5,312 research outputs found
A new source detection algorithm using FDR
The False Discovery Rate (FDR) method has recently been described by Miller
et al (2001), along with several examples of astrophysical applications. FDR is
a new statistical procedure due to Benjamini and Hochberg (1995) for
controlling the fraction of false positives when performing multiple hypothesis
testing. The importance of this method to source detection algorithms is
immediately clear. To explore the possibilities offered we have developed a new
task for performing source detection in radio-telescope images, Sfind 2.0,
which implements FDR. We compare Sfind 2.0 with two other source detection and
measurement tasks, Imsad and SExtractor, and comment on several issues arising
from the nature of the correlation between nearby pixels and the necessary
assumption of the null hypothesis. The strong suggestion is made that
implementing FDR as a threshold defining method in other existing
source-detection tasks is easy and worthwhile. We show that the constraint on
the fraction of false detections as specified by FDR holds true even for highly
correlated and realistic images. For the detection of true sources, which are
complex combinations of source-pixels, this constraint appears to be somewhat
less strict. It is still reliable enough, however, for a priori estimates of
the fraction of false source detections to be robust and realistic.Comment: 17 pages, 7 figures, accepted for publication by A
Image Coaddition with Temporally Varying Kernels
Large, multi-frequency imaging surveys, such as the Large Synaptic Survey
Telescope (LSST), need to do near-real time analysis of very large datasets.
This raises a host of statistical and computational problems where standard
methods do not work. In this paper, we study a proposed method for combining
stacks of images into a single summary image, sometimes referred to as a
template. This task is commonly referred to as image coaddition. In part, we
focus on a method proposed in previous work, which outlines a procedure for
combining stacks of images in an online fashion in the Fourier domain. We
evaluate this method by comparing it to two straightforward methods through the
use of various criteria and simulations. Note that the goal is not to propose
these comparison methods for use in their own right, but to ensure that
additional complexity also provides substantially improved performance
Anomalous Spin Polarization of GaAs Two-Dimensional Hole Systems
We report measurements and calculations of the spin-subband depopulation,
induced by a parallel magnetic field, of dilute GaAs two-dimensional (2D) hole
systems. The results reveal that the shape of the confining potential
dramatically affects the values of in-plane magnetic field at which the upper
spin subband is depopulated. Most surprisingly, unlike 2D electron systems, the
carrier-carrier interaction in 2D hole systems does not significantly enhance
the spin susceptibility. We interpret our findings using a multipole expansion
of the spin density matrix, and suggest that the suppression of the enhancement
is related to the holes' band structure and effective spin j=3/2.Comment: 6 pages, 4 figures, substantially extended discussion of result
Interpretation of the angular dependence of the de Haas-van Alphen effect in MgB_2
We present detailed results for the amplitude and field dependence of the de
Haas-van Alphen (dHvA) signal arising from the electron-like sheet of
Fermi surface in MgB_2. Our data and analysis show that the dip in dHvA
amplitude when the field is close to the basal plane is caused by a beat
between two very similar dHvA frequencies and not a spin-zero effect as
previously assumed. Our results imply that the Stoner enhancement factors in
MgB_2 are small on both the Sigma and Pi sheets.Comment: 4 pages with figures. Submitted to PR
Spectral Measures of Bipartivity in Complex Networks
We introduce a quantitative measure of network bipartivity as a proportion of
even to total number of closed walks in the network. Spectral graph theory is
used to quantify how close to bipartite a network is and the extent to which
individual nodes and edges contribute to the global network bipartivity. It is
shown that the bipartivity characterizes the network structure and can be
related to the efficiency of semantic or communication networks, trophic
interactions in food webs, construction principles in metabolic networks, or
communities in social networks.Comment: 16 pages, 1 figure, 1 tabl
The Association between Pathological Internet Use and Comorbid Psychopathology: A Systematic Review
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Fingerprint for Network Topologies
A network's topology information can be given as an adjacency matrix. The
bitmap of sorted adjacency matrix(BOSAM) is a network visualisation tool which
can emphasise different network structures by just looking at reordered
adjacent matrixes. A BOSAM picture resembles the shape of a flower and is
characterised by a series of 'leaves'. Here we show and mathematically prove
that for most networks, there is a self-similar relation between the envelope
of the BOSAM leaves. This self-similar property allows us to use a single
envelope to predict all other envelopes and therefore reconstruct the outline
of a network's BOSAM picture. We analogise the BOSAM envelope to human's
fingerprint as they share a number of common features, e.g. both are simple,
easy to obtain, and strongly characteristic encoding essential information for
identification.Comment: 12papes, 3 figures, in pres
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