11,276 research outputs found
Chimera and globally clustered chimera: Impact of time delay
Following a short report of our preliminary results [Phys. Rev. E 79,
055203(R) (2009)], we present a more detailed study of the effects of coupling
delay in diffusively coupled phase oscillator populations. We find that
coupling delay induces chimera and globally clustered chimera (GCC) states in
delay coupled populations. We show the existence of multi-clustered states that
act as link between the chimera and the GCC states. A stable GCC state goes
through a variety of GCC states, namely periodic, aperiodic, long-- and
short--period breathers and becomes unstable GCC leading to global
synchronization in the system, on increasing time delay. We provide numerical
evidence and theoretical explanations for the above results and discuss
possible applications of the observed phenomena.Comment: 10 pages, 10 figures, Accepted in Phys. Rev.
Globally clustered chimera states in delay--coupled populations
We have identified the existence of globally clustered chimera states in
delay coupled oscillator populations and find that these states can breathe
periodically, aperiodically and become unstable depending upon the value of
coupling delay. We also find that the coupling delay induces frequency
suppression in the desynchronized group. We provide numerical evidence and
theoretical explanations for the above results and discuss possible
applications of the observed phenomena.Comment: Accepted in Phys. Rev. E as a Rapid Communicatio
Exciton mediated one phonon resonant Raman scattering from one-dimensional systems
We use the Kramers-Heisenberg approach to derive a general expression for the
resonant Raman scattering cross section from a one-dimensional (1D) system
explicitly accounting for excitonic effects. The result should prove useful for
analyzing the Raman resonance excitation profile lineshapes for a variety of 1D
systems including carbon nanotubes and semiconductor quantum wires. We apply
this formalism to a simple 1D model system to illustrate the similarities and
differences between the free electron and correlated electron-hole theories.Comment: 10 pages, 6 figure
Adaptive intelligence applied to numerical optimisation
The article presents modification strategies theoretical comparison and experimental results achieved by adaptive heuristics applied to numerical optimisation of several non-constraint test functions. The aims of the study are to identify and compare how adaptive search heuristics behave within heterogeneous search space without retuning of the search parameters. The achieved results are summarised and analysed, which could be used for comparison to other methods and further investigation
Chirality dependence of the radial breathing phonon mode density in single wall carbon nanotubes
A mass and spring model is used to calculate the phonon mode dispersion for
single wall carbon nanotubes (SWNTs) of arbitrary chirality. The calculated
dispersions are used to determine the chirality dependence of the radial
breathing phonon mode (RBM) density. Van Hove singularities, usually discussed
in the context of the single particle electronic excitation spectrum, are found
in the RBM density of states with distinct qualitative differences for zig zag,
armchair and chiral SWNTs. The influence the phonon mode density has on the two
phonon resonant Raman scattering cross-section is discussed.Comment: 6 pages, 2 figures, submitted to Phys. Rev.
Some Issues in a Gauge Model of Unparticles
We address in a recent gauge model of unparticles the issues that are
important for consistency of a gauge theory, i.e., unitarity and Ward identity
of physical amplitudes. We find that non-integrable singularities arise in
physical quantities like cross section and decay rate from gauge interactions
of unparticles. We also show that Ward identity is violated due to the lack of
a dispersion relation for charged unparticles although the Ward-Takahashi
identity for general Green functions is incorporated in the model. A previous
observation that the unparticle's (with scaling dimension d) contribution to
the gauge boson self-energy is a factor (2-d) of the particle's has been
extended to the Green function of triple gauge bosons. This (2-d) rule may be
generally true for any point Green functions of gauge bosons. This implies that
the model would be trivial even as one that mimics certain dynamical effects on
gauge bosons in which unparticles serve as an interpolating field.Comment: v1:16 pages, 3 figures. v2: some clarifications made and presentation
improved, calculation and conclusion not modified; refs added and updated.
Version to appear in EPJ
A self-organizing random immigrants genetic algorithm for dynamic optimization problems
This is the post-print version of the article. The official published version can be obtained from the link below - Copyright @ 2007 SpringerIn this paper a genetic algorithm is proposed where the worst individual and individuals with indices close to its index are replaced in every generation by randomly generated individuals for dynamic optimization problems. In the proposed genetic algorithm, the replacement of an individual can affect other individuals in a chain reaction. The new individuals are preserved in a subpopulation which is defined by the number of individuals created in the current chain reaction. If the values of fitness are similar, as is the case with small diversity, one single replacement can affect a large number of individuals in the population. This simple approach can take the system to a self-organizing behavior, which can be useful to control the diversity level of the population and hence allows the genetic algorithm to escape from local optima once the problem changes due to the dynamics.This work was supported by FAPESP (Proc. 04/04289-6)
Continuous Statistical Models: With or Without Truncation Parameters?
Lifetime data are usually assumed to stem from a continuous distribution supported on [0, b) for some b ≤ ∞. The continuity assumption implies that the support of the distribution does not have atom points, particularly not at 0. Accordingly, it seems reasonable that with an accurate measurement tool all data observations will be positive. This suggests that the true support may be truncated from the left. In this work we investigate the effects of adding a left truncation parameter to a continuous lifetime data statistical model. We consider two main settings: right truncation parametric models with possible left truncation, and exponential family models with possible left truncation. We analyze the performance of some optimal estimators constructed under the assumption of no left truncation when left truncation is present, and vice versa. We investigate both asymptotic and finite-sample behavior of the estimators. We show that when left truncation is not assumed but is, in fact present, the estimators have a constant bias term, and therefore will result in inaccurate and inefficient estimation. We also show that assuming left truncation where actually there is none, typically does not result in substantial inefficiency, and some estimators in this case are asymptotically unbiased and efficient
Evolution of constrained layer damping using a cellular automaton algorithm
Constrained layer damping (CLD) is a highly effective passive vibration control strategy if optimized adequately. Factors controlling CLD performance are well documented for the flexural modes of beams but not for more complicated mode shapes or structures. The current paper introduces an approach that is suitable for locating CLD on any type of structure. It follows the cellular automaton (CA) principle and relies on the use of finite element models to describe the vibration properties of the structure. The ability of the algorithm to reach the best solution is demonstrated by applying it to the bending and torsion modes of a plate. Configurations that give the most weight-efficient coverage for each type of mode are first obtained by adapting the existing 'optimum length' principle used for treated beams. Next, a CA algorithm is developed, which grows CLD patches one at a time on the surface of the plate according to a simple set of rules. The effectiveness of the algorithm is then assessed by comparing the generated configurations with the known optimum ones
Conformative Filtering for Implicit Feedback Data
Implicit feedback is the simplest form of user feedback that can be used for
item recommendation. It is easy to collect and is domain independent. However,
there is a lack of negative examples. Previous work tackles this problem by
assuming that users are not interested or not as much interested in the
unconsumed items. Those assumptions are often severely violated since
non-consumption can be due to factors like unawareness or lack of resources.
Therefore, non-consumption by a user does not always mean disinterest or
irrelevance. In this paper, we propose a novel method called Conformative
Filtering (CoF) to address the issue. The motivating observation is that if
there is a large group of users who share the same taste and none of them have
consumed an item before, then it is likely that the item is not of interest to
the group. We perform multidimensional clustering on implicit feedback data
using hierarchical latent tree analysis (HLTA) to identify user `tastes' groups
and make recommendations for a user based on her memberships in the groups and
on the past behavior of the groups. Experiments on two real-world datasets from
different domains show that CoF has superior performance compared to several
common baselines
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