates by means of Monte Carlo simulations and deterministic microscopic Markov chain equations. This latter formulation allows us to derive analytically the different bifurcation points that separate the different phases of the system
Intergroup information exchange drives cooperation in the public goods game
In this paperwe explore the onset of cooperative traits in the public goods game. This well-known game involves N-agent interactions and thus reproduces a large number of social scenarios in which cooperation appears to be essential. Many studies have recently addressed how the structure of the interaction patterns influences the emergence of cooperation. Here we study how information about the payoffs collected by each individual in the different groups it participates in influences the decisions made by its group partners. Our results point out that cross-information plays a fundamental and positive role in the evolution of cooperation for different versions of the public goods game and different interaction structures
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