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Within the framework of Game Theory, contests study decision-making in those situations or conflicts when rewards depend on the relative rank between contenders rather than their absolute performance. By relying on the formalism of Tullock success functions, we propose a model where two contenders fight in a conflict on two fronts with different technology levels associated: a front with large resource demand and another with lower resource requirements. The parameter of the success function in each front determines the resource demand level. Furthermore, the redistribution or not of resources after a tie defines two different games. We solve the model analytically through the best-response map dynamics, finding a critical threshold for the ratio of the resources between contenders that determines the Nash Equilibrium basin and, consequently, the peace and fighting regimes. We also perform numerical simulations that corroborate and extend these findings. We hope this study will be of interest to areas as diverse as economic conflicts and geopolitics., Comment: 21 pages, 11 figures

Elucidating the mechanisms that lead to cooperation is still one of the main scientific challenges of current times, as many common cooperative scenarios remain elusive and at odds with Darwin's natural selection theory. Here, we study evolutionary games on populations that are structured beyond pairwise interactions. Specifically, we introduce a general evolutionary approach that allows studying situations in which indirect interactions via a neighbor other than the direct pairwise connection (or via a group of neighbors), impact the strategy of the focal player. To this end, we consider simplicial graphs that encode two- and three-body interactions, which enables to study competition between all possible pairs of social dilemmas and to scrutinize the role of three-body interactions in all the observed phenomenology. We simultaneously investigate how social dilemma with different Nash equilibria compete in simplicial structures and how such a competition is modulated by the unbalance of 2- and 1-simplices, which in its turn reflects the relative prevalence of pairwise or group interactions among the players. We report a number of results that: (i) support that higher-order games allow for non-dominant strategists to emerge and coexist with dominant ones, a scenario that can't be explained by any pairwise schemes, no matter the network of contacts; (ii) characterize a novel transition from dominant defection to dominant cooperation as a function of the simplicial structure of the population; and (iii) demonstrate that 2-simplex interactions are a source of strategy diversity, i.e. increasing the relative prevalence of group interactions always promotes diverse strategic identities of individuals. Our study constitutes a step forward in the quest for understanding the roots of cooperation and the mechanisms that sustain it in real-world and social environments., Comment: 9 pages and 6 figures. Submitted for publication

A projective network model is a model that enables predictions to be made based on a subsample of the network data, with the predictions remaining unchanged if a larger sample is taken into consideration. An exchangeable model is a model that does not depend on the order in which nodes are sampled. Despite a large variety of non-equilibrium (growing) and equilibrium (static) sparse complex network models that are widely used in network science, how to reconcile sparseness (constant average degree) with the desired statistical properties of projectivity and exchangeability is currently an outstanding scientific problem. Here we propose a network process with hidden variables which is projective and can generate sparse power-law networks. Despite the model not being exchangeable, it can be closely related to exchangeable uncorrelated networks as indicated by its information theory characterization and its network entropy. The use of the proposed network process as a null model is here tested on real data, indicating that the model offers a promising avenue for statistical network modelling., Comment: (26 pages 2 figures)

We study a pulse-coupled dynamics of excitable elements in uncorrelated scale-free networks. Regimes of self-sustained activity are found for homogeneous and inhomogeneous couplings, in which the system displays a wide variety of behaviors, including periodic and irregular global spiking signals, as well as coherent oscillations, an unexpected form of synchronization. Our numerical results also show that the properties of the population firing rate depend on the size of the system, particularly its structure and average value over time. However, a few straightforward dynamical and topological strategies can be introduced to enhance or hinder these global behaviors, rendering a scenario where signal control is attainable, which incorporates a basic mechanism to turn off the dynamics permanently. As our main result, here we present a framework to estimate, in the stationary state, the mean firing rate over a long time window and to decompose the global dynamics into average values of the inter-spike-interval of each connectivity group. Our approach provides accurate predictions of these average quantities when the network exhibits high heterogeneity, a remarkable finding that is not restricted exclusively to the scale-free topology., Comment: Working paper, 13 pages, 13 figures

Multilayer networks have been the subject of intense research during the last few years, as they represent better the interdependent nature of many real world systems. Here, we address the question of describing the three different structural phases in which a multiplex network might exist. We show that each phase can be characterized by the presence of gaps in the spectrum of the supra-Laplacian of the multiplex network. We therefore unveil the existence of different topological scales in the system, whose relation characterizes each phase. Moreover, by capitalizing on the coarse-grained representation that is given in terms of quotient graphs, we explain the mechanisms that produce those gaps as well as their dynamical consequences., Comment: 6 pages and 4 Figures. Final version. To appear in PRE

