3,294 research outputs found
Updating Neighbour Cell List via Crowdsourced User Reports: A Framework for Measuring Time Performance
In modern wireless networks deployments, each serving node needs to keep its Neighbour Cell List (NCL) constantly up to date to
keep track of network changes. The time needed by each serving node to update its NCL is an important parameter of the networkâs
reliability and performance. An adequate estimate of such parameter enables a significant improvement of self-configuration
functionalities. This paper focuses on the update time of NCLs when an approach of crowdsourced user reports is adopted. In
this setting, each user periodically reports to the serving node information about the set of nodes sensed by the user itself. We show
that, by mapping the local topological structure of the network onto states of increasing knowledge, a crisp mathematical framework
can be obtained, which allows in turn for the use of a variety of user mobility models. Further, using a simplified mobility model we
show how to obtain useful upper bounds on the expected time for a serving node to gain Full Knowledge of its local neighbourhood
Characterization of a periodically driven chaotic dynamical system
We discuss how to characterize the behavior of a chaotic dynamical system
depending on a parameter that varies periodically in time. In particular, we
study the predictability time, the correlations and the mean responses, by
defining a local--in--time version of these quantities. In systems where the
time scale related to the time periodic variation of the parameter is much
larger than the ``internal'' time scale, one has that the local quantities
strongly depend on the phase of the cycle. In this case, the standard global
quantities can give misleading information.Comment: 15 pages, Revtex 2.0, 8 figures, included. All files packed with
uufile
Type Ia supernovae tests of fractal bubble universe with no cosmic acceleration
The unexpected dimness of Type Ia supernovae at redshifts z >~ 1 has over the
past 7 years been seen as an indication that the expansion of the universe is
accelerating. A new model cosmology, the "fractal bubble model", has been
proposed by one of us [gr-qc/0503099], based on the idea that our observed
universe resides in an underdense bubble remnant from a primordial epoch of
cosmic inflation, together with a new solution for averaging in an
inhomogeneous universe. Although there is no cosmic acceleration, it is claimed
that the luminosity distance of type Ia supernovae data will nonetheless fit
the new model, since it mimics a Milne universe at low redshifts. In this paper
the hypothesis is tested statistically against the available type Ia supernovae
data by both chi-square and Bayesian methods. While the standard model with
cosmological constant Omega_Lambda = 1-Omega_m is favoured by a Bayesian
analysis with wide priors, the comparison depends strongly on the priors chosen
for the density parameter, Omega_m. The fractal bubble model gives better
agreement generally for Omega_m<0.2. It also gives reasonably good fits for all
the range, Omega_m=0.01-0.55, allowing the possibility of a viable cosmology
with just baryonic matter, or alternatively with both baryonic matter and
additional cold dark matter.Comment: 10 pages, 5 figures, aastex. v3: Corrected volume factor changes
parameter estimates and discussion, figures redrawn, references adde
Modeling Kelvin wave cascades in superfluid helium
We study two different types of simplified models for Kelvin wave turbulence on quantized vortex lines in superfluids near zero temperature. Our first model is obtained from a truncated expansion of the Local Induction Approximation (Truncated-LIA) and it is shown to possess the same scalings and the essential behaviour as the full Biot-Savart model, being much simpler than the later and, therefore, more amenable to theoretical and numerical investigations. The Truncated-LIA model supports six-wave interactions and dual cascades, which are clearly demonstrated via the direct numerical simulation of this model in the present paper. In particular, our simulations confirm presence of the weak turbulence regime and the theoretically predicted spectra for the direct energy cascade and the inverse wave action cascade. The second type of model we study, the Differential Approximation Model (DAM), takes a further drastic simplification by assuming locality of interactions in k-space via using a differential closure that preserves the main scalings of the Kelvin wave dynamics. DAMs are even more amenable to study and they form a useful tool by providing simple analytical solutions in the cases when extra physical effects are present, e.g. forcing by reconnections, friction dissipation and phonon radiation. We study these models numerically and test their theoretical predictions, in particular the formation of the stationary spectra, and closeness of numerics for the higher-order DAM to the analytical predictions for the lower-order DAM
Interference in Exclusive Vector Meson Production in Heavy Ion Collisions
Photons emitted from the electromagnetic fields of relativistic heavy ions
can fluctuate into quark anti-quark pairs and scatter from a target nucleus,
emerging as vector mesons. These coherent interactions are identifiable by
final states consisting of the two nuclei and a vector meson with a small
transverse momentum. The emitters and targets can switch roles, and the two
possibilities are indistinguishable, so interference may occur. Vector mesons
are negative parity so the amplitudes have opposite signs. When the meson
transverse wavelength is larger than the impact parameter, the interference is
large and destructive.
