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 $GCV$ 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.