We study the generation of propagation invariant photons with orbital angular momentum by spontaneous parametric down conversion (SPDC) using a Bessel-Gauss pump beam. The angular and conditional angular spectra are calculated for an uniaxial crystal optimized for type I SPDC with standard Gaussian pump beams. It is shown that, as the mean value of the magnitude of the transverse wave vector of the pump beam increases, the emission cone is deformed into two non coaxial cones that touch each other along a line determined by the orientation of the optical axis of the nonlinear crystal. At this location, the conditional spectrum becomes maximal for a pair of photons, one of which is best described by a Gaussian-like photon with a very small transverse wave vector, and the othera Bessel-Gauss photon with a distribution of transverse wave vectors similar in amplitude to that of the incident pump beam. A detailed analysis is then performed of the angular momentum content of SPDC photons by the evaluation of the corresponding transition amplitudes. As a result, we obtain conditions for the generation of heralded single photons which are approximately propagation invariant and have orbital angular momentum. A discussion is given about the difficulties in the interpretation of the results in terms of conservation of optical orbital angular momentum along the vector normal to the crystal surface. The angular spectra and the conditional angular spectra are successfully compared with available experimental data recently reported in the literature., Comment: 13 pages, 5 figures

In this paper we study the generation of photon pairs through the process of spontaneous four wave mixing (SFWM) in a $\chi^{(3)}$ cavity. Our key interest is the generation of photon pairs in a guided-wave configuration - fiber or waveguide - where at least one of the photons in a given pair is matched in frequency and bandwidth to a particular atomic transition, as required for the implementation of photon-atom interfaces. We present expressions, along with plots, for the two-photon joint intensity both in the spectral and temporal domains. We also present expressions for the absolute brightness, along with numerical simulations, and show that the presence of the cavity can result in a flux enhancement relative to an equivalent source without a cavity.

In the framework of the evolutionary dynamics of the Prisoner's Dilemma game on complex networks, we investigate the possibility that the average level of cooperation shows hysteresis under quasi-static variations of a model parameter (the "temptation to defect"). Under the "discrete replicator" strategy updating rule, for both Erdos-Renyi and Barabasi-Albert graphs we observe cooperation hysteresis cycles provided one reaches tipping point values of the parameter; otherwise, perfect reversibility is obtained. The selective fixation of cooperation at certain nodes and its organization in cooperator clusters, that are surrounded by fluctuating strategists, allows the rationalization of the "lagging behind" behavior observed., Comment: 6 pages, 5 figures

We develop a theoretical framework for the study of epidemic-like social contagion in large scale social systems. We consider the most general setting in which different communication platforms or categories form multiplex networks. Specifically, we propose a contact-based information spreading model, and show that the critical point of the multiplex system associated to the active phase is determined by the layer whose contact probability matrix has the largest eigenvalue. The framework is applied to a number of different situations, including a real multiplex system. Finally, we also show that when the system through which information is disseminating is inherently multiplex, working with the graph that results from the aggregation of the different layers is flawed., Comment: 5 pages and 3 figures. Final version to appear in PRE RC

Critical phenomena in complex networks, and the emergence of dynamical abrupt transitions in the macroscopic state of the system are currently a subject of the outmost interest. We report evidence of an explosive phase synchronization in networks of chaotic units. Namely, by means of both extensive simulations of networks made up of chaotic units, and validation with an experiment of electronic circuits in a star configuration, we demonstrate the existence of a first order transition towards synchronization of the phases of the networked units. Our findings constitute the first prove of this kind of synchronization in practice, thus opening the path to its use in real-world applications., Comment: Phys. Rev. Lett. in press

In this Brief Report we study the evolutionary dynamics of the Public Goods Game in a population of mobile agents embedded in a 2-dimensional space. In this framework, the backbone of interactions between agents changes in time, allowing us to study the impact that mobility has on the emergence of cooperation in structured populations. We compare our results with a static case in which agents interact on top of a Random Geometric Graph. Our results point out that a low degree of mobility enhances the onset of cooperation in the system while a moderate velocity favors the fixation of the full-cooperative state., Comment: 5 pages, 4 figures

