25,323 research outputs found
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 blind deconvolution approach to recover effective connectivity brain networks from resting state fMRI data
A great improvement to the insight on brain function that we can get from
fMRI data can come from effective connectivity analysis, in which the flow of
information between even remote brain regions is inferred by the parameters of
a predictive dynamical model. As opposed to biologically inspired models, some
techniques as Granger causality (GC) are purely data-driven and rely on
statistical prediction and temporal precedence. While powerful and widely
applicable, this approach could suffer from two main limitations when applied
to BOLD fMRI data: confounding effect of hemodynamic response function (HRF)
and conditioning to a large number of variables in presence of short time
series. For task-related fMRI, neural population dynamics can be captured by
modeling signal dynamics with explicit exogenous inputs; for resting-state fMRI
on the other hand, the absence of explicit inputs makes this task more
difficult, unless relying on some specific prior physiological hypothesis. In
order to overcome these issues and to allow a more general approach, here we
present a simple and novel blind-deconvolution technique for BOLD-fMRI signal.
Coming to the second limitation, a fully multivariate conditioning with short
and noisy data leads to computational problems due to overfitting. Furthermore,
conceptual issues arise in presence of redundancy. We thus apply partial
conditioning to a limited subset of variables in the framework of information
theory, as recently proposed. Mixing these two improvements we compare the
differences between BOLD and deconvolved BOLD level effective networks and draw
some conclusions
Deformation of a Trapped Fermi Gas with Unequal Spin Populations
The real-space densities of a polarized strongly-interacting two-component
Fermi gas of Li atoms reveal two low temperature regimes, both with a
fully-paired core. At the lowest temperatures, the unpolarized core deforms
with increasing polarization. Sharp boundaries between the core and the excess
unpaired atoms are consistent with a phase separation driven by a first-order
phase transition. In contrast, at higher temperatures the core does not deform
but remains unpolarized up to a critical polarization. The boundaries are not
sharp in this case, indicating a partially-polarized shell between the core and
the unpaired atoms. The temperature dependence is consistent with a tricritical
point in the phase diagram.Comment: Accepted for publication in Physical Review Letter
Electronic structures of [001]- and [111]-oriented InSb and GaSb free-standing nanowires
We report on a theoretical study of the electronic structures of InSb and
GaSb nanowires oriented along the [001] and [111] crystallographic directions.
The nanowires are described by atomistic, spin-orbit inteaction included,
tight-binding models, and the band structures and the wave functions of the
nanowires are calculated by means of a Lanczos iteration algorithm. For the
[001]-oriented InSb and GaSb nanowires, the systems with both square and
rectangular cross sections are considered. Here, it is found that all the
energy bands are double degenerate. Furthermore, although the lowest conduction
bands in these nanowires show good parabolic dispersions, the top valence bands
show rich and complex structures. In particular, the topmost valence bands of
these nanowires with a square cross section show a double maximum structure. In
the nanowires with a rectangular cross section, this double maximum structure
is suppressed and top valence bands gradually develop into parabolic bands as
the aspect ratio of the cross section is increased. For the [111]-oriented InSb
and GaSb nanowires, the systems with hexagonal cross sections are considered.
It is found that all the bands at the \Gamma-point are again double degenerate.
However, some of them will split into non-degenerate bands when the wave vector
moves away from the \Gamma-point. Furthermore, although the lowest conduction
bands again show good parabolic dispersions, the topmost valence bands do not
show the double maximum structure but, instead, a single maximum structure with
its maximum at a wave vector slightly away from the \Gamma-point. We also
investigate the effects of quantum confinement on the band structures of the
[001]- and [111]-oriented InSb and GaSb nanowires and present an empirical
formula for the description of quantization energies of the band edge states in
the nanowires.Comment: 17 pages, 19 figure
Resisting skew-accumulation for time-stepped applications in the cloud via exploiting parallelism
This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Time-stepped applications are pervasive in scientific computing domain but perform poorly in the cloud because these applications execute in discrete time-step or tick and use logical synchronization barriers at tick boundaries to ensure correctness. As a result, the accumulated computational skew and communication skew that were unsolved in each tick can slow downtime-stepped applications significantly. However, the existing solutions have focused only on the skew in each tick and thus cannot resist the accumulation of skew. To fill in this gap, an efficient approach to resisting the accumulation of skew is proposed in this paper via fully exploiting parallelism among ticks. This new approach allows the user to decompose much computational part (also called asynchronous part) of the processing for an object, into several asynchronous sub-processes which are dependent on one data object. Each sub-process from different ticks can then proceed in advance using the idle time whenever the needed data object is available, redressing the negative effects caused by accumulated unsolved computational and communication skew. To efficiently support such an approach, a data-centric programming model and also a runtime system, namely AsyTick, coupled with an ad hoc scheduler are developed. Experimental results show that the proposed approach can improve the performance of time-stepped applications over a state-of-the-art computational skew-resistant approach up to 2.53 times.This paper is supported by China National Natural
Science Foundation under grant No. 61272408,
61322210, National High-tech Research and Development
Program of China (863 Program) under grant
No.2012AA010905, CCCPC Youngth Talent Plan, Doctoral
Fund of Ministry of Education of China under
grant No. 20130142110048
Gauge Consistent Wilson Renormalization Group I: Abelian Case
A version of the Wilson Renormalization Group Equation consistent with gauge
symmetry is presented. A perturbative renormalizability proof is established. A
wilsonian derivation of the Callan-Symanzik equation is given.Comment: Latex2e, 39 pages, 3 eps figures. Revised version to appear in Int.
J. Mod. Phy
Simulating Ability: Representing Skills in Games
Throughout the history of games, representing the abilities of the various
agents acting on behalf of the players has been a central concern. With
increasingly sophisticated games emerging, these simulations have become more
realistic, but the underlying mechanisms are still, to a large extent, of an ad
hoc nature. This paper proposes using a logistic model from psychometrics as a
unified mechanism for task resolution in simulation-oriented games
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