102,193 research outputs found
Gravitational Lensing and Anisotropies of CBR on the Small Angular Scales
We investigate the effect of gravitational lensing, produced by linear
density perturbations, for anisotropies of the Cosmic Background Radiation
(CBR) on scales of arcminutes. In calculations, a flat universe ()
and the Harrison-Zel'dovich spectrum () are assumed. The numerical results
show that on scales of a few arcminutes, gravitational lensing produces only
negligible anisotropies in the temperature of the CBR. Our conclusion disagrees
with that of Cay\'{o}n {\it et al.} who argue that the amplification of on scales may even be larger than 100\%.Comment: Accepted by MNRAS. 16 pages, 2 figures, tarred, compressed and
uuencoded Postscript file
Rotor-to-stator rub vibration in centrifugal compressor
One example of excessive vibration encountered during loading of a centrifugal compressor train (H type compressor with HP casing) is discussed. An investigation was made of the effects of the dynamic load on the bearing stiffness and the rotor-bearing system critical speed. The high vibration occurred at a "threshold load," but the machine didn't run smoothly due to rubs even when it had passed through the threshold load. The acquisition and discussion of the data taken in the field as well as a description of the case history which utilizes background information to identify the malfunction conditions is presented. The analysis shows that the failures, including full reverse precession rub and exact one half subharmonic vibration, were caused by the oversize bearings and displacement of the rotor center due to foundation deformation and misalignment between gear shafts, etc. The corrective actions taken to alleviate excessive vibration and the problems which remain to be solved are also presented
On the Triality Theory for a Quartic Polynomial Optimization Problem
This paper presents a detailed proof of the triality theorem for a class of
fourth-order polynomial optimization problems. The method is based on linear
algebra but it solves an open problem on the double-min duality left in 2003.
Results show that the triality theory holds strongly in a tri-duality form if
the primal problem and its canonical dual have the same dimension; otherwise,
both the canonical min-max duality and the double-max duality still hold
strongly, but the double-min duality holds weakly in a symmetrical form. Four
numerical examples are presented to illustrate that this theory can be used to
identify not only the global minimum, but also the largest local minimum and
local maximum.Comment: 16 pages, 1 figure; J. Industrial and Management Optimization, 2011.
arXiv admin note: substantial text overlap with arXiv:1104.297
Semiclassical quantization with bifurcating orbits
Bifurcations of classical orbits introduce divergences into semiclassical
spectra which have to be smoothed with the help of uniform approximations. We
develop a technique to extract individual energy levels from semiclassical
spectra involving uniform approximations. As a prototype example, the method is
shown to yield excellent results for photo-absorption spectra for the hydrogen
atom in an electric field in a spectral range where the abundance of
bifurcations would render the standard closed-orbit formula without uniform
approximations useless. Our method immediately applies to semiclassical trace
formulae as well as closed-orbit theory and offers a general technique for the
semiclassical quantization of arbitrary systems
Random attractors for stochastic evolution equations driven by fractional Brownian motion
The main goal of this article is to prove the existence of a random attractor
for a stochastic evolution equation driven by a fractional Brownian motion with
. We would like to emphasize that we do not use the usual
cohomology method, consisting of transforming the stochastic equation into a
random one, but we deal directly with the stochastic equation. In particular,
in order to get adequate a priori estimates of the solution needed for the
existence of an absorbing ball, we will introduce stopping times to control the
size of the noise. In a first part of this article we shall obtain the
existence of a pullback attractor for the non-autonomous dynamical system
generated by the pathwise mild solution of an nonlinear infinite-dimensional
evolution equation with non--trivial H\"older continuous driving function. In a
second part, we shall consider the random setup: stochastic equations having as
driving process a fractional Brownian motion with . Under a
smallness condition for that noise we will show the existence and uniqueness of
a random attractor for the stochastic evolution equation
Simple scheme for two-qubit Grover search in cavity QED
Following the proposal by F. Yamaguchi et al.[Phys. Rev. A 66, 010302 (R)
(2002)], we present an alternative way to implement the two-qubit Grover search
algorithm in cavity QED. Compared with F. Yamaguchi et al.'s proposal, with a
strong resonant classical field added, our method is insensitive to both the
cavity decay and thermal field, and doesn't require that the cavity remain in
the vacuum state throughout the procedure. Moreover, the qubit definitions are
the same for both atoms, which makes the experiment easier. The strictly
numerical simulation shows that our proposal is good enough to demonstrate a
two-qubit Grover's search with high fidelity.Comment: manuscript 10 pages, 2 figures, to appear in Phys. Rev.