The topological analysis of biological networks has been a prolific topic in network science during the last decade. A persistent problem with this approach is the inherent uncertainty and noisy nature of the data. One of the cases in which this situation is more marked is that of transcriptional regulatory networks (TRNs) in bacteria. The datasets are incomplete because regulatory pathways associated to a relevant fraction of bacterial genes remain unknown. Furthermore, direction, strengths and signs of the links are sometimes unknown or simply overlooked. Finally, the experimental approaches to infer the regulations are highly heterogeneous, in a way that induces the appearance of systematic experimental-topological correlations. And yet, the quality of the available data increases constantly. In this work we capitalize on these advances to point out the influence of data (in)completeness and quality on some classical results on topological analysis of TRNs, specially regarding modularity at different levels. In doing so, we identify the most relevant factors affecting the validity of previous findings, highlighting important caveats to future prokaryotic TRNs topological analysis., Comment: Supplementary Material is available on request

Up to now, the effects of having heterogeneous networks of contacts have been studied mostly for diseases which are not persistent in time, i.e., for diseases where the infectious period can be considered very small compared to the lifetime of an individual. Moreover, all these previous results have been obtained for closed populations, where the number of individuals does not change during the whole duration of the epidemics. Here, we go one step further and analyze, both analytically and numerically, a radically different kind of diseases: those that are persistent and can last for an individual's lifetime. To be more specific, we particularize to the case of Tuberculosis' (TB) infection dynamics, where the infection remains latent for a period of time before showing up and spreading to other individuals. We introduce an epidemiological model for TB-like persistent infections taking into account the heterogeneity inherent to the population structure. This sort of dynamics introduces new analytical and numerical challenges that we are able to sort out. Our results show that also for persistent diseases the epidemic threshold depends on the ratio of the first two moments of the degree distribution so that it goes to zero in a class of scale-free networks when the system approaches the thermodynamic limit., Comment: 12 pages and 2 figures. Revtex format. Submitted for publication.

The use of {\it dyadic interaction} between agents, in combination with {\it homophily} (the principle that ``likes attract'') in the Axelrod model for the study of cultural dissemination has two important problems: the prediction of monoculture in large societies and an extremely narrow window of noise levels in which diversity with local convergence is obtained. Recently, the inclusion of {\it social influence} has proven to overcome them (A. Flache and M. W. Macey, arXiv:0808.2710). Here we extend the Axelrod model with social influence interaction for the study of Mass Media effects through the inclusion of a super-agent which acts over the whole system and has nonnull overlap with each agent of the society. The dependence with different parameters as the initial social diversity, size effects, Mass Media strength and noise is outlined. Our results might be relevant in several socio-economic contexts and for the study of the emergence of collective behavior in complex social systems., Comment: Revtex preprint, 21 pages, 5 Figures

The study of complex networks sheds light on the relation between the structure and function of complex systems. One remarkable result is the absence of an epidemic threshold in infinite-size scale-free networks, which implies that any infection will perpetually propagate regardless of the spreading rate. The vast majority of current theoretical approaches assumes that infections are transmitted as a reaction process from nodes to all neighbors. Here we adopt a different perspective and show that the epidemic incidence is shaped by traffic flow conditions. Specifically, we consider the scenario in which epidemic pathways are defined and driven by flows. Through extensive numerical simulations and theoretical predictions, it is shown that the value of the epidemic threshold in scale-free networks depends directly on flow conditions, in particular on the first and second moments of the betweenness distribution given a routing protocol. We consider the scenarios in which the delivery capability of the nodes is bounded or unbounded. In both cases, the threshold values depend on the traffic and decrease as flow increases. Bounded delivery provokes the emergence of congestion, slowing down the spreading of the disease and setting a limit for the epidemic incidence. Our results provide a general conceptual framework to understand spreading processes on complex networks., Comment: Final version to be published in Proceedings of the National Academy of Sciences USA

We discuss a model for evolutionary game dynamics in a growing, network-structured population. In our model, new players can either make connections to random preexisting players or preferentially attach to those that have been successful in the past. The latter depends on the dynamics of strategies in the game, which we implement following the so-called Fermi rule such that the limits of weak and strong strategy selection can be explored. Our framework allows to address general evolutionary games. With only two parameters describing the preferential attachment and the intensity of selection, we describe a wide range of network structures and evolutionary scenarios. Our results show that even for moderate payoff preferential attachment, over represented hubs arise. Interestingly, we find that while the networks are growing, high levels of cooperation are attained, but the same network structure does not promote cooperation as a static network. Therefore, the mechanism of payoff preferential attachment is different to those usually invoked to explain the promotion of cooperation in static, already-grown networks., Comment: 18 pages. IOP style. To appear in New Journal of Physics

