4,693 research outputs found
Efficient Rewirings for Enhancing Synchronizability of Dynamical Networks
In this paper, we present an algorithm for optimizing synchronizability of
complex dynamical networks. Based on some network properties, rewirings, i.e.
eliminating an edge and creating a new edge elsewhere, are performed
iteratively avoiding always self-loops and multiple edges between the same
nodes. We show that the method is able to enhance the synchronizability of
networks of any size and topological properties in a small number of steps that
scales with the network size.Although we take the eigenratio of the Laplacian
as the target function for optimization, we will show that it is also possible
to choose other appropriate target functions exhibiting almost the same
performance. The optimized networks are Ramanujan graphs, and thus, this
rewiring algorithm could be used to produce Ramanujan graphs of any size and
average degree
Topological properties and fractal analysis of recurrence network constructed from fractional Brownian motions
Many studies have shown that we can gain additional information on time
series by investigating their accompanying complex networks. In this work, we
investigate the fundamental topological and fractal properties of recurrence
networks constructed from fractional Brownian motions (FBMs). First, our
results indicate that the constructed recurrence networks have exponential
degree distributions; the relationship between and of recurrence networks decreases with the Hurst
index of the associated FBMs, and their dependence approximately satisfies
the linear formula . Moreover, our numerical results of
multifractal analysis show that the multifractality exists in these recurrence
networks, and the multifractality of these networks becomes stronger at first
and then weaker when the Hurst index of the associated time series becomes
larger from 0.4 to 0.95. In particular, the recurrence network with the Hurst
index possess the strongest multifractality. In addition, the
dependence relationships of the average information dimension on the Hurst index can also be
fitted well with linear functions. Our results strongly suggest that the
recurrence network inherits the basic characteristic and the fractal nature of
the associated FBM series.Comment: 25 pages, 1 table, 15 figures. accepted by Phys. Rev.
Fast Escape from Quantum Mazes in Integrated Photonics
Escaping from a complex maze, by exploring different paths with several
decision-making branches in order to reach the exit, has always been a very
challenging and fascinating task. Wave field and quantum objects may explore a
complex structure in parallel by interference effects, but without necessarily
leading to more efficient transport. Here, inspired by recent observations in
biological energy transport phenomena, we demonstrate how a quantum walker can
efficiently reach the output of a maze by partially suppressing the presence of
interference. In particular, we show theoretically an unprecedented improvement
in transport efficiency for increasing maze size with respect to purely quantum
and classical approaches. In addition, we investigate experimentally these
hybrid transport phenomena, by mapping the maze problem in an integrated
waveguide array, probed by coherent light, hence successfully testing our
theoretical results. These achievements may lead towards future bio-inspired
photonics technologies for more efficient transport and computation.Comment: 13 pages, 10 figure
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