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Nonlinear analysis of dynamical complex networks
Copyright © 2013 Zidong Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Complex networks are composed of a large number of highly interconnected dynamical units and therefore exhibit very complicated dynamics. Examples of such complex networks include the Internet, that is, a network of routers or domains, the World Wide Web (WWW), that is, a network of websites, the brain, that is, a network of neurons, and an organization, that is, a network of people. Since the introduction of the small-world network principle, a great deal of research has been focused on the dependence of the asymptotic behavior of interconnected oscillatory agents on the structural properties of complex networks. It has been found out that the general structure of the interaction network may play a crucial role in the emergence of synchronization phenomena in various fields such as physics, technology, and the life sciences
Synchronization of heterogeneous oscillators under network modifications: Perturbation and optimization of the synchrony alignment function
Synchronization is central to many complex systems in engineering physics
(e.g., the power-grid, Josephson junction circuits, and electro-chemical
oscillators) and biology (e.g., neuronal, circadian, and cardiac rhythms).
Despite these widespread applications---for which proper functionality depends
sensitively on the extent of synchronization---there remains a lack of
understanding for how systems evolve and adapt to enhance or inhibit
synchronization. We study how network modifications affect the synchronization
properties of network-coupled dynamical systems that have heterogeneous node
dynamics (e.g., phase oscillators with non-identical frequencies), which is
often the case for real-world systems. Our approach relies on a synchrony
alignment function (SAF) that quantifies the interplay between heterogeneity of
the network and of the oscillators and provides an objective measure for a
system's ability to synchronize. We conduct a spectral perturbation analysis of
the SAF for structural network modifications including the addition and removal
of edges, which subsequently ranks the edges according to their importance to
synchronization. Based on this analysis, we develop gradient-descent algorithms
to efficiently solve optimization problems that aim to maximize phase
synchronization via network modifications. We support these and other results
with numerical experiments.Comment: 25 pages, 6 figure
Leaders do not look back, or do they?
We study the effect of adding to a directed chain of interconnected systems a
directed feedback from the last element in the chain to the first. The problem
is closely related to the fundamental question of how a change in network
topology may influence the behavior of coupled systems. We begin the analysis
by investigating a simple linear system. The matrix that specifies the system
dynamics is the transpose of the network Laplacian matrix, which codes the
connectivity of the network. Our analysis shows that for any nonzero complex
eigenvalue of this matrix, the following inequality holds:
. This bound is
sharp, as it becomes an equality for an eigenvalue of a simple directed cycle
with uniform interaction weights. The latter has the slowest decay of
oscillations among all other network configurations with the same number of
states. The result is generalized to directed rings and chains of identical
nonlinear oscillators. For directed rings, a lower bound for the
connection strengths that guarantees asymptotic synchronization is found to
follow a similar pattern: .
Numerical analysis revealed that, depending on the network size , multiple
dynamic regimes co-exist in the state space of the system. In addition to the
fully synchronous state a rotating wave solution occurs. The effect is observed
in networks exceeding a certain critical size. The emergence of a rotating wave
highlights the importance of long chains and loops in networks of oscillators:
the larger the size of chains and loops, the more sensitive the network
dynamics becomes to removal or addition of a single connection
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