In the Axelrod's model of cultural dissemination, we consider mobility of cultural agents through the introduction of a density of empty sites and the possibility that agents in a dissimilar neighborhood can move to them if their mean cultural similarity with the neighborhood is below some threshold. While for low values of the density of empty sites the mobility enhances the convergence to a global culture, for high enough values of it the dynamics can lead to the coexistence of disconnected domains of different cultures. In this regime, the increase of initial cultural diversity paradoxically increases the convergence to a dominant culture. Further increase of diversity leads to fragmentation of the dominant culture into domains, forever changing in shape and number, as an effect of the never ending eroding activity of cultural minorities.

Many epidemic processes in networks spread by stochastic contacts among their connected vertices. There are two limiting cases widely analyzed in the physics literature, the so-called contact process (CP) where the contagion is expanded at a certain rate from an infected vertex to one neighbor at a time, and the reactive process (RP) in which an infected individual effectively contacts all its neighbors to expand the epidemics. However, a more realistic scenario is obtained from the interpolation between these two cases, considering a certain number of stochastic contacts per unit time. Here we propose a discrete-time formulation of the problem of contact-based epidemic spreading. We resolve a family of models, parameterized by the number of stochastic contact trials per unit time, that range from the CP to the RP. In contrast to the common heterogeneous mean-field approach, we focus on the probability of infection of individual nodes. Using this formulation, we can construct the whole phase diagram of the different infection models and determine their critical properties., Comment: 6 pages, 4 figures. Europhys Lett (in press 2010)

We address the problem of how the survival of cooperation in a social system depends on the motion of the individuals. Specifically, we study a model in which Prisoner's Dilemma players are allowed to move in a two-dimensional plane. Our results show that cooperation can survive in such a system provided that both the temptation to defect and the velocity at which agents move are not too high. Moreover, we show that when these conditions are fulfilled, the only asymptotic state of the system is that in which all players are cooperators. Our results might have implications for the design of cooperative strategies in motion coordination and other applications including wireless networks., Comment: 4 pages with 4 figures. APS format. Final version to be published in PRE

In this paper we study the cooperative behavior of agents playing the Prisoner's Dilemma game in random scale-free networks. We show that the survival of cooperation is enhanced with respect to random homogeneous graphs but, on the other hand, decreases when compared to that found in Barab\'asi-Albert scale-free networks. We show that the latter decrease is related with the structure of cooperation. Additionally, we present a mean field approximation for studying evolutionary dynamics in networks with no degree-degree correlations and with arbitrary degree distribution. The mean field approach is similar to the one used for describing the disease spreading in complex networks, making a further compartmentalization of the strategists partition into degree-classes. We show that this kind of approximation is suitable to describe the behavior of the system for a particular set of initial conditions, such as the placement of cooperators in the higher-degree classes, while it fails to reproduce the level of cooperation observed in the numerical simulations for arbitrary initial configurations., Comment: 7 pages, 4 figures

We introduce a general stochastic model for the spread of rumours, and derive mean-field equations that describe the dynamics of the model on complex social networks (in particular those mediated by the Internet). We use analytical and numerical solutions of these equations to examine the threshold behavior and dynamics of the model on several models of such networks: random graphs, uncorrelated scale-free networks and scale-free networks with assortative degree correlations. We show that in both homogeneous networks and random graphs the model exhibits a critical threshold in the rumour spreading rate below which a rumour cannot propagate in the system. In the case of scale-free networks, on the other hand, this threshold becomes vanishingly small in the limit of infinite system size. We find that the initial rate at which a rumour spreads is much higher in scale-free networks than in random graphs, and that the rate at which the spreading proceeds on scale-free networks is further increased when assortative degree correlations are introduced. The impact of degree correlations on the final fraction of nodes that ever hears a rumour, however, depends on the interplay between network topology and the rumour spreading rate. Our results show that scale-free social networks are prone to the spreading of rumours, just as they are to the spreading of infections. They are relevant to the spreading dynamics of chain emails, viral advertising and large-scale information dissemination algorithms on the Internet.

