506 research outputs found
Flow of the Coarse Grained Free Energy for Crossover Phenomena
The critical behaviour of a system of two coupled scalar fields in three
dimensions is studied within the formalism of the effective average action. The
fixed points of the system are identified and the crossover between them is
described in detail. Besides the universal critical behaviour, the flow of the
coarse grained free energy also describes the approach to scaling.Comment: 18 pages, latex, 4 figures appended as uuencoded fil
Designer Nets from Local Strategies
We propose a local strategy for constructing scale-free networks of arbitrary
degree distributions, based on the redirection method of Krapivsky and Redner
[Phys. Rev. E 63, 066123 (2001)]. Our method includes a set of external
parameters that can be tuned at will to match detailed behavior at small degree
k, in addition to the scale-free power-law tail signature at large k. The
choice of parameters determines other network characteristics, such as the
degree of clustering. The method is local in that addition of a new node
requires knowledge of only the immediate environs of the (randomly selected)
node to which it is attached. (Global strategies require information on finite
fractions of the growing net.
Solving non-perturbative flow equations
Non-perturbative exact flow equations describe the scale dependence of the
effective average action. We present a numerical solution for an approximate
form of the flow equation for the potential in a three-dimensional N-component
scalar field theory. The critical behaviour, with associated critical
exponents, can be inferred with good accuracy.Comment: Latex, 14 pages, 2 uuencoded figure
Kauffman Boolean model in undirected scale free networks
We investigate analytically and numerically the critical line in undirected
random Boolean networks with arbitrary degree distributions, including
scale-free topology of connections . We show that in
infinite scale-free networks the transition between frozen and chaotic phase
occurs for . The observation is interesting for two reasons.
First, since most of critical phenomena in scale-free networks reveal their
non-trivial character for , the position of the critical line in
Kauffman model seems to be an important exception from the rule. Second, since
gene regulatory networks are characterized by scale-free topology with
, the observation that in finite-size networks the mentioned
transition moves towards smaller is an argument for Kauffman model as
a good starting point to model real systems. We also explain that the
unattainability of the critical line in numerical simulations of classical
random graphs is due to percolation phenomena
Stable and unstable attractors in Boolean networks
Boolean networks at the critical point have been a matter of debate for many
years as, e.g., scaling of number of attractor with system size. Recently it
was found that this number scales superpolynomially with system size, contrary
to a common earlier expectation of sublinear scaling. We here point to the fact
that these results are obtained using deterministic parallel update, where a
large fraction of attractors in fact are an artifact of the updating scheme.
This limits the significance of these results for biological systems where
noise is omnipresent. We here take a fresh look at attractors in Boolean
networks with the original motivation of simplified models for biological
systems in mind. We test stability of attractors w.r.t. infinitesimal
deviations from synchronous update and find that most attractors found under
parallel update are artifacts arising from the synchronous clocking mode. The
remaining fraction of attractors are stable against fluctuating response
delays. For this subset of stable attractors we observe sublinear scaling of
the number of attractors with system size.Comment: extended version, additional figur
Interplay between network structure and self-organized criticality
We investigate, by numerical simulations, how the avalanche dynamics of the
Bak-Tang-Wiesenfeld (BTW) sandpile model can induce emergence of scale-free
(SF) networks and how this emerging structure affects dynamics of the system.
We also discuss how the observed phenomenon can be used to explain evolution of
scientific collaboration.Comment: 4 pages, 4 figure
Does dynamics reflect topology in directed networks?
We present and analyze a topologically induced transition from ordered,
synchronized to disordered dynamics in directed networks of oscillators. The
analysis reveals where in the space of networks this transition occurs and its
underlying mechanisms. If disordered, the dynamics of the units is precisely
determined by the topology of the network and thus characteristic for it. We
develop a method to predict the disordered dynamics from topology. The results
suggest a new route towards understanding how the precise dynamics of the units
of a directed network may encode information about its topology.Comment: 7 pages, 4 figures, Europhysics Letters, accepte
Topology of biological networks and reliability of information processing
Biological systems rely on robust internal information processing: Survival
depends on highly reproducible dynamics of regulatory processes. Biological
information processing elements, however, are intrinsically noisy (genetic
switches, neurons, etc.). Such noise poses severe stability problems to system
behavior as it tends to desynchronize system dynamics (e.g. via fluctuating
response or transmission time of the elements). Synchronicity in parallel
information processing is not readily sustained in the absence of a central
clock. Here we analyze the influence of topology on synchronicity in networks
of autonomous noisy elements. In numerical and analytical studies we find a
clear distinction between non-reliable and reliable dynamical attractors,
depending on the topology of the circuit. In the reliable cases, synchronicity
is sustained, while in the unreliable scenario, fluctuating responses of single
elements can gradually desynchronize the system, leading to non-reproducible
behavior. We find that the fraction of reliable dynamical attractors strongly
correlates with the underlying circuitry. Our model suggests that the observed
motif structure of biological signaling networks is shaped by the biological
requirement for reproducibility of attractors.Comment: 7 pages, 7 figure
Annealing schedule from population dynamics
We introduce a dynamical annealing schedule for population-based optimization
algorithms with mutation. On the basis of a statistical mechanics formulation
of the population dynamics, the mutation rate adapts to a value maximizing
expected rewards at each time step. Thereby, the mutation rate is eliminated as
a free parameter from the algorithm.Comment: 6 pages RevTeX, 4 figures PostScript; to be published in Phys. Rev.
Synchronization of networks with variable local properties
We study the synchronization transition of Kuramoto oscillators in scale-free
networks that are characterized by tunable local properties. Specifically, we
perform a detailed finite size scaling analysis and inspect how the critical
properties of the dynamics change when the clustering coefficient and the
average shortest path length are varied. The results show that the onset of
synchronization does depend on these properties, though the dependence is
smooth. On the contrary, the appearance of complete synchronization is
radically affected by the structure of the networks. Our study highlights the
need of exploring the whole phase diagram and not only the stability of the
fully synchronized state, where most studies have been done up to now.Comment: 5 pages and 3 figures. APS style. Paper to be published in IJBC
(special issue on Complex Networks' Structure and Dynamics
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