255 research outputs found
On the onset of synchronization of Kuramoto oscillators in scale-free networks
Despite the great attention devoted to the study of phase oscillators on
complex networks in the last two decades, it remains unclear whether scale-free
networks exhibit a nonzero critical coupling strength for the onset of
synchronization in the thermodynamic limit. Here, we systematically compare
predictions from the heterogeneous degree mean-field (HMF) and the quenched
mean-field (QMF) approaches to extensive numerical simulations on large
networks. We provide compelling evidence that the critical coupling vanishes as
the number of oscillators increases for scale-free networks characterized by a
power-law degree distribution with an exponent , in line
with what has been observed for other dynamical processes in such networks. For
, we show that the critical coupling remains finite, in agreement
with HMF calculations and highlight phenomenological differences between
critical properties of phase oscillators and epidemic models on scale-free
networks. Finally, we also discuss at length a key choice when studying
synchronization phenomena in complex networks, namely, how to normalize the
coupling between oscillators
Network centrality: an introduction
Centrality is a key property of complex networks that influences the behavior
of dynamical processes, like synchronization and epidemic spreading, and can
bring important information about the organization of complex systems, like our
brain and society. There are many metrics to quantify the node centrality in
networks. Here, we review the main centrality measures and discuss their main
features and limitations. The influence of network centrality on epidemic
spreading and synchronization is also pointed out in this chapter. Moreover, we
present the application of centrality measures to understand the function of
complex systems, including biological and cortical networks. Finally, we
discuss some perspectives and challenges to generalize centrality measures for
multilayer and temporal networks.Comment: Book Chapter in "From nonlinear dynamics to complex systems: A
Mathematical modeling approach" by Springe
Dynamical Systems on Networks: A Tutorial
We give a tutorial for the study of dynamical systems on networks. We focus
especially on "simple" situations that are tractable analytically, because they
can be very insightful and provide useful springboards for the study of more
complicated scenarios. We briefly motivate why examining dynamical systems on
networks is interesting and important, and we then give several fascinating
examples and discuss some theoretical results. We also briefly discuss
dynamical systems on dynamical (i.e., time-dependent) networks, overview
software implementations, and give an outlook on the field.Comment: 39 pages, 1 figure, submitted, more examples and discussion than
original version, some reorganization and also more pointers to interesting
direction
Graph Theory and Networks in Biology
In this paper, we present a survey of the use of graph theoretical techniques
in Biology. In particular, we discuss recent work on identifying and modelling
the structure of bio-molecular networks, as well as the application of
centrality measures to interaction networks and research on the hierarchical
structure of such networks and network motifs. Work on the link between
structural network properties and dynamics is also described, with emphasis on
synchronization and disease propagation.Comment: 52 pages, 5 figures, Survey Pape
Paths to Synchronization on Complex Networks
The understanding of emergent collective phenomena in natural and social
systems has driven the interest of scientists from different disciplines during
decades. Among these phenomena, the synchronization of a set of interacting
individuals or units has been intensively studied because of its ubiquity in
the natural world. In this paper, we show how for fixed coupling strengths
local patterns of synchronization emerge differently in homogeneous and
heterogeneous complex networks, driving the process towards a certain global
synchronization degree following different paths. The dependence of the
dynamics on the coupling strength and on the topology is unveiled. This study
provides a new perspective and tools to understand this emerging phenomena.Comment: Final version published in Physical Review Letter
Synchronization in complex networks
Synchronization processes in populations of locally interacting elements are
in the focus of intense research in physical, biological, chemical,
technological and social systems. The many efforts devoted to understand
synchronization phenomena in natural systems take now advantage of the recent
theory of complex networks. In this review, we report the advances in the
comprehension of synchronization phenomena when oscillating elements are
constrained to interact in a complex network topology. We also overview the new
emergent features coming out from the interplay between the structure and the
function of the underlying pattern of connections. Extensive numerical work as
well as analytical approaches to the problem are presented. Finally, we review
several applications of synchronization in complex networks to different
disciplines: biological systems and neuroscience, engineering and computer
science, and economy and social sciences.Comment: Final version published in Physics Reports. More information
available at http://synchronets.googlepages.com
Effect of assortative mixing in the second-order Kuramoto model
In this paper we analyze the second-order Kuramoto model presenting a
positive correlation between the heterogeneity of the connections and the
natural frequencies in scale-free networks. We numerically show that
discontinuous transitions emerge not just in disassortative but also in
assortative networks, in contrast with the first-order model. We also find that
the effect of assortativity on network synchronization can be compensated by
adjusting the phase damping. Our results show that it is possible to control
collective behavior of damped Kuramoto oscillators by tuning the network
structure or by adjusting the dissipation related to the phases movement.Comment: 7 pages, 6 figures. In press in Physical Review
Critical phenomena in complex networks
The combination of the compactness of networks, featuring small diameters,
and their complex architectures results in a variety of critical effects
dramatically different from those in cooperative systems on lattices. In the
last few years, researchers have made important steps toward understanding the
qualitatively new critical phenomena in complex networks. We review the
results, concepts, and methods of this rapidly developing field. Here we mostly
consider two closely related classes of these critical phenomena, namely
structural phase transitions in the network architectures and transitions in
cooperative models on networks as substrates. We also discuss systems where a
network and interacting agents on it influence each other. We overview a wide
range of critical phenomena in equilibrium and growing networks including the
birth of the giant connected component, percolation, k-core percolation,
phenomena near epidemic thresholds, condensation transitions, critical
phenomena in spin models placed on networks, synchronization, and
self-organized criticality effects in interacting systems on networks. We also
discuss strong finite size effects in these systems and highlight open problems
and perspectives.Comment: Review article, 79 pages, 43 figures, 1 table, 508 references,
extende
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