In Evolutionary Dynamics the understanding of cooperative phenomena in natural and social systems has been the subject of intense research during decades. We focus attention here on the so-called "Lattice Reciprocity" mechanisms that enhance evolutionary survival of the cooperative phenotype in the Prisoner's Dilemma game when the population of darwinian replicators interact through a fixed network of social contacts. Exact results on a "Dipole Model" are presented, along with a mean-field analysis as well as results from extensive numerical Monte Carlo simulations. The theoretical framework used is that of standard Statistical Mechanics of macroscopic systems, but with no energy considerations. We illustrate the power of this perspective on social modeling, by consistently interpreting the onset of lattice reciprocity as a thermodynamical phase transition that, moreover, cannot be captured by a purely mean-field approach., Comment: 10 pages. APS style

In spite of its relevance to the origin of complex networks, the interplay between form and function and its role during network formation remains largely unexplored. While recent studies introduce dynamics by considering rewiring processes of a pre-existent network, we study network growth and formation by proposing an evolutionary preferential attachment model, its main feature being that the capacity of a node to attract new links depends on a dynamical variable governed in turn by the node interactions. As a specific example, we focus on the problem of the emergence of cooperation by analyzing the formation of a social network with interactions given by the Prisoner's Dilemma. The resulting networks show many features of real systems, such as scale-free degree distributions, cooperative behavior and hierarchical clustering. Interestingly, results such as the cooperators being located mostly on nodes of intermediate degree are very different from the observations of cooperative behavior on static networks. The evolutionary preferential attachment mechanism points to an evolutionary origin of scale-free networks and may help understand similar feedback problems in the dynamics of complex networks by appropriately choosing the game describing the interaction of nodes., Comment: 6 pages and 4 figures, APS format. Submitted for publication

We propose a model of random diffusion to investigate flow fluctuations in complex networks. We derive an analytical law showing that the dependence of fluctuations with the mean traffic in a network is ruled by the delicate interplay of three factors, respectively of dynamical, topological and statistical nature. In particular, we demonstrate that the existence of a power-law scaling characterizing the flow fluctuations at every node in the network can not be claimed for. We show the validity of this scaling breakdown under quite general topological and dynamical situations by means of different traffic algorithms and by analyzing real data., Comment: Final version appeared in PRL. Minor changes with respect to the previous version

The spread of sexually transmitted diseases (e.g. Chlamydia, Syphilis, Gonorrhea, HIV) across populations is a major concern for scientists and health agencies. In this context, both data collection on sexual contact networks and the modeling of disease spreading, are intensively contributing to the search for effective immunization policies. Here, the spreading of sexually transmitted diseases on bipartite scale-free graphs, representing heterosexual contact networks, is considered. We analytically derive the expression for the epidemic threshold and its dependence with the system size in finite populations. We show that the epidemic outbreak in bipartite populations, with number of sexual partners distributed as in empirical observations from national sex surveys, takes place for larger spreading rates than for the case in which the bipartite nature of the network is not taken into account. Numerical simulations confirm the validity of the theoretical results. Our findings indicate that the restriction to crossed infections between the two classes of individuals (males and females) has to be taken into account in the design of efficient immunization strategies for sexually transmitted diseases., Comment: 7 pages, 3 figures and 2 tables

Recent studies on the evolutionary dynamics of the Prisoner's Dilemma game in scale-free networks have demonstrated that the heterogeneity of the network interconnections enhances the evolutionary success of cooperation. In this paper we address the issue of how the characterization of the asymptotic states of the evolutionary dynamics depends on the initial concentration of cooperators. We find that the measure and the connectedness properties of the set of nodes where cooperation reaches fixation is largely independent of initial conditions, in contrast with the behavior of both the set of nodes where defection is fixed, and the fluctuating nodes. We also check for the robustness of these results when varying the degree heterogeneity along a one-parametric family of networks interpolating between the class of Erdos-Renyi graphs and the Barabasi-Albert networks., Comment: 18 pages, 6 figures, revised version accepted for publication in New Journal of Physics (2007)

In this Letter, we study how cooperation is organized in complex topologies by analyzing the evolutionary (replicator) dynamics of the Prisoner's Dilemma, a two-players game with two available strategies, defection and cooperation, whose payoff matrix favors defection. We show that, asymptotically, the population is partitioned into three subsets: individuals that always cooperate ({\em pure cooperators}), always defect ({\em pure defectors}) and those that intermittently change their strategy. In fact the size of the latter set is the biggest for a wide range of the "stimulus to defect" parameter. While in homogeneous random graphs pure cooperators are grouped into several clusters, in heterogeneous scale-free (SF) networks they always form a single cluster containing the most connected individuals (hubs). Our results give further insights into why cooperation in SF networks is favored., Comment: 4 pages and 4 figures. Final version as published in Physical Review Letters