11 research outputs found
Nonequilibrium phase transition in a model for the propagation of innovations among economic agents
We characterize the different morphological phases that occur in a simple
one-dimensional model of propagation of innovations among economic agents [X.\
Guardiola, {\it et. al.}, Phys. Rev E {\bf 66}, 026121 (2002)]. We show that
the model can be regarded as a nonequilibrium surface growth model. This allows
us to demonstrate the presence of a continuous roughening transition between a
flat (system size independent fluctuations) and a rough phase (system size
dependent fluctuations). Finite-size scaling studies at the transition strongly
suggest that the dynamic critical transition does not belong to directed
percolation and, in fact, critical exponents do not seem to fit in any of the
known universality classes of nonequilibrium phase transitions. Finally, we
present an explanation for the occurrence of the roughening transition and
argue that avalanche driven dynamics is responsible for the novel critical
behavior
Optimization as a result of the interplay between dynamics and structure
In this work we study the interplay between the dynamics of a model of
diffusion governed by a mechanism of imitation and its underlying structure.
The dynamics of the model can be quantified by a macroscopic observable which
permits the characterization of an optimal regime. We show that dynamics and
underlying network cannot be considered as separated ingredients in order to
achieve an optimal behavior.Comment: 12 pages, 4 figures, to appear in Physica
Modelling diffusion of innovations in a social network
A new simple model of diffusion of innovations in a social network with
upgrading costs is introduced. Agents are characterized by a single real
variable, their technological level. According to local information agents
decide whether to upgrade their level or not balancing their possible benefit
with the upgrading cost. A critical point where technological avalanches
display a power-law behavior is also found. This critical point is
characterized by a macroscopic observable that turns out to optimize
technological growth in the stationary state. Analytical results supporting our
findings are found for the globally coupled case.Comment: 4 pages, 5 figures. Final version accepted in PR
Synchronization, Diversity, and Topology of Networks of Integrate and Fire Oscillators
We study synchronization dynamics of a population of pulse-coupled
oscillators. In particular, we focus our attention in the interplay between
networks topological disorder and its synchronization features. Firstly, we
analyze synchronization time in random networks, and find a scaling law
which relates to networks connectivity. Then, we carry on comparing
synchronization time for several other topological configurations,
characterized by a different degree of randomness. The analysis shows that
regular lattices perform better than any other disordered network. The fact can
be understood by considering the variability in the number of links between two
adjacent neighbors. This phenomenon is equivalent to have a non-random topology
with a distribution of interactions and it can be removed by an adequate local
normalization of the couplings.Comment: 6 pages, 8 figures, LaTeX 209, uses RevTe
Optimizing Functional Network Representation of Multivariate Time Series
By combining complex network theory and data mining techniques, we provide objective criteria for optimization of the functional network representation of generic multivariate time series. In particular, we propose a method for the principled selection of the threshold value for functional network reconstruction from raw data, and for proper identification of the network's indicators that unveil the most discriminative information on the system for classification purposes. We illustrate our method by analysing networks of functional brain activity of healthy subjects, and patients suffering from Mild Cognitive Impairment, an intermediate stage between the expected cognitive decline of normal aging and the more pronounced decline of dementia. We discuss extensions of the scope of the proposed methodology to network engineering purposes, and to other data mining tasks
Nonequilibrium phase transition in a model for the propagation of innovations among economic agents
We characterize the different morphological phases that occur in a simple one-dimensional model of propagation of innovations among economic agents [X. Guardiola et al., Phys. Rev E 66, 026121 (2002)]. We show that the model can be regarded as a nonequilibrium surface growth model. This allows us to demonstrate the presence of a continuous roughening transition between a flat (system size independent fluctuations) and a rough phase (system size dependent fluctuations). Finite-size scaling studies at the transition strongly suggest that the dynamic critical transition does not belong to directed percolation and, in fact, critical exponents do not seem to fit in any of the known universality classes of nonequilibrium phase transitions. Finally, we present an explanation for the occurrence of the roughening transition and argue that avalanche driven dynamics is responsible for the novel critical behavior