378 research outputs found
On Optimal Detection of Point Sources in CMB Maps
Point-source contamination in high-precision Cosmic Microwave Background
(CMB) maps severely affects the precision of cosmological parameter estimates.
Among the methods that have been proposed for source detection, wavelet
techniques based on ``optimal'' filters have been proposed.In this paper we
show that these filters are in fact only restrictive cases of a more general
class of matched filters that optimize signal-to-noise ratio and that have, in
general, better source detection capabilities, especially for lower amplitude
sources. These conclusions are confirmed by some numerical experiments.
\keywords{Methods: data analysis -- Methods: statisticalComment: 6 pages, 3 figure
Statistical properties of dust far-infrared emission
The description of the statistical properties of dust emission gives
important constraints on the physics of the interstellar medium but it is also
a useful way to estimate the contamination of diffuse interstellar emission in
the cases where it is considered a nuisance. The main goals of this analysis of
the power spectrum and non-Gaussian properties of 100 micron dust emission are
1) to estimate the power spectrum of interstellar matter density in three
dimensions, 2) to review and extend previous estimates of the cirrus noise due
to dust emission and 3) to produce simulated dust emission maps that reproduce
the observed statistical properties. The main results are the following. 1) The
cirrus noise level as a function of brightness has been previously
overestimated. It is found to be proportional to instead of ^1.5, where
is the local average brightness at 100 micron. This scaling is in
accordance with the fact that the brightness fluctuation level observed at a
given angular scale on the sky is the sum of fluctuations of increasing
amplitude with distance on the line of sight. 2) The spectral index of dust
emission at scales between 5 arcmin and 12.5 degrees is =-2.9 on average
but shows significant variations over the sky. Bright regions have
systematically steeper power spectra than diffuse regions. 3) The skewness and
kurtosis of brightness fluctuations is high, indicative of strong
non-Gaussianity. 4) Based on our characterization of the 100 micron power
spectrum we provide a prescription of the cirrus confusion noise as a function
of wavelength and scale. 5) Finally we present a method based on a modification
of Gaussian random fields to produce simulations of dust maps which reproduce
the power spectrum and non-Gaussian properties of interstellar dust emission.Comment: 13 pages, 13 figures. Accepted for publication in A&
Digital Deblurring of CMB Maps II: Asymmetric Point Spread Function
In this second paper in a series dedicated to developing efficient numerical
techniques for the deblurring Cosmic Microwave Background (CMB) maps, we
consider the case of asymmetric point spread functions (PSF). Although
conceptually this problem is not different from the symmetric case, there are
important differences from the computational point of view because it is no
longer possible to use some of the efficient numerical techniques that work
with symmetric PSFs. We present procedures that permit the use of efficient
techniques even when this condition is not met. In particular, two methods are
considered: a procedure based on a Kronecker approximation technique that can
be implemented with the numerical methods used with symmetric PSFs but that has
the limitation of requiring only mildly asymmetric PSFs. The second is a
variant of the classic Tikhonov technique that works even with very asymmetric
PSFs but that requires discarding the edges of the maps. We provide details for
efficient implementations of the algorithms. Their performance is tested on
simulated CMB maps.Comment: 9 pages, 13 Figure
A simple but efficient algorithm for multiple-image deblurring
We consider the simultaneous deblurring of a set of noisy images whose point
spread functions are different but known and spatially invariant, and the noise
is Gaussian. Currently available iterative algorithms that are typically used
for this type of problem are computationally expensive, which makes their
application for very large images impractical. We present a simple extension of
a classical least-squares (LS) method where the multi-image deblurring is
efficiently reduced to a computationally efficient single-image deblurring. In
particular, we show that it is possible to remarkably improve the
ill-conditioning of the LS problem by means of stable operations on the
corresponding normal equations, which in turn speed up the convergence rate of
the iterative algorithms. The performance and limitations of the method are
analyzed through numerical simulations. Its connection with a column weighted
least-squares approach is also considered in an appendix.Comment: 9 pages, 16 figures. High resolution figures available upon demand.
To appear in A&
Estimation of Regularization Parameters in Multiple-Image Deblurring
We consider the estimation of the regularization parameter for the
simultaneous deblurring of multiple noisy images via Tikhonov regularization.
