20,688 research outputs found
Dynamics and Steady States in excitable mobile agent systems
We study the spreading of excitations in 2D systems of mobile agents where
the excitation is transmitted when a quiescent agent keeps contact with an
excited one during a non-vanishing time. We show that the steady states
strongly depend on the spatial agent dynamics. Moreover, the coupling between
exposition time () and agent-agent contact rate (CR) becomes crucial to
understand the excitation dynamics, which exhibits three regimes with CR: no
excitation for low CR, an excited regime in which the number of quiescent
agents (S) is inversely proportional to CR, and for high CR, a novel third
regime, model dependent, here S scales with an exponent , with
being the scaling exponent of with CR
The Opportunistic Transmission of Wireless Worms between Mobile Devices
The ubiquity of portable wireless-enabled computing and communications
devices has stimulated the emergence of malicious codes (wireless worms) that
are capable of spreading between spatially proximal devices. The potential
exists for worms to be opportunistically transmitted between devices as they
move around, so human mobility patterns will have an impact on epidemic spread.
The scenario we address in this paper is proximity attacks from fleetingly
in-contact wireless devices with short-range communication range, such as
Bluetooth-enabled smart phones. An individual-based model of mobile devices is
introduced and the effect of population characteristics and device behaviour on
the outbreak dynamics is investigated. We show through extensive simulations
that in the above scenario the resulting mass-action epidemic models remain
applicable provided the contact rate is derived consistently from the
underlying mobility model. The model gives useful analytical expressions
against which more refined simulations of worm spread can be developed and
tested.Comment: Submitted for publicatio
On the onset of synchronization of Kuramoto oscillators in scale-free networks
Despite the great attention devoted to the study of phase oscillators on
complex networks in the last two decades, it remains unclear whether scale-free
networks exhibit a nonzero critical coupling strength for the onset of
synchronization in the thermodynamic limit. Here, we systematically compare
predictions from the heterogeneous degree mean-field (HMF) and the quenched
mean-field (QMF) approaches to extensive numerical simulations on large
networks. We provide compelling evidence that the critical coupling vanishes as
the number of oscillators increases for scale-free networks characterized by a
power-law degree distribution with an exponent , in line
with what has been observed for other dynamical processes in such networks. For
, we show that the critical coupling remains finite, in agreement
with HMF calculations and highlight phenomenological differences between
critical properties of phase oscillators and epidemic models on scale-free
networks. Finally, we also discuss at length a key choice when studying
synchronization phenomena in complex networks, namely, how to normalize the
coupling between oscillators
Non-equilibrium Phase Transitions with Long-Range Interactions
This review article gives an overview of recent progress in the field of
non-equilibrium phase transitions into absorbing states with long-range
interactions. It focuses on two possible types of long-range interactions. The
first one is to replace nearest-neighbor couplings by unrestricted Levy flights
with a power-law distribution P(r) ~ r^(-d-sigma) controlled by an exponent
sigma. Similarly, the temporal evolution can be modified by introducing waiting
times Dt between subsequent moves which are distributed algebraically as P(Dt)~
(Dt)^(-1-kappa). It turns out that such systems with Levy-distributed
long-range interactions still exhibit a continuous phase transition with
critical exponents varying continuously with sigma and/or kappa in certain
ranges of the parameter space. In a field-theoretical framework such
algebraically distributed long-range interactions can be accounted for by
replacing the differential operators nabla^2 and d/dt with fractional
derivatives nabla^sigma and (d/dt)^kappa. As another possibility, one may
introduce algebraically decaying long-range interactions which cannot exceed
the actual distance to the nearest particle. Such interactions are motivated by
studies of non-equilibrium growth processes and may be interpreted as Levy
flights cut off at the actual distance to the nearest particle. In the
continuum limit such truncated Levy flights can be described to leading order
by terms involving fractional powers of the density field while the
differential operators remain short-ranged.Comment: LaTeX, 39 pages, 13 figures, minor revision
Targeted Recovery as an Effective Strategy against Epidemic Spreading
We propose a targeted intervention protocol where recovery is restricted to
individuals that have the least number of infected neighbours. Our recovery
strategy is highly efficient on any kind of network, since epidemic outbreaks
are minimal when compared to the baseline scenario of spontaneous recovery. In
the case of spatially embedded networks, we find that an epidemic stays
strongly spatially confined with a characteristic length scale undergoing a
random walk. We demonstrate numerically and analytically that this dynamics
leads to an epidemic spot with a flat surface structure and a radius that grows
linearly with the spreading rate.Comment: 6 pages, 5 figure
Long-range epidemic spreading with immunization
We study the phase transition between survival and extinction in an epidemic
process with long-range interactions and immunization. This model can be viewed
as the well-known general epidemic process (GEP) in which nearest-neighbor
interactions are replaced by Levy flights over distances r which are
distributed as P(r) ~ r^(-d-sigma). By extensive numerical simulations we
confirm previous field-theoretical results obtained by Janssen et al. [Eur.
Phys. J. B7, 137 (1999)].Comment: LaTeX, 14 pages, 4 eps figure
Epidemic Threshold in Continuous-Time Evolving Networks
Current understanding of the critical outbreak condition on temporal networks
relies on approximations (time scale separation, discretization) that may bias
the results. We propose a theoretical framework to compute the epidemic
threshold in continuous time through the infection propagator approach. We
introduce the {\em weak commutation} condition allowing the interpretation of
annealed networks, activity-driven networks, and time scale separation into one
formalism. Our work provides a coherent connection between discrete and
continuous time representations applicable to realistic scenarios.Comment: 13 pages, 2 figure
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