1,496 research outputs found
Synchronization of Kuramoto oscillators with distance-dependent delay
We investigate the synchronization process in a Kuramoto model of phase-coupled oscillators with distance-dependent delay. The oscillators occupy the nodes of a two-dimensional square lattice subjected to periodic boundary conditions. The mean-field interactions with velocity-dependent delays propagate along the lattice sites. This gives rise to a non-uniform distribution of delays and lattice dimensionality dependence, which is not present in mean-field models without delays. We find that the 'coupling strength-delay' phase diagram does not show up reentrant behavior present in models with uniform delay. A number of dynamic patterns, reported earlier for a generalized Kuramoto model with non-mean-field distance-dependent interactions, is also found
Phase synchronization of coupled bursting neurons and the generalized Kuramoto model
Bursting neurons fire rapid sequences of action potential spikes followed by
a quiescent period. The basic dynamical mechanism of bursting is the slow
currents that modulate a fast spiking activity caused by rapid ionic currents.
Minimal models of bursting neurons must include both effects. We considered one
of these models and its relation with a generalized Kuramoto model, thanks to
the definition of a geometrical phase for bursting and a corresponding
frequency. We considered neuronal networks with different connection topologies
and investigated the transition from a non-synchronized to a partially
phase-synchronized state as the coupling strength is varied. The numerically
determined critical coupling strength value for this transition to occur is
compared with theoretical results valid for the generalized Kuramoto model.Comment: 31 pages, 5 figure
Network Structure, Topology and Dynamics in Generalized Models of Synchronization
We explore the interplay of network structure, topology, and dynamic
interactions between nodes using the paradigm of distributed synchronization in
a network of coupled oscillators. As the network evolves to a global steady
state, interconnected oscillators synchronize in stages, revealing network's
underlying community structure. Traditional models of synchronization assume
that interactions between nodes are mediated by a conservative process, such as
diffusion. However, social and biological processes are often non-conservative.
We propose a new model of synchronization in a network of oscillators coupled
via non-conservative processes. We study dynamics of synchronization of a
synthetic and real-world networks and show that different synchronization
models reveal different structures within the same network
Hysteretic behavior of spatially coupled phase-oscillators
Motivated by phenomena related to biological systems such as the
synchronously flashing swarms of fireflies, we investigate a network of phase
oscillators evolving under the generalized Kuramoto model with inertia. A
distance-dependent, spatial coupling between the oscillators is considered.
Zeroth and first order kernel functions with finite kernel radii were chosen to
investigate the effect of local interactions. The hysteretic dynamics of the
synchronization depending on the coupling parameter was analyzed for different
kernel radii. Numerical investigations demonstrate that (1) locally locked
clusters develop for small coupling strength values, (2) the hysteretic
behavior vanishes for small kernel radii, (3) the ratio of the kernel radius
and the maximal distance between the oscillators characterizes the behavior of
the network
Collective Almost Synchronization in Complex Networks
This work introduces the phenomenon of Collective Almost Synchronization
(CAS), which describes a universal way of how patterns can appear in complex
networks even for small coupling strengths. The CAS phenomenon appears due to
the existence of an approximately constant local mean field and is
characterized by having nodes with trajectories evolving around periodic stable
orbits. Common notion based on statistical knowledge would lead one to
interpret the appearance of a local constant mean field as a consequence of the
fact that the behavior of each node is not correlated to the behaviors of the
others. Contrary to this common notion, we show that various well known weaker
forms of synchronization (almost, time-lag, phase synchronization, and
generalized synchronization) appear as a result of the onset of an almost
constant local mean field. If the memory is formed in a brain by minimising the
coupling strength among neurons and maximising the number of possible patterns,
then the CAS phenomenon is a plausible explanation for it.Comment: 3 figure
Quantum correlations and synchronization measures
The phenomenon of spontaneous synchronization is universal and only recently
advances have been made in the quantum domain. Being synchronization a kind of
temporal correlation among systems, it is interesting to understand its
connection with other measures of quantum correlations. We review here what is
known in the field, putting emphasis on measures and indicators of
synchronization which have been proposed in the literature, and comparing their
validity for different dynamical systems, highlighting when they give similar
insights and when they seem to fail.Comment: book chapter, 18 pages, 7 figures, Fanchini F., Soares Pinto D.,
Adesso G. (eds) Lectures on General Quantum Correlations and their
Applications. Quantum Science and Technology. Springer (2017
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