4,947 research outputs found
Symmetries, Cluster Synchronization, and Isolated Desynchronization in Complex Networks
Synchronization is of central importance in power distribution,
telecommunication, neuronal, and biological networks. Many networks are
observed to produce patterns of synchronized clusters, but it has been
difficult to predict these clusters or understand the conditions under which
they form, except for in the simplest of networks. In this article, we shed
light on the intimate connection between network symmetry and cluster
synchronization. We introduce general techniques that use network symmetries to
reveal the patterns of synchronized clusters and determine the conditions under
which they persist. The connection between symmetry and cluster synchronization
is experimentally explored using an electro-optic network. We experimentally
observe and theoretically predict a surprising phenomenon in which some
clusters lose synchrony while leaving others synchronized. The results could
guide the design of new power grid systems or lead to new understanding of the
dynamical behavior of networks ranging from neural to social
Complete Characterization of Stability of Cluster Synchronization in Complex Dynamical Networks
Synchronization is an important and prevalent phenomenon in natural and
engineered systems. In many dynamical networks, the coupling is balanced or
adjusted in order to admit global synchronization, a condition called Laplacian
coupling. Many networks exhibit incomplete synchronization, where two or more
clusters of synchronization persist, and computational group theory has
recently proved to be valuable in discovering these cluster states based upon
the topology of the network. In the important case of Laplacian coupling,
additional synchronization patterns can exist that would not be predicted from
the group theory analysis alone. The understanding of how and when clusters
form, merge, and persist is essential for understanding collective dynamics,
synchronization, and failure mechanisms of complex networks such as electric
power grids, distributed control networks, and autonomous swarming vehicles. We
describe here a method to find and analyze all of the possible cluster
synchronization patterns in a Laplacian-coupled network, by applying methods of
computational group theory to dynamically-equivalent networks. We present a
general technique to evaluate the stability of each of the dynamically valid
cluster synchronization patterns. Our results are validated in an electro-optic
experiment on a 5 node network that confirms the synchronization patterns
predicted by the theory.Comment: 6 figure
Experimental Observations of Group Synchrony in a System of Chaotic Optoelectronic Oscillators
We experimentally demonstrate group synchrony in a network of four nonlinear
optoelectronic oscillators with time-delayed coupling. We divide the nodes into
two groups of two each, by giving each group different parameters and by
enabling only inter-group coupling. When coupled in this fashion, the two
groups display different dynamics, with no isochronal synchrony between them,
but the nodes in a single group are isochronally synchronized, even though
there is no intra-group coupling. We compare experimental behavior with
theoretical and numerical results
Dynamic filtering of static dipoles in magnetoencephalography
We consider the problem of estimating neural activity from measurements
of the magnetic fields recorded by magnetoencephalography. We exploit
the temporal structure of the problem and model the neural current as a
collection of evolving current dipoles, which appear and disappear, but whose
locations are constant throughout their lifetime. This fully reflects the physiological
interpretation of the model.
In order to conduct inference under this proposed model, it was necessary
to develop an algorithm based around state-of-the-art sequential Monte
Carlo methods employing carefully designed importance distributions. Previous
work employed a bootstrap filter and an artificial dynamic structure
where dipoles performed a random walk in space, yielding nonphysical artefacts
in the reconstructions; such artefacts are not observed when using the
proposed model. The algorithm is validated with simulated data, in which
it provided an average localisation error which is approximately half that of
the bootstrap filter. An application to complex real data derived from a somatosensory
experiment is presented. Assessment of model fit via marginal
likelihood showed a clear preference for the proposed model and the associated
reconstructions show better localisation
Cooling of Sr to high phase-space density by laser and sympathetic cooling in isotopic mixtures
Based on an experimental study of two-body and three-body collisions in
ultracold strontium samples, a novel optical-sympathetic cooling method in
isotopic mixtures is demonstrated. Without evaporative cooling, a phase-space
density of is obtained with a high spatial density that should
allow to overcome the difficulties encountered so far to reach quantum
degeneracy for Sr atoms.Comment: 5 pages, 4 figure
HOW DO MILLENNIALS FORESEE THE CAR OF THE FUTURE AND THE FUTURE OF THE CAR? EMPIRICAL EVIDENCE FROM AN OPEN INNOVATION PROCESS PROMOTED BY A MULTINATIONAL COMPANY
Network synchronization of groups
In this paper we study synchronized motions in complex networks in which
there are distinct groups of nodes where the dynamical systems on each node
within a group are the same but are different for nodes in different groups.
Both continuous time and discrete time systems are considered. We initially
focus on the case where two groups are present and the network has bipartite
topology (i.e., links exist between nodes in different groups but not between
nodes in the same group). We also show that group synchronous motions are
compatible with more general network topologies, where there are also
connections within the groups
Red valerian (Centranthus ruber L.): wild host of Cucumber mosaic virus in uncultivated areas of Campania region (Southern Italy)
Experimental characterization of pull-in parameters for an electrostatically actuated cantilever
MEMS-NEMS applications extensively use micro-nano cantilever structures as actuation system, thanks to their intrinsically simple end efficient configuration. Under the action of an electrostatic actuation voltage the can- tilever deflects, until it reaches the maximum value of the electrostatic actuation voltage, namely the pull-in voltage. This limits its operating point and is a critical issue for the switching of the actuator.
The present work aims to experimentally measure the variation of the pull-in voltage and the tip deflection for different geometri- cal parameters of an electrostatically actuated cantilever. First, by relying on a nonlinear differential model from the literature, we designed and built a macro-scale cantilever switch, which can be simply adapted to different configurations. Second, we experimentally investigated the effect of the free length of the suspended electrode, and of the gap from the ground, on the pull-in response. The experimental results always showed a close agree- ment with the analytical predictions, with a maximum relative error lower that 10% for the pull-in voltage, and a relative difference lower than 18% for the pull-in deflection
The role of Entrepreneurial Quality in Equity Crowdfunding success: An explorative analysis of Italian platforms.
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