We approach the problem in three ways. We first reduce the problem to a
single-image deblurring for which the regularization parameter can be estimated
through a classic generalized cross-validation (GCV) method. A modification of
this function is used for correcting the undersmoothing typical of the original
technique. With a second method, we minimize an average least-squares fit to
the images and define a new GCV function. In the last approach, we use the
classical on a single higher-dimensional image obtained by concatanating
all the images into a single vector. With a reliable estimator of the
regularization parameter, one can fully exploit the excellent computational
characteristics typical of direct deblurring methods, which, especially for
large images, makes them competitive with the more flexible but much slower
iterative algorithms. The performance of the techniques is analyzed through
numerical experiments. We find that under the independent homoscedastic and
Gaussian assumptions made on the noise, the three approaches provide almost
identical results with the first single image providing the practical advantage
that no new software is required and the same image can be used with other
deblurring algorithms.Comment: To appear in Astronomy & Astrophysic
Hábitat popular y condiciones de vida de los hogares recuperadores del partido de San Martín en la posconvertibilidad
This article analyses the living conditions of a segment of the popular classes whose social strategies of reproduction involve informal access to land and housing on the one hand – either by participating in the spontaneous and/or organized occupation of lands, or by buying lands away from the registry of the regulatory institutions – and work in the recovery of solid urban waste on the other, in order to obtain both use values and a household income. It proposes to illustrate the relations that can be established between these social reproduction strategies and the living conditions these households achieve.Fil: Vio, Marcela L. CONICETFil: Vio, Marcela L. Facultad de Arquitectura, Diseño y Urbanismo. Universidad de Buenos AiresFil: Vio, Marcela L. Universidad Nacional de AvellanedaO artigo analisa as condições de vida de uma parcela das classes populares, onde sua matriz de estratégias de reprodução social apela à informalidade para resolver suas necessidades habitacionais – participando em processos de ocupações de terras organizadas ou espontâneas, comprando terra e/ou moradia por fora dos requisitos previstos pelas instituições que regulam essas operações – e à recuperação de resíduos sólidos urbanos para obter bens e ingressos. Propõe-se aclarar as relações que podem ser estabelecidas entre as estretégias de obtenção de bens e ingressos vinculadas à recuperação de resíduos e as condições de vida que adquirem os lares que alcançam sua reprodução social principalmente por esta via.El artículo analiza las condiciones de vida de una fracción de las clases populares que en su matriz de estrategias de reproducción social ha recurrido a la informalidad para resolver sus necesidades habitacionales —participando en procesos de tomas de tierra organizadas u ocupaciones espontáneas, y/o comprando suelo y/o vivienda por fuera de los requerimientos registrales previstos por las instituciones que regulan estas operaciones— y a la recuperación de desechos sólidos urbanos1 para obtener bienes e ingresos. Se propone iluminar las relaciones que pueden establecerse entre las estrategias de obtención de bienes e ingresos vinculadas a la recuperación de desechos y las condiciones de vida que alcanzan los hogares que logran su reproducción social principalmente por esta vía
QPOs: Einstein's gravity non-linear resonances
There is strong evidence that the observed kHz Quasi Periodic Oscillations
(QPOs) in the X-ray flux of neutron star and black hole sources in LMXRBs are
linked to Einstein's General Relativity. Abramowicz&Klu\'zniak (2001) suggested
a non-linear resonance model to explain the QPOs origin: here we summarize
their idea and the development of a mathematical toy-model which begins to
throw light on the nature of Einstein's gravity non-linear oscillations.Comment: Proceeding of the Einstein's Legacy, Munich 200
A Cross-Validation Approach to Approximate Basis Function Selection of the Stall Flutter Response of a Rectangular Wing in a Wind Tunnel
The stall flutter response of a rectangular wing in a low speed wind tunnel is modelled using a nonlinear difference equation description. Static and dynamic tests are used to select a suitable model structure and basis function. Bifurcation criteria such as the Hopf condition and vibration amplitude variation with airspeed were used to ensure the model was representative of experimentally measured stall flutter phenomena. Dynamic test data were used to estimate model parameters and estimate an approximate basis function
Filter design for the detection of compact sources based on the Neyman-Pearson detector
This paper considers the problem of compact source detection on a Gaussian
background in 1D. Two aspects of this problem are considered: the design of the
detector and the filtering of the data. Our detection scheme is based on local
maxima and it takes into account not only the amplitude but also the curvature
of the maxima. A Neyman-Pearson test is used to define the region of
acceptance, that is given by a sufficient linear detector that is independent
on the amplitude distribution of the sources. We study how detection can be
enhanced by means of linear filters with a scaling parameter and compare some
of them (the Mexican Hat wavelet, the matched and the scale-adaptive filters).
We introduce a new filter, that depends on two free parameters (biparametric
scale-adaptive filter). The value of these two parameters can be determined,
given the a priori pdf of the amplitudes of the sources, such that the filter
optimizes the performance of the detector in the sense that it gives the
maximum number of real detections once fixed the number density of spurious
sources. The combination of a detection scheme that includes information on the
curvature and a flexible filter that incorporates two free parameters (one of
them a scaling) improves significantly the number of detections in some
interesting cases. In particular, for the case of weak sources embedded in
white noise the improvement with respect to the standard matched filter is of
the order of 40%. Finally, an estimation of the amplitude of the source is
introduced and it is proven that such an estimator is unbiased and it has
maximum efficiency. We perform numerical simulations to test these theoretical
ideas and conclude that the results of the simulations agree with the
analytical ones.Comment: 15 pages, 13 figures, version accepted for publication in MNRAS.
Corrected typos in Tab.
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