8,949 research outputs found
Shadows and Twisted Variables
We explain how a new type of fields called shadows and the use of twisted
variables allow for a better description of Yang-Mills supersymmetric theories.
(Based on lectures given in Cargese, June 2006.)Comment: Cargese Jun 200
Propagation of seismic waves through a spatio-temporally fluctuating medium: Homogenization
Measurements of seismic wave travel times at the photosphere of the Sun have
enabled inferences of its interior structure and dynamics. In interpreting
these measurements, the simplifying assumption that waves propagate through a
temporally stationary medium is almost universally invoked. However, the Sun is
in a constant state of evolution, on a broad range of spatio-temporal scales.
At the zero wavelength limit, i.e., when the wavelength is much shorter than
the scale over which the medium varies, the WKBJ (ray) approximation may be
applied. Here, we address the other asymptotic end of the spectrum, the
infinite wavelength limit, using the technique of homogenization. We apply
homogenization to scenarios where waves are propagating through rapidly varying
media (spatially and temporally), and derive effective models for the media.
One consequence is that a scalar sound speed becomes a tensorial wavespeed in
the effective model and anisotropies can be induced depending on the nature of
the perturbation. The second term in this asymptotic two-scale expansion, the
so-called corrector, contains contributions due to higher-order scattering,
leading to the decoherence of the wavefield. This decoherence may be causally
linked to the observed wave attenuation in the Sun. Although the examples we
consider here consist of periodic arrays of perturbations to the background,
homogenization may be extended to ergodic and stationary random media. This
method may have broad implications for the manner in which we interpret seismic
measurements in the Sun and for modeling the effects of granulation on the
scattering of waves and distortion of normal-mode eigenfunctions.Comment: 17 pages, 6 figures, in press, Ap
Optimization of TFRC loss history initialization
This letter deals with the initialization of the loss
history structure in the TFRC (TCP-Friendly Rate Control)
mechanism. This initialization occurs after the detection of the first loss event after every slowstart phase. The loss history is crucial for the algorithm since it returns the packet loss rate estimation. This estimation is used in the TFRC equation to compute the sending rate. In this letter, we propose a new method to compute the packet loss rate which is more computationally efficient and remains as accurate as the classical commonly used method. The motivation of this work is to reduce the computation
time and formulate a unified computation scheme. This method is based on the Newton’s algorithm issued from numerical analysis of the TCP throughput equation. This proposal is evaluated analytically and the results show a significant improvement in terms of the computation time
Twisted Superspace
We formulate the ten-dimensional super-Yang-Mills theory in a twisted
superspace with 8+1 supercharges. Its constraints do not imply the equations of
motion and we solve them. As a preliminary step for a complete formulation in a
twisted superspace, we give a superspace path-integral formulation of the N=2,
d=4 super-Yang-Mills theory without matter. The action is the sum of a
Chern--Simons term depending on a super-connection plus a BF-like term. The
integration over the superfield B implements the twisted superspace constraints
on the super-gauge field, and the Chern-Simons action reduces to the known
action in components
From calls to communities: a model for time varying social networks
Social interactions vary in time and appear to be driven by intrinsic
mechanisms, which in turn shape the emerging structure of the social network.
Large-scale empirical observations of social interaction structure have become
possible only recently, and modelling their dynamics is an actual challenge.
Here we propose a temporal network model which builds on the framework of
activity-driven time-varying networks with memory. The model also integrates
key mechanisms that drive the formation of social ties - social reinforcement,
focal closure and cyclic closure, which have been shown to give rise to
community structure and the global connectedness of the network. We compare the
proposed model with a real-world time-varying network of mobile phone
communication and show that they share several characteristics from
heterogeneous degrees and weights to rich community structure. Further, the
strong and weak ties that emerge from the model follow similar weight-topology
correlations as real-world social networks, including the role of weak ties.Comment: 10 pages, 5 figure
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