Combining Models of Approximation with Partial Learning
In Gold's framework of inductive inference, the model of partial learning
requires the learner to output exactly one correct index for the target object
and only the target object infinitely often. Since infinitely many of the
learner's hypotheses may be incorrect, it is not obvious whether a partial
learner can be modifed to "approximate" the target object.
Fulk and Jain (Approximate inference and scientific method. Information and
Computation 114(2):179--191, 1994) introduced a model of approximate learning
of recursive functions. The present work extends their research and solves an
open problem of Fulk and Jain by showing that there is a learner which
approximates and partially identifies every recursive function by outputting a
sequence of hypotheses which, in addition, are also almost all finite variants
of the target function.
The subsequent study is dedicated to the question how these findings
generalise to the learning of r.e. languages from positive data. Here three
variants of approximate learning will be introduced and investigated with
respect to the question whether they can be combined with partial learning.
Following the line of Fulk and Jain's research, further investigations provide
conditions under which partial language learners can eventually output only
finite variants of the target language. The combinabilities of other partial
learning criteria will also be briefly studied.Comment: 28 page
Halo assembly bias and its effects on galaxy clustering
The clustering of dark halos depends not only on their mass but also on their
assembly history, a dependence we term `assembly bias'. Using a galaxy
formation model grafted onto the Millennium Simulation of the LCDM cosmogony,
we study how assembly bias affects galaxy clustering. We compare the original
simulation to `shuffled' versions where the galaxy populations are randomly
swapped among halos of similar mass, thus isolating the effects of correlations
between assembly history and environment at fixed mass. Such correlations are
ignored in the halo occupation distribution models often used populate dark
matter simulations with galaxies, but they are significant in our more
realistic simulation. Assembly bias enhances 2-point correlations by 10% for
galaxies with M_bJ-5logh brighter than -17, but suppresses them by a similar
amount for galaxies brighter than -20. When such samples are split by colour,
assembly bias is 5% stronger for red galaxies and 5% weaker for blue ones. Halo
central galaxies are differently affected by assembly bias than are galaxies of
all types. It almost doubles the correlation amplitude for faint red central
galaxies. Shuffling galaxies among halos of fixed formation redshift or
concentration in addition to fixed mass produces biases which are not much
smaller than when mass alone is fixed. Assembly bias must reflect a correlation
of environment with aspects of halo assembly which are not encoded in either of
these parameters. It induces effects which could compromise precision
measurements of cosmological parameters from large galaxy surveys.Comment: 8 pages, 4 figures, accepted for publication in MNRA
Independence Test for High Dimensional Random Vectors
This paper proposes a new mutual independence test for a large number of high dimensional random vectors. The test statistic is based on the characteristic function of the empirical spectral distribution of the sample covariance matrix. The asymptotic distributions of the test statistic under the null and local alternative hypotheses are established as dimensionality and the sample size of the data are comparable. We apply this test to examine multiple MA(1) and AR(1) models, panel data models with some spatial cross-sectional structures. In addition, in a flexible applied fashion, the proposed test can capture some dependent but uncorrelated structures, for example, nonlinear MA(1) models, multiple ARCH(1) models and vandermonde matrices. Simulation results are provided for detecting these dependent structures. An empirical study of dependence between closed stock prices of several companies from New York Stock Exchange (NYSE) demonstrates that the feature of cross-sectional dependence is popular in stock marketsIndependence test, cross-sectional dependence, empirical spectral distribution, characteristic function, Marcenko-Pastur Law
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