The short-lived vector mesons decay before amplitudes from the two sources
can overlap, and so cannot interfere directly. However, the decay products are
emitted in an entangled state, and the interference depends on observing the
complete final state. The non-local wave function is an example of the
Einstein-Podolsky-Rosen paradox.Comment: 13 pages with 3 figures; submitted to Physical Review Letter
Dark energy from scalar field with Gauss Bonnet and non-minimal kinetic coupling
We study a model of scalar field with a general non-minimal kinetic coupling
to itself and to the curvature, and additional coupling to the Gauss Bonnet
4-dimensional invariant. The model presents rich cosmological dynamics and some
of its solutions are analyzed. A variety of scalar fields and potentials giving
rise to power-law expansion have been found. The dynamical equation of state is
studied for two cases, with and without free kinetic term . In both cases
phenomenologically acceptable solutions have been found. Some solutions
describe essentially dark energy behavior, and and some solutions contain the
decelerated and accelerated phases.Comment: 21 page
Behaviour and attitudes in HIV (BEAHIV): a national survey study to examine the level of agreement between physicians and patients in symptom reporting
Improved linear response for stochastically driven systems
The recently developed short-time linear response algorithm, which predicts
the average response of a nonlinear chaotic system with forcing and dissipation
to small external perturbation, generally yields high precision of the response
prediction, although suffers from numerical instability for long response times
due to positive Lyapunov exponents. However, in the case of stochastically
driven dynamics, one typically resorts to the classical fluctuation-dissipation
formula, which has the drawback of explicitly requiring the probability density
of the statistical state together with its derivative for computation, which
might not be available with sufficient precision in the case of complex
dynamics (usually a Gaussian approximation is used). Here we adapt the
short-time linear response formula for stochastically driven dynamics, and
observe that, for short and moderate response times before numerical
instability develops, it is generally superior to the classical formula with
Gaussian approximation for both the additive and multiplicative stochastic
forcing. Additionally, a suitable blending with classical formula for longer
response times eliminates numerical instability and provides an improved
response prediction even for long response times
Predictability in Systems with Many Characteristic Times: The Case of Turbulence
In chaotic dynamical systems, an infinitesimal perturbation is exponentially
amplified at a time-rate given by the inverse of the maximum Lyapunov exponent
. In fully developed turbulence, grows as a power of the
Reynolds number. This result could seem in contrast with phenomenological
arguments suggesting that, as a consequence of `physical' perturbations, the
predictability time is roughly given by the characteristic life-time of the
large scale structures, and hence independent of the Reynolds number. We show
that such a situation is present in generic systems with many degrees of
freedom, since the growth of a non-infinitesimal perturbation is determined by
cumulative effects of many different characteristic times and is unrelated to
the maximum Lyapunov exponent. Our results are illustrated in a chain of
coupled maps and in a shell model for the energy cascade in turbulence.Comment: 24 pages, 10 Postscript figures (included), RevTeX 3.0, files packed
with uufile
Growth of non-infinitesimal perturbations in turbulence
We discuss the effects of finite perturbations in fully developed turbulence
by introducing a measure of the chaoticity degree associated to a given scale
of the velocity field. This allows one to determine the predictability time for
non-infinitesimal perturbations, generalizing the usual concept of maximum
Lyapunov exponent. We also determine the scaling law for our indicator in the
framework of the multifractal approach. We find that the scaling exponent is
not sensitive to intermittency corrections, but is an invariant of the
multifractal models. A numerical test of the results is performed in the shell
model for the turbulent energy cascade.Comment: 4 pages, 2 Postscript figures (included), RevTeX 3.0, files packed
with uufile
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