63 research outputs found

    Nonlinear Stochastic Differential Equations and Self-Organized Criticality

    Full text link
    Several nonlinear stochastic differential equations have been proposed in connection with self-organized critical phenomena. Due to the threshold condition involved in its dynamic evolution an infinite number of nonlinearities arises in a hydrodynamic description. We study two models with different noise correlations which make all the nonlinear contribution to be equally relevant below the upper critical dimension. The asymptotic values of the critical exponents are estimated from a systematic expansion in the number of coupling constants by means of the dynamic renormalization group.Comment: RevTeX 3.0, no figure

    Dynamical properties of the Zhang model of Self-Organized Criticality

    Get PDF
    Critical exponents of the infinitely slowly driven Zhang model of self-organized criticality are computed for d=2,3d=2,3 with particular emphasis devoted to the various roughening exponents. Besides confirming recent estimates of some exponents, new quantities are monitored and their critical exponents computed. Among other results, it is shown that the three dimensional exponents do not coincide with the Bak, Tang, and Wiesenfeld (abelian) model and that the dynamical exponent as computed from the correlation length and from the roughness of the energy profile do not necessarily coincide as it is usually implicitly assumed. An explanation for this is provided. The possibility of comparing these results with those obtained from Renormalization Group arguments is also briefly addressed.Comment: 8 pages, 12 PostScript figures, RevTe

    Synchronization in dynamical networks of locally coupled self-propelled oscillators

    Get PDF
    Systems of mobile physical entities exchanging information with their neighborhood can be found in many different situations. The understanding of their emergent cooperative behaviour has become an important issue across disciplines, requiring a general conceptual framework in order to harvest the potential of these systems. We study the synchronization of coupled oscillators in time-evolving networks defined by the positions of self-propelled agents interacting in real space. In order to understand the impact of mobility in the synchronization process on general grounds, we introduce a simple model of self-propelled hard disks performing persistent random walks in 2dd space and carrying an internal Kuramoto phase oscillator. For non-interacting particles, self-propulsion accelerates synchronization. The competition between agent mobility and excluded volume interactions gives rise to a richer scenario, leading to an optimal self-propulsion speed. We identify two extreme dynamic regimes where synchronization can be understood from theoretical considerations. A systematic analysis of our model quantifies the departure from the latter ideal situations and characterizes the different mechanisms leading the evolution of the system. We show that the synchronization of locally coupled mobile oscillators generically proceeds through coarsening verifying dynamic scaling and sharing strong similarities with the phase ordering dynamics of the 2dd XY model following a quench. Our results shed light into the generic mechanisms leading the synchronization of mobile agents, providing a efficient way to understand more complex or specific situations involving time-dependent networks where synchronization, mobility and excluded volume are at play

    Modeling the Internet

    Full text link
    We model the Internet as a network of interconnected Autonomous Systems which self-organize under an absolute lack of centralized control. Our aim is to capture how the Internet evolves by reproducing the assembly that has led to its actual structure and, to this end, we propose a growing weighted network model driven by competition for resources and adaptation to maintain functionality in a demand and supply ``equilibrium''. On the demand side, we consider the environment, a pool of users which need to transfer information and ask for service. On the supply side, ASs compete to gain users, but to be able to provide service efficiently, they must adapt their bandwidth as a function of their size. Hence, the Internet is not modeled as an isolated system but the environment, in the form of a pool of users, is also a fundamental part which must be taken into account. ASs compete for users and big and small come up, so that not all ASs are identical. New connections between ASs are made or old ones are reinforced according to the adaptation needs. Thus, the evolution of the Internet can not be fully understood if just described as a technological isolated system. A socio-economic perspective must also be considered.Comment: Submitted to the Proceedings of the 3rd International Conference NEXT-SigmaPh

    Dynamical properties of model communication networks

    Get PDF
    We study the dynamical properties of a collection of models for communication processes, characterized by a single parameter ξ\xi representing the relation between information load of the nodes and its ability to deliver this information. The critical transition to congestion reported so far occurs only for ξ=1\xi=1. This case is well analyzed for different network topologies. We focus of the properties of the order parameter, the susceptibility and the time correlations when approaching the critical point. For ξ<1\xi<1 no transition to congestion is observed but it remains a cross-over from a low-density to a high-density state. For ξ>1\xi>1 the transition to congestion is discontinuous and congestion nuclei arise.Comment: 8 pages, 8 figure

    Synchronization of moving integrate and fire oscillators

    Get PDF
    We present a model of integrate and fire oscillators that move on a plane. The phase of the oscillators evolves linearly in time and when it reaches a threshold value they fire choosing their neighbors according to a certain interaction range. Depending on the velocity of the ballistic motion and the average number of neighbors each oscillator fires to, we identify different regimes shown in a phase diagram. We characterize these regimes by means of novel parameters as the accumulated number of contacted neighbors.Comment: 9 pages, 5 figure
    corecore